Unit - 6
GIS Data and Applications
Q1) Explain GIS data types and data representation
A1)
GIS DATA TYPES GIS era makes use of simple sorts of information.
These are:
1) Spatial information: describes absolutely and relative region of geographic capabilities.
2) Attribute information: describes traits of the spatial capabilities. These traits may be quantitative and/or qualitative in nature. Attribute information is frequently stated as tabular information.
SPATIAL DATA MODELS
1) Vector
2) Raster
3) Image
VECTOR
All spatial information fashions are strategies for storing the spatial region of geographic capabilities in a database. Vector garage implies the usage of vectors (directional lines) to symbolize a geographic feature.
RASTER
Raster information fashions contain the usage of a grid-mobileular information shape in which the geographic place is split into cells diagnosed via way of means of row and column. This information shape is normally known as raster.
IMAGE
Image information is most usually used to symbolize photo or pictorial information. The time period photo inherently displays a photo representation, and with inside the GIS world, differs notably from raster information.
Q2) Give advantages and disadvantages of vector information model.
A2)
Advantages of vector information model
• Data may be represented at its authentic decision and shape with out generalization.
• Graphic output is typically greater aesthetically pleasing (traditional cartographic representation);
• Since maximum information, e.g. Difficult reproduction maps, is in vector shape no information conversion is needed.
• Accurate geographic region of information is maintained.
• Allows for green encoding of topology, and as an end result greater green operations that require topological information, e.g. Proximity, community evaluation.
Disadvantages of vector information model
• The region of every vertex desires to be saved explicitly.
• For powerful evaluation, vector information ought to be transformed into a topological shape.
• Algorithms for manipulative and evaluation features are complex and can be processing intensive. Often, this inherently limits the capability for big information sets, e.g. a big wide variety of capabilities.
• Continuous information, which includes elevation information, isn't always effectively represented in vector shape. Usually giant information generalization or interpolation is needed for those information layers.
• Spatial evaluation and filtering inside polygons is impossible Advantages of raster information model
• The geographic region of every mobileular is implied via way of means of its role in the mobileular matrix.
Accordingly, aside from a foundation point, e.g. Bottom left corner, no geographic coordinates are saved.
• Due to the character of the information garage approach information evaluation is typically clean to application and short to perform.
• The inherent nature of raster maps, e.g. One characteristic maps, is perfectly suited for mathematical modeling and quantitative evaluation.
• Discrete information, e.g. Forestry stands, is accommodated similarly well as non-stop information, e.g. Elevation information, and helps the integrating of the 2 information types.
• Grid-mobileular structures are very well suited with raster-primarily based totally output devices, e.g. Electrostatic plotters, photo terminals. Disadvantages of raster information model
• The mobileular length determines the decision at which the information is represented.
• It is especially hard to competently constitute linear capabilities relying at the mobileular decision.
Accordingly, community linkages are hard to establish.
• Processing of related characteristic information can be bulky if big quantities of information exists.
Raster maps inherently mirror only one characteristic or feature for a place.
• Since maximum enter information is in vector shape, information ought to undergo vector-to-raster conversion.
Besides expanded processing necessities this will introduce information integrity issues due to generalization and desire of beside the point mobileular length.
• Most output maps from grid-mobileular structures do now no longer agree to high quality cartographic desires.
Q3) Explain Data Synthesis and Visualization
A3)
The present established programs for cartography (ESRI, ERDAS, LHS, Multispeed and etc.), permit synthesizing polygonal and hyper spectral pics.
The recognized methods, like which are described [1-3], discover multispectral pix of items to show them. These responsibilities require pixel category, which isn't always an easy operation and may be done with the aid of using numerous methods.
It takes lots time to do it. The approach offered right here does now no longer require initial category. It can therefore be used with the intention to swiftly carry out the responsibilities of visible interpretation.
We shall illustrate this approach with an instance of the synthesis of n-area aero pics. We anticipate that the pics are superimposed.
Everyone pixel of such set of the pix has n the spectral traits or attributes.
A pixel with all its attributes is chosen as a well-known version.
Apart from the spectral traits a few different attributes can be assigned to a pixel. These may be acquired by way of initial processing of every spectral photo or a hard and fast of pix.
The attributes of the usual version are as compared to the ones of all different pixels. The synthesis of the pix is produced primarily based totally on a precept of comparable attributes.
The maximum brightness is assigned to the pixels that resemble maximum the usual version. The brightness fee of the relaxation of the pixels is calculated on the idea in their resemblance with the usual version.
Different attributes may be hired as a degree of resemblance, specifically the ones which are used for category with inside the famous software programs Multispeed, ESRI, ERDAS.
It may be the Euclidean metric with inside the n-dimensional area of the attributes or the maximal distinction among values of the identical attributes. No extra data is wanted for this metrics. If the data at the opportunity distribution of the usual version attributes is recognized, one could employ the conditional probabilities (the Bayesian approach) to assess resemblance.
All the traits which have been anticipated earlier can be concerned whilst growing a resemblance metric.
The very last synthesized photo is offered in grayscale. It carries the data on a diploma of similarity of the attributes of each pixel to the ones of the usual version. The synthesis time of a photo relies upon most effective at the time had to calculate the attributes of each pixel.
When the use of most effective the experimentally measured attributes, along with the spectral values of brightness, the very last photo is fashioned in actual time, because the calculation of resemblance is done instantly.
In addition it's far of the significance that this approach entails no multiplexing. And throughput of transmitting of data is excessive.
Note, that the recognized approach “infrared satiation vision” visualizes preliminary pix in numerous spectral durations into one photo in which every of preliminary photo is submitted with the aid of using monochromatic satiatioñ red, inexperienced or blue (RGB).
But multichannel switch of the data is vital in that case.
Q4) Give various example of data representation.
A4)
EXAMPLES
- We gift the outcomes of synthesis of imaging data (aero pics of a terrestrial floor) that acquired in nine spectral bands. The Euclidean metric in nine-dimensional area of spectral attributes have been used. Pixels with numerous coordinates had been decided on as well-known models.
- The first column of discern 1 carries the pics of terrestrial floor in nine spectral ranges. In the second one column we gift the outcomes of photo synthesis.
- The maximum brightness degree is assigned to pixels with spectral attributes bearing the very best resemblance to its well-known version.
- The others pixels have the brightness placing that corresponds to the extent of resemblance of the attributes.
- The well-known version coordinates are marked subsequent to the very last pix. One can have a look at that the synthesized pix are lots greater detailed, than the pix similar to every spectral band.
- The pixels of the synthesized photo, which have an excessive degree of resemblance than a positive threshold fee, can be highlighted in color.
- The discern 2 gives the synthesis outcomes of the pics in four spectral bands with one-of-a-kind threshold values.
- Note that this photo transformation set of rules is likewise appropriate for processing panchromatic pix.
- The regions of the photo which are of greater hobby to the spectator may be emphasized with the very best brightness.
- It is plain that this processing approach can't boom the decision of a panchromatic photo except extra data is used, however it may boom its perceptibility.
- The degree of depth with inside the pics is decided with the aid of using the reflective cap potential of items and relies upon at the ecosystem condition, the exposition parameters, etc.
- The well-known version is acquired below the identical conditions; consequently the end result of the synthesis does now no longer rely on those factors. In the given instance most effective spectral values of brightness have been used as attributes.
- Apart from the measured spectral values of brightness one may want to use a few extra attributes acquired by way of processing the preliminary data: as an instance structural, contextual and textural attributes. The desire of the attributes can adjust the end result significantly.
Q5) Explain data acquisition.
A5)
Data acquisition is the method of sampling alerts that degree actual international bodily situations and changing the ensuing samples into virtual numeric values that may be manipulated via way of means of a computer.
Data acquisition structures, abbreviated via way of means of the initializes DAS, DAQ, or DAU, commonly convert analog waveforms into virtual values for processing.
The additives of records acquisition structures include: Sensors, to transform bodily parameters to electric alerts. Signal conditioning circuitry, to transform sensor alerts right into a shape that may be transformed to virtual values. Analog-to-virtual converters, to transform conditioned sensor alerts to virtual values.
Although records to be had from numerous earth statement structures were robotically used in lots of useful resource packages, but there were gaps, and records wishes of packages at distinctive ranges of information have now no longer been met.
There is a developing call for availability of records at better receptivity, at better spatial decision, in extra and narrower spectral bands etc. Some of the thrust regions of packages mainly with inside the Indian context are;
- Management of herbal sources to make certain sustainable boom in agricultural manufacturing, -
Study the kingdom of the environment, its tracking and evaluation of the effect of. Numerous improvement movements at the environment,
- Updating and technology of massive scale topographical maps.
- Exploration/exploitation of marine and mineral sources and
- Operational meteorology and reading numerous land and oceanic methods to understand/expect international weather adjustments.
Each of those thrust location of software has many additives, associated with simple useful resource regions which includes agriculture, forestry, water sources, minerals, marine sources etc. and the sector of cartography. Observational necessities for primary packages were summarized as under.
Monitoring plants fitness from area stays the maximum crucial observational parameter with packages, in agriculture, forestry, environment, hydrology etc. Vegetation extent, amount and temporal adjustments are the 3 primary necessities which aren't absolutely found out with RS records to be had.
Vegetation productivity, wooded area biomass, cover moisture status, cover biogeochemistry are a few examples. Crop manufacturing forecasting is a crucial software location. Remotely sensed records has been used for identity of plants and their acreage estimation.
Fragmented holdings, massive unfold in crop calendars and distinctive control practices retain to pose an assignment lo faraway sensing. Remotely sensed records at lots better spatial decision than hitherto to be had in addition to at extra receptivity are required to satisfy this need.
Non-availability of cloud-unfastened records with inside the Khari season is one of the severe troubles in operational use of faraway sensing for crop inventory. Synthetic aperture radar records al X & Ku bands is vital to satisfy this call for. Nutrient stress/sickness detection calls for observations in slender spectral bands. In case of forestry packages, multispectral records at excessive spatial decision of the order of five to ten meters is needed to make running plans at wooded area compartment level.
Observations from area for deriving tree peak are required for extent estimation. Observations with inside the center infrared location could substantially beautify functionality of satellite TV for pc faraway sensing in wooded area hearth place detection.
Temporal, spatial and spectral observational necessities in numerous packages on plants viewing are diverse, as they deal with methods at distinctive spatial and time scales. Hence, it might be profitable to deal with this trouble in 3 wide categories.
Q6) What is geo-referencing of data.
A6)
Geo-referencing method that the inner coordinate device of a map or aerial image photo may be associated with a geographic coordinate device.
The maximum seen impact of geo-referencing is that show software program can display floor coordinates (together with latitude/longitude or UTM coordinates) and additionally degree floor distances and regions. In different words, geo-referencing method to partner a virtual photo document with places in bodily space.
The time period is generally used with inside the geographic records structures discipline to explain the technique of associating a bodily map or raster photo of a map with spatial places.
Geo-referencing can be implemented to any form of item or shape that may be associated with a geographical location, together with factors of interest, roads, places, bridges, or buildings. Geographic places are maximum generally represented the use of a coordinate reference device, which in flip may be associated with a geodetic reference device together with WGS-84.
Examples encompass organizing the appropriate function of an aerial picture graph inside a map or locating the geographical coordinates of an area call or avenue address (Geocoding).
Geo-referencing is essential to make aerial and satellite TV for pc imagery, typically raster pictures, beneficial for mapping because it explains how different information, together with the above GPS factors, relate to the imagery.
Very vital records can be contained in information or pictures that had been produced at a one-of-a-kind factor of time. It can be preferred both to mix and examine this information with that presently available. The latter may be used to research the modifications with inside the functions below have a look at over a length of time.
Different maps might also additionally use one-of-a-kind projection structures. Geo-referencing gear include techniques to mix and overlay those maps with minimal distortion.
Using geo-referencing techniques, information acquired from surveying gear like general stations can be given a factor of reference from topographic maps already available.
It can be required to set up the connection among social survey outcomes that have been coded with postal codes or avenue addresses and different geographic regions together with census zones or different regions utilized in public management or provider planning.
Q7) What is projection system?
A7)
Projection system:
- A projection is the approach via way of means of that you show the coordinate gadget and your records on a flat floor, consisting of a bit of paper or a virtual screen.
- Mathematical calculations are used to transform the coordinate gadget used at the curved floor of earth to 1 for a flat floor.
- Since there may be no ideal manner to transpose a curved floor to a flat floor without a few distortion, diverse map projections exist that offer exceptional properties.
- Some maintain shape, even as others maintain distance. Some maintain vicinity or direction. The extent, location, and belongings you need to maintain should tell your preference of map projection.
- There are extra than 4,000 coordinate structures with inside the ArcGIS platform, so it's far possibly you will locate one to in shape your records.
- If now no longer, you could create a custom coordinate gadget to show the records. ArcGIS Pro projects records at the fly so any records you upload to a map adopts the coordinate gadget definition of the primary layer delivered.
- As lengthy because the first layer delivered has its coordinate gadget efficiently defined, all different records with accurate coordinate gadget data projects at the fly to the coordinate gadget of the map?
- This technique helps exploring and mapping records, however it have to now no longer be used for evaluation or editing, due to the fact it may result in inaccuracies from misaligned records amongst layers.
- Data is likewise slower to attract while it's far projected at the fly.
- If you would like to carry out evaluation or edit the records, first assignment it right into a constant coordinate gadget shared via way of means of all of your layers.
- This creates a new edition of your records. After defining the coordinate gadget that fits your records, you can nonetheless need to apply records in an exceptional coordinate gadget.
- This is while modifications are useful. Transformations convert records among exceptional geographic coordinate structures or among exceptional vertical coordinate structures.
- Unless your records strains up, you will come upon problems and inaccuracies in any evaluation and mapping you carry out at the mismatched records.
Q8) Write a note on vector data.
A8)
Vector Data
Vector information is what maximum humans think about once they don't forget spatial information.
Data on this layout includes factors, traces or polygons. At its handiest level, vector information accommodates of person factors saved as coordinate pairs that suggest a bodily place with inside the world.
These factors may be joined, in a specific order, to shape traces or joined into closed regions to shape polygons.
Vector information is extraordinarily beneficial for storing and representing information that has discrete boundaries, which include borders or constructing footprints, streets and different delivery links, and place factors.
Ubiquitous on-line mapping portals, which include Google Maps and Open Street Maps, gift information on this layout.
Q9) What is raster data.
A9)
Raster Data
Raster information gives an illustration of the arena as a floor divided up right into an ordinary grid array, or cells, wherein every of those cells has an related value. In an exchange sense, we are able to don't forget a virtual picture as an instance of a raster dataset.
Here every cell, which on this example is called a pixel, corresponds to a specific coloration value. When transferred right into a GIS setting, the cells in a raster grid can doubtlessly constitute different information values, which include temperature, rainfall or elevation.
The major factor of distinction among the virtual picture and the GIS illustration is that with inside the GIS there may be accompanying information detailing wherein the cells may be discovered on a globe and the way large those cells may be.
Q10) How raster to vector conversion will be done?
A10)
Raster to vector conversion:
Extracting vector capabilities from a picture (or “vector zing a raster”) includes changing organizations of raster pixels into polygons.
Maybe you’d want to digitize a scanned map, convert a DEM to polygons primarily based totally on elevation, extract textual content from a picture, or in any other case generate polygons from a provided picture.
There are many viable approaches to address those problems, a few less complicated than others, a few greater accurate.
Here are 3 approaches you could do it through processing your raster in an FME information integration workflow.
1. Trace and picture to transform it to CAD or GIS Pot race is a loose device for turning bitmaps into vector graphics.
In FME, you could leverage it through the custom transformer Pot race Caller. Converting raster to vector on this context includes
3 steps: Prepare the raster (e.g. Discover color stages with inside the enter JPEG) Call Pot race Prepare the output (e.g. Generalize polygons, fashion for AutoCAD) in the underneath example, the person has an RGB picture of a place and desires to extract CAD polygons of homes.
In the picture, homes are proven in a darker color.
Preparing the raster consequently includes classifying cooler stages so the range of colors is reduced — extracting the darkish color representing homes and leaving the whole lot else because the background.
Preparing the output includes smoothing the polygons generated through Pot race so we become with exceptional blocky shapes rather than loopy 1000-sided chiliad guns.
2. Extract textual content from a picture with Optical Character Recognition Converting and picture to textual content may be performed through leveraging Tess erect, a loose device that plays OCR.
In FME, this could be performed with the custom transformer TesseractCaller. OCR is beneficial for digitizing scanned maps and documents, making the information searchable and index able. As above, this workflow additionally includes pre-processing steps to outline cooler stages, and making ready information for the output format.
3. Extract polygons from a raster primarily based totally on pixel values
This is likewise recognized as “classifying” a raster and includes producing a polygon for every contiguous region of pixels with comparable values.
FME has assist for a number of raster and imagery formats, in addition to a number of very effective capability for operating with raster’s.
To classify a raster and convert organizations of pixels to polygons, ship it through the Raster to PolygonCoercer. While this approach is easier because it doesn’t contain downloading the 3rd-celebration device Pot race, notice it’s greater in depth and consequently slower than Pot race.
If you've got a huge raster, it’ll likely be greater really well worth your whilst to apply approach
Q11) Explain various terms used in vector data.
A11)
Object Oriented
The tabular version is the way wherein maximum early GIS software program applications saved their characteristic records. The subsequent 3 fashions are the ones maximum generally applied in database control system (DBMS). The item orientated is more modern however hastily gaining reputation for a few application.
A quick assessment of every version is given below. Tabular Model: -The easy tabular version shops characteristic records as sequential records documents with constant formats. This form of records version is previous in GIS arena. It lacks any approach of checking records integrity, in addition to being inefficient with admire to records garage.
Hierarchical Model: -
The hierarchical database organizes records in a tree shape. Data is dependent downward in a hierarchy of tables. Any degree with inside the hierarchy will have limitless children, however any baby will have handiest one parent. Hierarchical DBMS have now no longer won any important reputation to be used inside GIS. They are orientated for records units which might be very stable, in which number one courting a few of the records extrude regularly or by no means at all. Also, the difficulty at the variety of mother and father that and detail can also additionally have isn't usually conducive to real geographic phenomenon.
Network Model: -
The community database organizes records in a community or plea shape. Any column in a plea shape may be related to another like a tree shape. A plea shape may be defined in phrases of mother and father and children. This version permits having a couple of parent.
Network DBMS have determined now no longer an awful lot greater reputation in GIS than the hierarchical DBMS.
They have the identical flexibility boundaries as hierarchical database: however, the greater effective shape for representing records relationships permits a greater sensible modeling of geographic phenomena.
In this regard it is straightforward to lose manage and knowledge of the relationships among factors.
Relational Model: -
The relational database organizes records in tables. Each desk is recognized with the aid of using a completely unique desk name, and is prepared with the aid of using rows and columns.
Each column inside a desk additionally has a completely unique name. Columns shop the values for a particular characteristic, e.g. Cowl group, tree height.
In GIS every row is generally related to a separate function, e.g. a forestry stand. Accordingly, every row might be constructed from numerous columns, every column containing a particular fee for that geographic function. In this version a key represents one or greater attributes whose fee can uniquely become aware of a file in a desk.
Therefore, a key not unusual place to 2 tables can set up connection among corresponding data with inside the tables.
Usually right here varieties of desk are defined- the supply desk & the vacation spot desk. If the reason is to feature characteristic records from a desk to the function characteristic desk, then the function characteristic desk is the vacation spot desk and the alternative one is the supply desk. Owing to this way, 3 varieties of relationships may be created.
Object Oriented Model: -
The item orientated records version manages records via item. An item is a group of records factors and operations that collectively are taken into consideration as unmarried entity. The item orientated database is an enormously new version.
This technique has the enchantment that querying could be very natural, as functions may be bundled collectively with attributes on the database. Today, just a few GIS applications are selling the usage of this characteristic records version. However, preliminary impressions imply that this technique can also additionally maintain many operational advantages with admire to geographic records processing.
Q12) What is remote sensing data in GIS?
A12)
Any region on earth has large quantities of facts tied to it, which now no longer most effective encompass bodily features, however political, monetary and social facts, as well. GIS allows the technique through which we will visualize, examine and recognize this facts.
Remote sensing is one of the techniques typically used for accumulating bodily facts to be incorporated into GIS.
Remote sensors acquire facts from gadgets on earth with none direct contact. They do that through detecting strength contemplated from the earth, and are generally established on satellites or aircraft.
Remote sensing generation has come to be a lot greater prevalent, correct and available in current years, and covers an extensive variety of engineering applications.
First, engineers use faraway sensing to assist them decide the topography of our earth. Three-dimensional pix of the earth’s floor (proven in Figure 1) may be generated the usage of LiDAR, which stands for Light Detection and Ranging.
LiDAR sensors use pulsed lasers blended with role and orientation facts to acquire dense agencies of elevation factors known as factor clouds.
These factor clouds can then be processed into contours and virtual elevation models (DEMs) representing the form of the earth.
Engineers can use a DEM to calculate a completely brief and pretty correct estimate of the extent of earth-transferring essential to expand a tract of land. Remote sensing is likewise used to screen land use, which aids engineers and planners in making choices at some point of the direction of a layout project.
Optical sensors degree the sun radiation contemplated from the floor of the earth. The distinctive wavelengths detected are blended, ensuing in a photograph that resembles a photo taken through a digital of the earth’s floor.
Remote sensing is a sort of geospatial generation that samples emitted and contemplated electromagnetic (EM) radiation from the Earth’s terrestrial, atmospheric, and aquatic ecosystems so one can stumble on and screen the bodily traits of a place without making bodily contact.
This approach of facts series generally entails aircraft-primarily based totally and satellite-primarily based totally sensor technologies, which might be categorized as either passive sensors or energetic sensors.
Passive sensors reply to outside stimuli, accumulating radiation this is contemplated or emitted through an item or the encompassing space.
The maximum not unusual place supply of radiation measured through passive faraway sensing is contemplated sunlight. Popular examples of passive faraway sensors encompass charge-coupled devices, movie photography, radiometers, and infrared.
Active sensors use inner stimuli to acquire facts, emitting strength so one can experiment gadgets and regions whereupon a sensor measures the strength contemplated from the target.
RADAR and LiDAR are traditional energetic faraway sensing equipment that degree the time postpone among emission and go back so one can set up the region, direction, and velocity of an item.
The faraway sensing facts amassed is then processed and analyzed with faraway sensing hardware and pc software that is to be had in quite a few proprietary and open supply applications.
Q13) Explain GIS database and database management system.
A13)
- A database is a dependent series of statistics documents. A database control gadget (DBMS) is a software program package deal that lets in for the creation, storage, maintenance, manipulation, and retrieval of big datasets which are disbursed over one or greater documents.
- A DBMS and its related capabilities are commonly accessed via industrial software program applications along with Microsoft Access, Oracle, FileMaker Pro, or Avenues My Database.
- Database control usually refers back to the control of tabular statistics in row and column layout and is often used for personal, business, authorities, and clinical endeavors.
- Geospatial database control structures, alternatively, encompass the capability of a DBMS however additionally include particular geographic statistics approximately every statistics factor along with identity, location, shape, and orientation.
- Integrating this geographic statistics with the tabular characteristic statistics of a classical DBMS offer customers with effective gear to visualize and solution the spatially express questions that stand up in an increasing number of technological society.
- Clarita’s and comparable groups use database control structures (DBMS) to create the "way of life segments" that I mentioned with inside the preceding section. Basic database ideas are vital considering the fact that GIS contains a great deal of the capability of DBMS.
- Digital statistics are saved in computer systems as documents. Often, statistics are arrayed in tabular form. For this reason, statistics documents are frequently known as tables.
- A database is a group of tables. Businesses and authorities companies that serve big clienteles, along with telecommunications groups, airlines, and credit score card firms, and banks, depend on sizeable databases for his or her billing, payroll, inventory, and advertising and marketing operations.
- Database control structures are statistics structures that human beings use to store, update, and examine non-geographic databases.
- Often, statistics documents are tabular in form, composed of rows and columns. Rows, additionally called information, correspond with person entities, along with consumer debts.
- Columns correspond with the diverse attributes related to every entity.
- Geographic statistics are a unique case: information correspond with places, now no longer human beings or debts. Columns constitute the attributes of places. The statistics with inside the following table, for example, encompass information for Pennsylvania counties.
- Columns include decided on attributes of every county, such as the county's ID code, name, and 1980 population.
- Database control structures are treasured due to the fact they offer stable manner of storing and updating statistics. Database directors can shield documents in order that most effective legal customers could make changes. DBMS offer transaction control capabilities that permit more than one customers to edit the database simultaneously.
- In addition, DBMS additionally offer state-of-the-art manner to retrieve statistics that meet person precise standards.
- In different words, they allow customers to pick statistics in reaction to specific questions. A query this is addressed to a database via a DBMS is known as a query.
- Database queries encompass fundamental set operations, such as union, intersection, and distinction. The manufactured from a union of or greater statistics documents is a unmarried report that consists of all information and attributes, without redundancy.
- An intersection produces a statistics report that incorporates most effective information found in all documents.
- A distinction operation produces a statistics report that removes information that seem in each authentic documents. (Try drawing Venn diagrams--intersecting circles that display relationships among or greater entities--to demonstrate the 3 operations. Then evaluate your cartoon to the Venn diagram example.)
- All operations that contain more than one statistics documents depend on the reality that each one documents include a not unusual place key.
- The key lets in the database gadget to narrate the separate documents. Databases that include several documents that proportion one or greater keys are known as relational databases.
- Database structures that allow customers to supply statistics from relational databases are known as relational database control structures. A not unusual place use of database queries is to become aware of subsets of information that meet standards hooked up via way of means of the person.
- For example, a credit score card organization can also additionally want to become aware of all debts which are 30 days or greater beyond due.
- A county tax assessor can also additionally want to list all residences now no longer assessed in the beyond 10 years. Or the U.S. Census Bureau can also additionally want to become aware of all addresses that want to be visited via way of means of census takers, due to the fact census questionnaires had been now no longer back via way of means of mail.
- DBMS software program companies have followed a standardized language known as SQL (Structured Query Language) to pose such queries.
Q14) Write a note on Case studies: demarcation of dam catchment and command area.
A14)
Surface water reassess are alternatively insufficient in peninsular India to fulfil the call for and need to be supplemented with groundwater. Productivity through groundwater is pretty excessive in comparison to floor water.
Cauvery basin is one of the high-satisfactory regulated and completely exploited basins and no documented estimates of groundwater are to be had for the basin with inside the critical a part of Tamil Nadu region.
Various geological and geo-morphological elements play a first-rate position with inside the prevalence, motion and capability of floor water reasserts. Survey of India (SOI) Topographic maps and LANDSAT TM satellite TV for pc pics had been used to put together diverse thematic layers along with geology, geomorphology, drainage pattern, lineaments, soil and slope, which impact the prevalence, motion, yield and nice of groundwater.
All those topics and their character functions had been then assigned weights in line with their relative significance in groundwater prevalence.
The thematic layers are then incorporated the use of ERDAS photograph processing software program and through using raster calculator equipment in ArcGIS platform, a composite groundwater capability index (GWPI) for the have a look at location become generated on the idea of which the general groundwater capability map become produced.
Three classes of groundwater capability zones had been delineated as poor; mild and excessive.
Groundwater prevalence is categorized as 'poor' in 63.34% of the have a look at location which substantiates synthetic recharge to reinforce groundwater with inside the region.
The institution extensively undertakes research in meteorology, carried out hydrology, physic-chemical strategies for water nice and hydraulics of surficial processes.
This laboratory includes 3 technical divisions viz., Hydrometeorology, Water Quality Analysis and Modelling and Surface Water Hydraulics.
The institution as a result conducts research in river and reservoir structures through area experimentations, mathematical modelling equipment and location precise table research.
Hydrometeorology Division
Hydrometeorology department become fashioned in 2012 through merging the erstwhile Physics (fashioned in 1947) and Statistics (fashioned in 1947) divisions to cater to the desires of the customers requiring precise research to be completed in carried out hydrology, meteorology carried out in hydrology and information.
In the preliminary segment of its functioning, the Physics department had contributed to water assets region through electric analogy method in supplying answers for PMF estimation, seepage, subsurface flows and flood routing.
With the utility of computer systems in hydrology and different fields, Physics department additionally inherited the mathematical modelling method and followed many a fashions and additionally advanced a few with inside the location of work.
On the opposite hand, the information department become conceived to cater to hydrology in addition to hydraulic modelling agencies in information evaluation of diverse initiatives adopting stochastic, probabilistic processes and optimization techniques.
Extreme Value Analysis (EVA) of Meteorological Parameters
Paperwork part of the technical and engineering investigations for designing Nuclear Power Plants (NPPs), which want to be safeguarded towards herbal hazards. (Madhya Pradesh), MythicVerdi (Gujarat) and Gorakhpur (Haryana), CWPRS completed EVA of meteorological parameters recorded on the meteorological stations, that are with inside the location of the NPPs and the effects received from the research might be beneficial to NPCIL for arriving at layout parameters for the proposed
Fig: Extreme Value analysis
Estimation of Probable Maximum Flood
The estimation of PMF for Narmada at numerous places i.e., Narmada Sager, Mahesh war, Omkareshwar and SardarSarovar turned into completed via way of means of this department beneath World Bank aide. The research had been completed adopting lumped conceptual version OPSET (changed model of Stanford Watershed Model). Flood moderation in river channel turned into modelled adopting Muskingum method. The version turned into advanced for the entire of Narmada catchment from its supply to SardarSarovar.
Evaluation of the version research carried out turned into made via way of means of World Bank specialists and PMF predicted via way of means of CWPRS turned into followed for layout.
Fig: Estimation of probable maximum flood
Flood Frequency Analysis
Estimation of most flood discharge (MFD) with a particular go back duration is vital for the layout of hydraulic structures. MFD may be correctly decided via way of means of becoming of chance distributions to the collection of recorded annual most discharge (AMD) data. An AMD is the best immediate discharge cost at a precise cross-phase of a herbal move at some stage in a whole hydrologic year (water year). CWPRS completed flood estimation research for rivers Krishna, Narmada, Godavari, Tapi, etc. The FFA approach turned into additionally followed via way of means of CWPRS to estimate the intense max/ min values of different meteorological parameters which include Rainfall, wind speed, temperatures, etc. Some of the tasks are NPPs of NPCIL in which the layout parameters had been derived and river valley tasks in which the rainfall turned into used to compute layout flood.
Fig: Flood Frequency Analysis
Unit - 6
GIS Data and Applications
Q1) Explain GIS data types and data representation
A1)
GIS DATA TYPES GIS era makes use of simple sorts of information.
These are:
1) Spatial information: describes absolutely and relative region of geographic capabilities.
2) Attribute information: describes traits of the spatial capabilities. These traits may be quantitative and/or qualitative in nature. Attribute information is frequently stated as tabular information.
SPATIAL DATA MODELS
1) Vector
2) Raster
3) Image
VECTOR
All spatial information fashions are strategies for storing the spatial region of geographic capabilities in a database. Vector garage implies the usage of vectors (directional lines) to symbolize a geographic feature.
RASTER
Raster information fashions contain the usage of a grid-mobileular information shape in which the geographic place is split into cells diagnosed via way of means of row and column. This information shape is normally known as raster.
IMAGE
Image information is most usually used to symbolize photo or pictorial information. The time period photo inherently displays a photo representation, and with inside the GIS world, differs notably from raster information.
Q2) Give advantages and disadvantages of vector information model.
A2)
Advantages of vector information model
• Data may be represented at its authentic decision and shape with out generalization.
• Graphic output is typically greater aesthetically pleasing (traditional cartographic representation);
• Since maximum information, e.g. Difficult reproduction maps, is in vector shape no information conversion is needed.
• Accurate geographic region of information is maintained.
• Allows for green encoding of topology, and as an end result greater green operations that require topological information, e.g. Proximity, community evaluation.
Disadvantages of vector information model
• The region of every vertex desires to be saved explicitly.
• For powerful evaluation, vector information ought to be transformed into a topological shape.
• Algorithms for manipulative and evaluation features are complex and can be processing intensive. Often, this inherently limits the capability for big information sets, e.g. a big wide variety of capabilities.
• Continuous information, which includes elevation information, isn't always effectively represented in vector shape. Usually giant information generalization or interpolation is needed for those information layers.
• Spatial evaluation and filtering inside polygons is impossible Advantages of raster information model
• The geographic region of every mobileular is implied via way of means of its role in the mobileular matrix.
Accordingly, aside from a foundation point, e.g. Bottom left corner, no geographic coordinates are saved.
• Due to the character of the information garage approach information evaluation is typically clean to application and short to perform.
• The inherent nature of raster maps, e.g. One characteristic maps, is perfectly suited for mathematical modeling and quantitative evaluation.
• Discrete information, e.g. Forestry stands, is accommodated similarly well as non-stop information, e.g. Elevation information, and helps the integrating of the 2 information types.
• Grid-mobileular structures are very well suited with raster-primarily based totally output devices, e.g. Electrostatic plotters, photo terminals. Disadvantages of raster information model
• The mobileular length determines the decision at which the information is represented.
• It is especially hard to competently constitute linear capabilities relying at the mobileular decision.
Accordingly, community linkages are hard to establish.
• Processing of related characteristic information can be bulky if big quantities of information exists.
Raster maps inherently mirror only one characteristic or feature for a place.
• Since maximum enter information is in vector shape, information ought to undergo vector-to-raster conversion.
Besides expanded processing necessities this will introduce information integrity issues due to generalization and desire of beside the point mobileular length.
• Most output maps from grid-mobileular structures do now no longer agree to high quality cartographic desires.
Q3) Explain Data Synthesis and Visualization
A3)
The present established programs for cartography (ESRI, ERDAS, LHS, Multispeed and etc.), permit synthesizing polygonal and hyper spectral pics.
The recognized methods, like which are described [1-3], discover multispectral pix of items to show them. These responsibilities require pixel category, which isn't always an easy operation and may be done with the aid of using numerous methods.
It takes lots time to do it. The approach offered right here does now no longer require initial category. It can therefore be used with the intention to swiftly carry out the responsibilities of visible interpretation.
We shall illustrate this approach with an instance of the synthesis of n-area aero pics. We anticipate that the pics are superimposed.
Everyone pixel of such set of the pix has n the spectral traits or attributes.
A pixel with all its attributes is chosen as a well-known version.
Apart from the spectral traits a few different attributes can be assigned to a pixel. These may be acquired by way of initial processing of every spectral photo or a hard and fast of pix.
The attributes of the usual version are as compared to the ones of all different pixels. The synthesis of the pix is produced primarily based totally on a precept of comparable attributes.
The maximum brightness is assigned to the pixels that resemble maximum the usual version. The brightness fee of the relaxation of the pixels is calculated on the idea in their resemblance with the usual version.
Different attributes may be hired as a degree of resemblance, specifically the ones which are used for category with inside the famous software programs Multispeed, ESRI, ERDAS.
It may be the Euclidean metric with inside the n-dimensional area of the attributes or the maximal distinction among values of the identical attributes. No extra data is wanted for this metrics. If the data at the opportunity distribution of the usual version attributes is recognized, one could employ the conditional probabilities (the Bayesian approach) to assess resemblance.
All the traits which have been anticipated earlier can be concerned whilst growing a resemblance metric.
The very last synthesized photo is offered in grayscale. It carries the data on a diploma of similarity of the attributes of each pixel to the ones of the usual version. The synthesis time of a photo relies upon most effective at the time had to calculate the attributes of each pixel.
When the use of most effective the experimentally measured attributes, along with the spectral values of brightness, the very last photo is fashioned in actual time, because the calculation of resemblance is done instantly.
In addition it's far of the significance that this approach entails no multiplexing. And throughput of transmitting of data is excessive.
Note, that the recognized approach “infrared satiation vision” visualizes preliminary pix in numerous spectral durations into one photo in which every of preliminary photo is submitted with the aid of using monochromatic satiatioñ red, inexperienced or blue (RGB).
But multichannel switch of the data is vital in that case.
Q4) Give various example of data representation.
A4)
EXAMPLES
- We gift the outcomes of synthesis of imaging data (aero pics of a terrestrial floor) that acquired in nine spectral bands. The Euclidean metric in nine-dimensional area of spectral attributes have been used. Pixels with numerous coordinates had been decided on as well-known models.
- The first column of discern 1 carries the pics of terrestrial floor in nine spectral ranges. In the second one column we gift the outcomes of photo synthesis.
- The maximum brightness degree is assigned to pixels with spectral attributes bearing the very best resemblance to its well-known version.
- The others pixels have the brightness placing that corresponds to the extent of resemblance of the attributes.
- The well-known version coordinates are marked subsequent to the very last pix. One can have a look at that the synthesized pix are lots greater detailed, than the pix similar to every spectral band.
- The pixels of the synthesized photo, which have an excessive degree of resemblance than a positive threshold fee, can be highlighted in color.
- The discern 2 gives the synthesis outcomes of the pics in four spectral bands with one-of-a-kind threshold values.
- Note that this photo transformation set of rules is likewise appropriate for processing panchromatic pix.
- The regions of the photo which are of greater hobby to the spectator may be emphasized with the very best brightness.
- It is plain that this processing approach can't boom the decision of a panchromatic photo except extra data is used, however it may boom its perceptibility.
- The degree of depth with inside the pics is decided with the aid of using the reflective cap potential of items and relies upon at the ecosystem condition, the exposition parameters, etc.
- The well-known version is acquired below the identical conditions; consequently the end result of the synthesis does now no longer rely on those factors. In the given instance most effective spectral values of brightness have been used as attributes.
- Apart from the measured spectral values of brightness one may want to use a few extra attributes acquired by way of processing the preliminary data: as an instance structural, contextual and textural attributes. The desire of the attributes can adjust the end result significantly.
Q5) Explain data acquisition.
A5)
Data acquisition is the method of sampling alerts that degree actual international bodily situations and changing the ensuing samples into virtual numeric values that may be manipulated via way of means of a computer.
Data acquisition structures, abbreviated via way of means of the initializes DAS, DAQ, or DAU, commonly convert analog waveforms into virtual values for processing.
The additives of records acquisition structures include: Sensors, to transform bodily parameters to electric alerts. Signal conditioning circuitry, to transform sensor alerts right into a shape that may be transformed to virtual values. Analog-to-virtual converters, to transform conditioned sensor alerts to virtual values.
Although records to be had from numerous earth statement structures were robotically used in lots of useful resource packages, but there were gaps, and records wishes of packages at distinctive ranges of information have now no longer been met.
There is a developing call for availability of records at better receptivity, at better spatial decision, in extra and narrower spectral bands etc. Some of the thrust regions of packages mainly with inside the Indian context are;
- Management of herbal sources to make certain sustainable boom in agricultural manufacturing, -
Study the kingdom of the environment, its tracking and evaluation of the effect of. Numerous improvement movements at the environment,
- Updating and technology of massive scale topographical maps.
- Exploration/exploitation of marine and mineral sources and
- Operational meteorology and reading numerous land and oceanic methods to understand/expect international weather adjustments.
Each of those thrust location of software has many additives, associated with simple useful resource regions which includes agriculture, forestry, water sources, minerals, marine sources etc. and the sector of cartography. Observational necessities for primary packages were summarized as under.
Monitoring plants fitness from area stays the maximum crucial observational parameter with packages, in agriculture, forestry, environment, hydrology etc. Vegetation extent, amount and temporal adjustments are the 3 primary necessities which aren't absolutely found out with RS records to be had.
Vegetation productivity, wooded area biomass, cover moisture status, cover biogeochemistry are a few examples. Crop manufacturing forecasting is a crucial software location. Remotely sensed records has been used for identity of plants and their acreage estimation.
Fragmented holdings, massive unfold in crop calendars and distinctive control practices retain to pose an assignment lo faraway sensing. Remotely sensed records at lots better spatial decision than hitherto to be had in addition to at extra receptivity are required to satisfy this need.
Non-availability of cloud-unfastened records with inside the Khari season is one of the severe troubles in operational use of faraway sensing for crop inventory. Synthetic aperture radar records al X & Ku bands is vital to satisfy this call for. Nutrient stress/sickness detection calls for observations in slender spectral bands. In case of forestry packages, multispectral records at excessive spatial decision of the order of five to ten meters is needed to make running plans at wooded area compartment level.
Observations from area for deriving tree peak are required for extent estimation. Observations with inside the center infrared location could substantially beautify functionality of satellite TV for pc faraway sensing in wooded area hearth place detection.
Temporal, spatial and spectral observational necessities in numerous packages on plants viewing are diverse, as they deal with methods at distinctive spatial and time scales. Hence, it might be profitable to deal with this trouble in 3 wide categories.
Q6) What is geo-referencing of data.
A6)
Geo-referencing method that the inner coordinate device of a map or aerial image photo may be associated with a geographic coordinate device.
The maximum seen impact of geo-referencing is that show software program can display floor coordinates (together with latitude/longitude or UTM coordinates) and additionally degree floor distances and regions. In different words, geo-referencing method to partner a virtual photo document with places in bodily space.
The time period is generally used with inside the geographic records structures discipline to explain the technique of associating a bodily map or raster photo of a map with spatial places.
Geo-referencing can be implemented to any form of item or shape that may be associated with a geographical location, together with factors of interest, roads, places, bridges, or buildings. Geographic places are maximum generally represented the use of a coordinate reference device, which in flip may be associated with a geodetic reference device together with WGS-84.
Examples encompass organizing the appropriate function of an aerial picture graph inside a map or locating the geographical coordinates of an area call or avenue address (Geocoding).
Geo-referencing is essential to make aerial and satellite TV for pc imagery, typically raster pictures, beneficial for mapping because it explains how different information, together with the above GPS factors, relate to the imagery.
Very vital records can be contained in information or pictures that had been produced at a one-of-a-kind factor of time. It can be preferred both to mix and examine this information with that presently available. The latter may be used to research the modifications with inside the functions below have a look at over a length of time.
Different maps might also additionally use one-of-a-kind projection structures. Geo-referencing gear include techniques to mix and overlay those maps with minimal distortion.
Using geo-referencing techniques, information acquired from surveying gear like general stations can be given a factor of reference from topographic maps already available.
It can be required to set up the connection among social survey outcomes that have been coded with postal codes or avenue addresses and different geographic regions together with census zones or different regions utilized in public management or provider planning.
Q7) What is projection system?
A7)
Projection system:
- A projection is the approach via way of means of that you show the coordinate gadget and your records on a flat floor, consisting of a bit of paper or a virtual screen.
- Mathematical calculations are used to transform the coordinate gadget used at the curved floor of earth to 1 for a flat floor.
- Since there may be no ideal manner to transpose a curved floor to a flat floor without a few distortion, diverse map projections exist that offer exceptional properties.
- Some maintain shape, even as others maintain distance. Some maintain vicinity or direction. The extent, location, and belongings you need to maintain should tell your preference of map projection.
- There are extra than 4,000 coordinate structures with inside the ArcGIS platform, so it's far possibly you will locate one to in shape your records.
- If now no longer, you could create a custom coordinate gadget to show the records. ArcGIS Pro projects records at the fly so any records you upload to a map adopts the coordinate gadget definition of the primary layer delivered.
- As lengthy because the first layer delivered has its coordinate gadget efficiently defined, all different records with accurate coordinate gadget data projects at the fly to the coordinate gadget of the map?
- This technique helps exploring and mapping records, however it have to now no longer be used for evaluation or editing, due to the fact it may result in inaccuracies from misaligned records amongst layers.
- Data is likewise slower to attract while it's far projected at the fly.
- If you would like to carry out evaluation or edit the records, first assignment it right into a constant coordinate gadget shared via way of means of all of your layers.
- This creates a new edition of your records. After defining the coordinate gadget that fits your records, you can nonetheless need to apply records in an exceptional coordinate gadget.
- This is while modifications are useful. Transformations convert records among exceptional geographic coordinate structures or among exceptional vertical coordinate structures.
- Unless your records strains up, you will come upon problems and inaccuracies in any evaluation and mapping you carry out at the mismatched records.
Q8) Write a note on vector data.
A8)
Vector Data
Vector information is what maximum humans think about once they don't forget spatial information.
Data on this layout includes factors, traces or polygons. At its handiest level, vector information accommodates of person factors saved as coordinate pairs that suggest a bodily place with inside the world.
These factors may be joined, in a specific order, to shape traces or joined into closed regions to shape polygons.
Vector information is extraordinarily beneficial for storing and representing information that has discrete boundaries, which include borders or constructing footprints, streets and different delivery links, and place factors.
Ubiquitous on-line mapping portals, which include Google Maps and Open Street Maps, gift information on this layout.
Q9) What is raster data.
A9)
Raster Data
Raster information gives an illustration of the arena as a floor divided up right into an ordinary grid array, or cells, wherein every of those cells has an related value. In an exchange sense, we are able to don't forget a virtual picture as an instance of a raster dataset.
Here every cell, which on this example is called a pixel, corresponds to a specific coloration value. When transferred right into a GIS setting, the cells in a raster grid can doubtlessly constitute different information values, which include temperature, rainfall or elevation.
The major factor of distinction among the virtual picture and the GIS illustration is that with inside the GIS there may be accompanying information detailing wherein the cells may be discovered on a globe and the way large those cells may be.
Q10) How raster to vector conversion will be done?
A10)
Raster to vector conversion:
Extracting vector capabilities from a picture (or “vector zing a raster”) includes changing organizations of raster pixels into polygons.
Maybe you’d want to digitize a scanned map, convert a DEM to polygons primarily based totally on elevation, extract textual content from a picture, or in any other case generate polygons from a provided picture.
There are many viable approaches to address those problems, a few less complicated than others, a few greater accurate.
Here are 3 approaches you could do it through processing your raster in an FME information integration workflow.
1. Trace and picture to transform it to CAD or GIS Pot race is a loose device for turning bitmaps into vector graphics.
In FME, you could leverage it through the custom transformer Pot race Caller. Converting raster to vector on this context includes
3 steps: Prepare the raster (e.g. Discover color stages with inside the enter JPEG) Call Pot race Prepare the output (e.g. Generalize polygons, fashion for AutoCAD) in the underneath example, the person has an RGB picture of a place and desires to extract CAD polygons of homes.
In the picture, homes are proven in a darker color.
Preparing the raster consequently includes classifying cooler stages so the range of colors is reduced — extracting the darkish color representing homes and leaving the whole lot else because the background.
Preparing the output includes smoothing the polygons generated through Pot race so we become with exceptional blocky shapes rather than loopy 1000-sided chiliad guns.
2. Extract textual content from a picture with Optical Character Recognition Converting and picture to textual content may be performed through leveraging Tess erect, a loose device that plays OCR.
In FME, this could be performed with the custom transformer TesseractCaller. OCR is beneficial for digitizing scanned maps and documents, making the information searchable and index able. As above, this workflow additionally includes pre-processing steps to outline cooler stages, and making ready information for the output format.
3. Extract polygons from a raster primarily based totally on pixel values
This is likewise recognized as “classifying” a raster and includes producing a polygon for every contiguous region of pixels with comparable values.
FME has assist for a number of raster and imagery formats, in addition to a number of very effective capability for operating with raster’s.
To classify a raster and convert organizations of pixels to polygons, ship it through the Raster to PolygonCoercer. While this approach is easier because it doesn’t contain downloading the 3rd-celebration device Pot race, notice it’s greater in depth and consequently slower than Pot race.
If you've got a huge raster, it’ll likely be greater really well worth your whilst to apply approach
Q11) Explain various terms used in vector data.
A11)
Object Oriented
The tabular version is the way wherein maximum early GIS software program applications saved their characteristic records. The subsequent 3 fashions are the ones maximum generally applied in database control system (DBMS). The item orientated is more modern however hastily gaining reputation for a few application.
A quick assessment of every version is given below. Tabular Model: -The easy tabular version shops characteristic records as sequential records documents with constant formats. This form of records version is previous in GIS arena. It lacks any approach of checking records integrity, in addition to being inefficient with admire to records garage.
Hierarchical Model: -
The hierarchical database organizes records in a tree shape. Data is dependent downward in a hierarchy of tables. Any degree with inside the hierarchy will have limitless children, however any baby will have handiest one parent. Hierarchical DBMS have now no longer won any important reputation to be used inside GIS. They are orientated for records units which might be very stable, in which number one courting a few of the records extrude regularly or by no means at all. Also, the difficulty at the variety of mother and father that and detail can also additionally have isn't usually conducive to real geographic phenomenon.
Network Model: -
The community database organizes records in a community or plea shape. Any column in a plea shape may be related to another like a tree shape. A plea shape may be defined in phrases of mother and father and children. This version permits having a couple of parent.
Network DBMS have determined now no longer an awful lot greater reputation in GIS than the hierarchical DBMS.
They have the identical flexibility boundaries as hierarchical database: however, the greater effective shape for representing records relationships permits a greater sensible modeling of geographic phenomena.
In this regard it is straightforward to lose manage and knowledge of the relationships among factors.
Relational Model: -
The relational database organizes records in tables. Each desk is recognized with the aid of using a completely unique desk name, and is prepared with the aid of using rows and columns.
Each column inside a desk additionally has a completely unique name. Columns shop the values for a particular characteristic, e.g. Cowl group, tree height.
In GIS every row is generally related to a separate function, e.g. a forestry stand. Accordingly, every row might be constructed from numerous columns, every column containing a particular fee for that geographic function. In this version a key represents one or greater attributes whose fee can uniquely become aware of a file in a desk.
Therefore, a key not unusual place to 2 tables can set up connection among corresponding data with inside the tables.
Usually right here varieties of desk are defined- the supply desk & the vacation spot desk. If the reason is to feature characteristic records from a desk to the function characteristic desk, then the function characteristic desk is the vacation spot desk and the alternative one is the supply desk. Owing to this way, 3 varieties of relationships may be created.
Object Oriented Model: -
The item orientated records version manages records via item. An item is a group of records factors and operations that collectively are taken into consideration as unmarried entity. The item orientated database is an enormously new version.
This technique has the enchantment that querying could be very natural, as functions may be bundled collectively with attributes on the database. Today, just a few GIS applications are selling the usage of this characteristic records version. However, preliminary impressions imply that this technique can also additionally maintain many operational advantages with admire to geographic records processing.
Q12) What is remote sensing data in GIS?
A12)
Any region on earth has large quantities of facts tied to it, which now no longer most effective encompass bodily features, however political, monetary and social facts, as well. GIS allows the technique through which we will visualize, examine and recognize this facts.
Remote sensing is one of the techniques typically used for accumulating bodily facts to be incorporated into GIS.
Remote sensors acquire facts from gadgets on earth with none direct contact. They do that through detecting strength contemplated from the earth, and are generally established on satellites or aircraft.
Remote sensing generation has come to be a lot greater prevalent, correct and available in current years, and covers an extensive variety of engineering applications.
First, engineers use faraway sensing to assist them decide the topography of our earth. Three-dimensional pix of the earth’s floor (proven in Figure 1) may be generated the usage of LiDAR, which stands for Light Detection and Ranging.
LiDAR sensors use pulsed lasers blended with role and orientation facts to acquire dense agencies of elevation factors known as factor clouds.
These factor clouds can then be processed into contours and virtual elevation models (DEMs) representing the form of the earth.
Engineers can use a DEM to calculate a completely brief and pretty correct estimate of the extent of earth-transferring essential to expand a tract of land. Remote sensing is likewise used to screen land use, which aids engineers and planners in making choices at some point of the direction of a layout project.
Optical sensors degree the sun radiation contemplated from the floor of the earth. The distinctive wavelengths detected are blended, ensuing in a photograph that resembles a photo taken through a digital of the earth’s floor.
Remote sensing is a sort of geospatial generation that samples emitted and contemplated electromagnetic (EM) radiation from the Earth’s terrestrial, atmospheric, and aquatic ecosystems so one can stumble on and screen the bodily traits of a place without making bodily contact.
This approach of facts series generally entails aircraft-primarily based totally and satellite-primarily based totally sensor technologies, which might be categorized as either passive sensors or energetic sensors.
Passive sensors reply to outside stimuli, accumulating radiation this is contemplated or emitted through an item or the encompassing space.
The maximum not unusual place supply of radiation measured through passive faraway sensing is contemplated sunlight. Popular examples of passive faraway sensors encompass charge-coupled devices, movie photography, radiometers, and infrared.
Active sensors use inner stimuli to acquire facts, emitting strength so one can experiment gadgets and regions whereupon a sensor measures the strength contemplated from the target.
RADAR and LiDAR are traditional energetic faraway sensing equipment that degree the time postpone among emission and go back so one can set up the region, direction, and velocity of an item.
The faraway sensing facts amassed is then processed and analyzed with faraway sensing hardware and pc software that is to be had in quite a few proprietary and open supply applications.
Q13) Explain GIS database and database management system.
A13)
- A database is a dependent series of statistics documents. A database control gadget (DBMS) is a software program package deal that lets in for the creation, storage, maintenance, manipulation, and retrieval of big datasets which are disbursed over one or greater documents.
- A DBMS and its related capabilities are commonly accessed via industrial software program applications along with Microsoft Access, Oracle, FileMaker Pro, or Avenues My Database.
- Database control usually refers back to the control of tabular statistics in row and column layout and is often used for personal, business, authorities, and clinical endeavors.
- Geospatial database control structures, alternatively, encompass the capability of a DBMS however additionally include particular geographic statistics approximately every statistics factor along with identity, location, shape, and orientation.
- Integrating this geographic statistics with the tabular characteristic statistics of a classical DBMS offer customers with effective gear to visualize and solution the spatially express questions that stand up in an increasing number of technological society.
- Clarita’s and comparable groups use database control structures (DBMS) to create the "way of life segments" that I mentioned with inside the preceding section. Basic database ideas are vital considering the fact that GIS contains a great deal of the capability of DBMS.
- Digital statistics are saved in computer systems as documents. Often, statistics are arrayed in tabular form. For this reason, statistics documents are frequently known as tables.
- A database is a group of tables. Businesses and authorities companies that serve big clienteles, along with telecommunications groups, airlines, and credit score card firms, and banks, depend on sizeable databases for his or her billing, payroll, inventory, and advertising and marketing operations.
- Database control structures are statistics structures that human beings use to store, update, and examine non-geographic databases.
- Often, statistics documents are tabular in form, composed of rows and columns. Rows, additionally called information, correspond with person entities, along with consumer debts.
- Columns correspond with the diverse attributes related to every entity.
- Geographic statistics are a unique case: information correspond with places, now no longer human beings or debts. Columns constitute the attributes of places. The statistics with inside the following table, for example, encompass information for Pennsylvania counties.
- Columns include decided on attributes of every county, such as the county's ID code, name, and 1980 population.
- Database control structures are treasured due to the fact they offer stable manner of storing and updating statistics. Database directors can shield documents in order that most effective legal customers could make changes. DBMS offer transaction control capabilities that permit more than one customers to edit the database simultaneously.
- In addition, DBMS additionally offer state-of-the-art manner to retrieve statistics that meet person precise standards.
- In different words, they allow customers to pick statistics in reaction to specific questions. A query this is addressed to a database via a DBMS is known as a query.
- Database queries encompass fundamental set operations, such as union, intersection, and distinction. The manufactured from a union of or greater statistics documents is a unmarried report that consists of all information and attributes, without redundancy.
- An intersection produces a statistics report that incorporates most effective information found in all documents.
- A distinction operation produces a statistics report that removes information that seem in each authentic documents. (Try drawing Venn diagrams--intersecting circles that display relationships among or greater entities--to demonstrate the 3 operations. Then evaluate your cartoon to the Venn diagram example.)
- All operations that contain more than one statistics documents depend on the reality that each one documents include a not unusual place key.
- The key lets in the database gadget to narrate the separate documents. Databases that include several documents that proportion one or greater keys are known as relational databases.
- Database structures that allow customers to supply statistics from relational databases are known as relational database control structures. A not unusual place use of database queries is to become aware of subsets of information that meet standards hooked up via way of means of the person.
- For example, a credit score card organization can also additionally want to become aware of all debts which are 30 days or greater beyond due.
- A county tax assessor can also additionally want to list all residences now no longer assessed in the beyond 10 years. Or the U.S. Census Bureau can also additionally want to become aware of all addresses that want to be visited via way of means of census takers, due to the fact census questionnaires had been now no longer back via way of means of mail.
- DBMS software program companies have followed a standardized language known as SQL (Structured Query Language) to pose such queries.
Q14) Write a note on Case studies: demarcation of dam catchment and command area.
A14)
Surface water reassess are alternatively insufficient in peninsular India to fulfil the call for and need to be supplemented with groundwater. Productivity through groundwater is pretty excessive in comparison to floor water.
Cauvery basin is one of the high-satisfactory regulated and completely exploited basins and no documented estimates of groundwater are to be had for the basin with inside the critical a part of Tamil Nadu region.
Various geological and geo-morphological elements play a first-rate position with inside the prevalence, motion and capability of floor water reasserts. Survey of India (SOI) Topographic maps and LANDSAT TM satellite TV for pc pics had been used to put together diverse thematic layers along with geology, geomorphology, drainage pattern, lineaments, soil and slope, which impact the prevalence, motion, yield and nice of groundwater.
All those topics and their character functions had been then assigned weights in line with their relative significance in groundwater prevalence.
The thematic layers are then incorporated the use of ERDAS photograph processing software program and through using raster calculator equipment in ArcGIS platform, a composite groundwater capability index (GWPI) for the have a look at location become generated on the idea of which the general groundwater capability map become produced.
Three classes of groundwater capability zones had been delineated as poor; mild and excessive.
Groundwater prevalence is categorized as 'poor' in 63.34% of the have a look at location which substantiates synthetic recharge to reinforce groundwater with inside the region.
The institution extensively undertakes research in meteorology, carried out hydrology, physic-chemical strategies for water nice and hydraulics of surficial processes.
This laboratory includes 3 technical divisions viz., Hydrometeorology, Water Quality Analysis and Modelling and Surface Water Hydraulics.
The institution as a result conducts research in river and reservoir structures through area experimentations, mathematical modelling equipment and location precise table research.
Hydrometeorology Division
Hydrometeorology department become fashioned in 2012 through merging the erstwhile Physics (fashioned in 1947) and Statistics (fashioned in 1947) divisions to cater to the desires of the customers requiring precise research to be completed in carried out hydrology, meteorology carried out in hydrology and information.
In the preliminary segment of its functioning, the Physics department had contributed to water assets region through electric analogy method in supplying answers for PMF estimation, seepage, subsurface flows and flood routing.
With the utility of computer systems in hydrology and different fields, Physics department additionally inherited the mathematical modelling method and followed many a fashions and additionally advanced a few with inside the location of work.
On the opposite hand, the information department become conceived to cater to hydrology in addition to hydraulic modelling agencies in information evaluation of diverse initiatives adopting stochastic, probabilistic processes and optimization techniques.
Extreme Value Analysis (EVA) of Meteorological Parameters
Paperwork part of the technical and engineering investigations for designing Nuclear Power Plants (NPPs), which want to be safeguarded towards herbal hazards. (Madhya Pradesh), MythicVerdi (Gujarat) and Gorakhpur (Haryana), CWPRS completed EVA of meteorological parameters recorded on the meteorological stations, that are with inside the location of the NPPs and the effects received from the research might be beneficial to NPCIL for arriving at layout parameters for the proposed
Fig: Extreme Value analysis
Estimation of Probable Maximum Flood
The estimation of PMF for Narmada at numerous places i.e., Narmada Sager, Mahesh war, Omkareshwar and SardarSarovar turned into completed via way of means of this department beneath World Bank aide. The research had been completed adopting lumped conceptual version OPSET (changed model of Stanford Watershed Model). Flood moderation in river channel turned into modelled adopting Muskingum method. The version turned into advanced for the entire of Narmada catchment from its supply to SardarSarovar.
Evaluation of the version research carried out turned into made via way of means of World Bank specialists and PMF predicted via way of means of CWPRS turned into followed for layout.
Fig: Estimation of probable maximum flood
Flood Frequency Analysis
Estimation of most flood discharge (MFD) with a particular go back duration is vital for the layout of hydraulic structures. MFD may be correctly decided via way of means of becoming of chance distributions to the collection of recorded annual most discharge (AMD) data. An AMD is the best immediate discharge cost at a precise cross-phase of a herbal move at some stage in a whole hydrologic year (water year). CWPRS completed flood estimation research for rivers Krishna, Narmada, Godavari, Tapi, etc. The FFA approach turned into additionally followed via way of means of CWPRS to estimate the intense max/ min values of different meteorological parameters which include Rainfall, wind speed, temperatures, etc. Some of the tasks are NPPs of NPCIL in which the layout parameters had been derived and river valley tasks in which the rainfall turned into used to compute layout flood.
Fig: Flood Frequency Analysis
Unit - 6
GIS Data and Applications
Q1) Explain GIS data types and data representation
A1)
GIS DATA TYPES GIS era makes use of simple sorts of information.
These are:
1) Spatial information: describes absolutely and relative region of geographic capabilities.
2) Attribute information: describes traits of the spatial capabilities. These traits may be quantitative and/or qualitative in nature. Attribute information is frequently stated as tabular information.
SPATIAL DATA MODELS
1) Vector
2) Raster
3) Image
VECTOR
All spatial information fashions are strategies for storing the spatial region of geographic capabilities in a database. Vector garage implies the usage of vectors (directional lines) to symbolize a geographic feature.
RASTER
Raster information fashions contain the usage of a grid-mobileular information shape in which the geographic place is split into cells diagnosed via way of means of row and column. This information shape is normally known as raster.
IMAGE
Image information is most usually used to symbolize photo or pictorial information. The time period photo inherently displays a photo representation, and with inside the GIS world, differs notably from raster information.
Q2) Give advantages and disadvantages of vector information model.
A2)
Advantages of vector information model
• Data may be represented at its authentic decision and shape with out generalization.
• Graphic output is typically greater aesthetically pleasing (traditional cartographic representation);
• Since maximum information, e.g. Difficult reproduction maps, is in vector shape no information conversion is needed.
• Accurate geographic region of information is maintained.
• Allows for green encoding of topology, and as an end result greater green operations that require topological information, e.g. Proximity, community evaluation.
Disadvantages of vector information model
• The region of every vertex desires to be saved explicitly.
• For powerful evaluation, vector information ought to be transformed into a topological shape.
• Algorithms for manipulative and evaluation features are complex and can be processing intensive. Often, this inherently limits the capability for big information sets, e.g. a big wide variety of capabilities.
• Continuous information, which includes elevation information, isn't always effectively represented in vector shape. Usually giant information generalization or interpolation is needed for those information layers.
• Spatial evaluation and filtering inside polygons is impossible Advantages of raster information model
• The geographic region of every mobileular is implied via way of means of its role in the mobileular matrix.
Accordingly, aside from a foundation point, e.g. Bottom left corner, no geographic coordinates are saved.
• Due to the character of the information garage approach information evaluation is typically clean to application and short to perform.
• The inherent nature of raster maps, e.g. One characteristic maps, is perfectly suited for mathematical modeling and quantitative evaluation.
• Discrete information, e.g. Forestry stands, is accommodated similarly well as non-stop information, e.g. Elevation information, and helps the integrating of the 2 information types.
• Grid-mobileular structures are very well suited with raster-primarily based totally output devices, e.g. Electrostatic plotters, photo terminals. Disadvantages of raster information model
• The mobileular length determines the decision at which the information is represented.
• It is especially hard to competently constitute linear capabilities relying at the mobileular decision.
Accordingly, community linkages are hard to establish.
• Processing of related characteristic information can be bulky if big quantities of information exists.
Raster maps inherently mirror only one characteristic or feature for a place.
• Since maximum enter information is in vector shape, information ought to undergo vector-to-raster conversion.
Besides expanded processing necessities this will introduce information integrity issues due to generalization and desire of beside the point mobileular length.
• Most output maps from grid-mobileular structures do now no longer agree to high quality cartographic desires.
Q3) Explain Data Synthesis and Visualization
A3)
The present established programs for cartography (ESRI, ERDAS, LHS, Multispeed and etc.), permit synthesizing polygonal and hyper spectral pics.
The recognized methods, like which are described [1-3], discover multispectral pix of items to show them. These responsibilities require pixel category, which isn't always an easy operation and may be done with the aid of using numerous methods.
It takes lots time to do it. The approach offered right here does now no longer require initial category. It can therefore be used with the intention to swiftly carry out the responsibilities of visible interpretation.
We shall illustrate this approach with an instance of the synthesis of n-area aero pics. We anticipate that the pics are superimposed.
Everyone pixel of such set of the pix has n the spectral traits or attributes.
A pixel with all its attributes is chosen as a well-known version.
Apart from the spectral traits a few different attributes can be assigned to a pixel. These may be acquired by way of initial processing of every spectral photo or a hard and fast of pix.
The attributes of the usual version are as compared to the ones of all different pixels. The synthesis of the pix is produced primarily based totally on a precept of comparable attributes.
The maximum brightness is assigned to the pixels that resemble maximum the usual version. The brightness fee of the relaxation of the pixels is calculated on the idea in their resemblance with the usual version.
Different attributes may be hired as a degree of resemblance, specifically the ones which are used for category with inside the famous software programs Multispeed, ESRI, ERDAS.
It may be the Euclidean metric with inside the n-dimensional area of the attributes or the maximal distinction among values of the identical attributes. No extra data is wanted for this metrics. If the data at the opportunity distribution of the usual version attributes is recognized, one could employ the conditional probabilities (the Bayesian approach) to assess resemblance.
All the traits which have been anticipated earlier can be concerned whilst growing a resemblance metric.
The very last synthesized photo is offered in grayscale. It carries the data on a diploma of similarity of the attributes of each pixel to the ones of the usual version. The synthesis time of a photo relies upon most effective at the time had to calculate the attributes of each pixel.
When the use of most effective the experimentally measured attributes, along with the spectral values of brightness, the very last photo is fashioned in actual time, because the calculation of resemblance is done instantly.
In addition it's far of the significance that this approach entails no multiplexing. And throughput of transmitting of data is excessive.
Note, that the recognized approach “infrared satiation vision” visualizes preliminary pix in numerous spectral durations into one photo in which every of preliminary photo is submitted with the aid of using monochromatic satiatioñ red, inexperienced or blue (RGB).
But multichannel switch of the data is vital in that case.
Q4) Give various example of data representation.
A4)
EXAMPLES
- We gift the outcomes of synthesis of imaging data (aero pics of a terrestrial floor) that acquired in nine spectral bands. The Euclidean metric in nine-dimensional area of spectral attributes have been used. Pixels with numerous coordinates had been decided on as well-known models.
- The first column of discern 1 carries the pics of terrestrial floor in nine spectral ranges. In the second one column we gift the outcomes of photo synthesis.
- The maximum brightness degree is assigned to pixels with spectral attributes bearing the very best resemblance to its well-known version.
- The others pixels have the brightness placing that corresponds to the extent of resemblance of the attributes.
- The well-known version coordinates are marked subsequent to the very last pix. One can have a look at that the synthesized pix are lots greater detailed, than the pix similar to every spectral band.
- The pixels of the synthesized photo, which have an excessive degree of resemblance than a positive threshold fee, can be highlighted in color.
- The discern 2 gives the synthesis outcomes of the pics in four spectral bands with one-of-a-kind threshold values.
- Note that this photo transformation set of rules is likewise appropriate for processing panchromatic pix.
- The regions of the photo which are of greater hobby to the spectator may be emphasized with the very best brightness.
- It is plain that this processing approach can't boom the decision of a panchromatic photo except extra data is used, however it may boom its perceptibility.
- The degree of depth with inside the pics is decided with the aid of using the reflective cap potential of items and relies upon at the ecosystem condition, the exposition parameters, etc.
- The well-known version is acquired below the identical conditions; consequently the end result of the synthesis does now no longer rely on those factors. In the given instance most effective spectral values of brightness have been used as attributes.
- Apart from the measured spectral values of brightness one may want to use a few extra attributes acquired by way of processing the preliminary data: as an instance structural, contextual and textural attributes. The desire of the attributes can adjust the end result significantly.
Q5) Explain data acquisition.
A5)
Data acquisition is the method of sampling alerts that degree actual international bodily situations and changing the ensuing samples into virtual numeric values that may be manipulated via way of means of a computer.
Data acquisition structures, abbreviated via way of means of the initializes DAS, DAQ, or DAU, commonly convert analog waveforms into virtual values for processing.
The additives of records acquisition structures include: Sensors, to transform bodily parameters to electric alerts. Signal conditioning circuitry, to transform sensor alerts right into a shape that may be transformed to virtual values. Analog-to-virtual converters, to transform conditioned sensor alerts to virtual values.
Although records to be had from numerous earth statement structures were robotically used in lots of useful resource packages, but there were gaps, and records wishes of packages at distinctive ranges of information have now no longer been met.
There is a developing call for availability of records at better receptivity, at better spatial decision, in extra and narrower spectral bands etc. Some of the thrust regions of packages mainly with inside the Indian context are;
- Management of herbal sources to make certain sustainable boom in agricultural manufacturing, -
Study the kingdom of the environment, its tracking and evaluation of the effect of. Numerous improvement movements at the environment,
- Updating and technology of massive scale topographical maps.
- Exploration/exploitation of marine and mineral sources and
- Operational meteorology and reading numerous land and oceanic methods to understand/expect international weather adjustments.
Each of those thrust location of software has many additives, associated with simple useful resource regions which includes agriculture, forestry, water sources, minerals, marine sources etc. and the sector of cartography. Observational necessities for primary packages were summarized as under.
Monitoring plants fitness from area stays the maximum crucial observational parameter with packages, in agriculture, forestry, environment, hydrology etc. Vegetation extent, amount and temporal adjustments are the 3 primary necessities which aren't absolutely found out with RS records to be had.
Vegetation productivity, wooded area biomass, cover moisture status, cover biogeochemistry are a few examples. Crop manufacturing forecasting is a crucial software location. Remotely sensed records has been used for identity of plants and their acreage estimation.
Fragmented holdings, massive unfold in crop calendars and distinctive control practices retain to pose an assignment lo faraway sensing. Remotely sensed records at lots better spatial decision than hitherto to be had in addition to at extra receptivity are required to satisfy this need.
Non-availability of cloud-unfastened records with inside the Khari season is one of the severe troubles in operational use of faraway sensing for crop inventory. Synthetic aperture radar records al X & Ku bands is vital to satisfy this call for. Nutrient stress/sickness detection calls for observations in slender spectral bands. In case of forestry packages, multispectral records at excessive spatial decision of the order of five to ten meters is needed to make running plans at wooded area compartment level.
Observations from area for deriving tree peak are required for extent estimation. Observations with inside the center infrared location could substantially beautify functionality of satellite TV for pc faraway sensing in wooded area hearth place detection.
Temporal, spatial and spectral observational necessities in numerous packages on plants viewing are diverse, as they deal with methods at distinctive spatial and time scales. Hence, it might be profitable to deal with this trouble in 3 wide categories.
Q6) What is geo-referencing of data.
A6)
Geo-referencing method that the inner coordinate device of a map or aerial image photo may be associated with a geographic coordinate device.
The maximum seen impact of geo-referencing is that show software program can display floor coordinates (together with latitude/longitude or UTM coordinates) and additionally degree floor distances and regions. In different words, geo-referencing method to partner a virtual photo document with places in bodily space.
The time period is generally used with inside the geographic records structures discipline to explain the technique of associating a bodily map or raster photo of a map with spatial places.
Geo-referencing can be implemented to any form of item or shape that may be associated with a geographical location, together with factors of interest, roads, places, bridges, or buildings. Geographic places are maximum generally represented the use of a coordinate reference device, which in flip may be associated with a geodetic reference device together with WGS-84.
Examples encompass organizing the appropriate function of an aerial picture graph inside a map or locating the geographical coordinates of an area call or avenue address (Geocoding).
Geo-referencing is essential to make aerial and satellite TV for pc imagery, typically raster pictures, beneficial for mapping because it explains how different information, together with the above GPS factors, relate to the imagery.
Very vital records can be contained in information or pictures that had been produced at a one-of-a-kind factor of time. It can be preferred both to mix and examine this information with that presently available. The latter may be used to research the modifications with inside the functions below have a look at over a length of time.
Different maps might also additionally use one-of-a-kind projection structures. Geo-referencing gear include techniques to mix and overlay those maps with minimal distortion.
Using geo-referencing techniques, information acquired from surveying gear like general stations can be given a factor of reference from topographic maps already available.
It can be required to set up the connection among social survey outcomes that have been coded with postal codes or avenue addresses and different geographic regions together with census zones or different regions utilized in public management or provider planning.
Q7) What is projection system?
A7)
Projection system:
- A projection is the approach via way of means of that you show the coordinate gadget and your records on a flat floor, consisting of a bit of paper or a virtual screen.
- Mathematical calculations are used to transform the coordinate gadget used at the curved floor of earth to 1 for a flat floor.
- Since there may be no ideal manner to transpose a curved floor to a flat floor without a few distortion, diverse map projections exist that offer exceptional properties.
- Some maintain shape, even as others maintain distance. Some maintain vicinity or direction. The extent, location, and belongings you need to maintain should tell your preference of map projection.
- There are extra than 4,000 coordinate structures with inside the ArcGIS platform, so it's far possibly you will locate one to in shape your records.
- If now no longer, you could create a custom coordinate gadget to show the records. ArcGIS Pro projects records at the fly so any records you upload to a map adopts the coordinate gadget definition of the primary layer delivered.
- As lengthy because the first layer delivered has its coordinate gadget efficiently defined, all different records with accurate coordinate gadget data projects at the fly to the coordinate gadget of the map?
- This technique helps exploring and mapping records, however it have to now no longer be used for evaluation or editing, due to the fact it may result in inaccuracies from misaligned records amongst layers.
- Data is likewise slower to attract while it's far projected at the fly.
- If you would like to carry out evaluation or edit the records, first assignment it right into a constant coordinate gadget shared via way of means of all of your layers.
- This creates a new edition of your records. After defining the coordinate gadget that fits your records, you can nonetheless need to apply records in an exceptional coordinate gadget.
- This is while modifications are useful. Transformations convert records among exceptional geographic coordinate structures or among exceptional vertical coordinate structures.
- Unless your records strains up, you will come upon problems and inaccuracies in any evaluation and mapping you carry out at the mismatched records.
Q8) Write a note on vector data.
A8)
Vector Data
Vector information is what maximum humans think about once they don't forget spatial information.
Data on this layout includes factors, traces or polygons. At its handiest level, vector information accommodates of person factors saved as coordinate pairs that suggest a bodily place with inside the world.
These factors may be joined, in a specific order, to shape traces or joined into closed regions to shape polygons.
Vector information is extraordinarily beneficial for storing and representing information that has discrete boundaries, which include borders or constructing footprints, streets and different delivery links, and place factors.
Ubiquitous on-line mapping portals, which include Google Maps and Open Street Maps, gift information on this layout.
Q9) What is raster data.
A9)
Raster Data
Raster information gives an illustration of the arena as a floor divided up right into an ordinary grid array, or cells, wherein every of those cells has an related value. In an exchange sense, we are able to don't forget a virtual picture as an instance of a raster dataset.
Here every cell, which on this example is called a pixel, corresponds to a specific coloration value. When transferred right into a GIS setting, the cells in a raster grid can doubtlessly constitute different information values, which include temperature, rainfall or elevation.
The major factor of distinction among the virtual picture and the GIS illustration is that with inside the GIS there may be accompanying information detailing wherein the cells may be discovered on a globe and the way large those cells may be.
Q10) How raster to vector conversion will be done?
A10)
Raster to vector conversion:
Extracting vector capabilities from a picture (or “vector zing a raster”) includes changing organizations of raster pixels into polygons.
Maybe you’d want to digitize a scanned map, convert a DEM to polygons primarily based totally on elevation, extract textual content from a picture, or in any other case generate polygons from a provided picture.
There are many viable approaches to address those problems, a few less complicated than others, a few greater accurate.
Here are 3 approaches you could do it through processing your raster in an FME information integration workflow.
1. Trace and picture to transform it to CAD or GIS Pot race is a loose device for turning bitmaps into vector graphics.
In FME, you could leverage it through the custom transformer Pot race Caller. Converting raster to vector on this context includes
3 steps: Prepare the raster (e.g. Discover color stages with inside the enter JPEG) Call Pot race Prepare the output (e.g. Generalize polygons, fashion for AutoCAD) in the underneath example, the person has an RGB picture of a place and desires to extract CAD polygons of homes.
In the picture, homes are proven in a darker color.
Preparing the raster consequently includes classifying cooler stages so the range of colors is reduced — extracting the darkish color representing homes and leaving the whole lot else because the background.
Preparing the output includes smoothing the polygons generated through Pot race so we become with exceptional blocky shapes rather than loopy 1000-sided chiliad guns.
2. Extract textual content from a picture with Optical Character Recognition Converting and picture to textual content may be performed through leveraging Tess erect, a loose device that plays OCR.
In FME, this could be performed with the custom transformer TesseractCaller. OCR is beneficial for digitizing scanned maps and documents, making the information searchable and index able. As above, this workflow additionally includes pre-processing steps to outline cooler stages, and making ready information for the output format.
3. Extract polygons from a raster primarily based totally on pixel values
This is likewise recognized as “classifying” a raster and includes producing a polygon for every contiguous region of pixels with comparable values.
FME has assist for a number of raster and imagery formats, in addition to a number of very effective capability for operating with raster’s.
To classify a raster and convert organizations of pixels to polygons, ship it through the Raster to PolygonCoercer. While this approach is easier because it doesn’t contain downloading the 3rd-celebration device Pot race, notice it’s greater in depth and consequently slower than Pot race.
If you've got a huge raster, it’ll likely be greater really well worth your whilst to apply approach
Q11) Explain various terms used in vector data.
A11)
Object Oriented
The tabular version is the way wherein maximum early GIS software program applications saved their characteristic records. The subsequent 3 fashions are the ones maximum generally applied in database control system (DBMS). The item orientated is more modern however hastily gaining reputation for a few application.
A quick assessment of every version is given below. Tabular Model: -The easy tabular version shops characteristic records as sequential records documents with constant formats. This form of records version is previous in GIS arena. It lacks any approach of checking records integrity, in addition to being inefficient with admire to records garage.
Hierarchical Model: -
The hierarchical database organizes records in a tree shape. Data is dependent downward in a hierarchy of tables. Any degree with inside the hierarchy will have limitless children, however any baby will have handiest one parent. Hierarchical DBMS have now no longer won any important reputation to be used inside GIS. They are orientated for records units which might be very stable, in which number one courting a few of the records extrude regularly or by no means at all. Also, the difficulty at the variety of mother and father that and detail can also additionally have isn't usually conducive to real geographic phenomenon.
Network Model: -
The community database organizes records in a community or plea shape. Any column in a plea shape may be related to another like a tree shape. A plea shape may be defined in phrases of mother and father and children. This version permits having a couple of parent.
Network DBMS have determined now no longer an awful lot greater reputation in GIS than the hierarchical DBMS.
They have the identical flexibility boundaries as hierarchical database: however, the greater effective shape for representing records relationships permits a greater sensible modeling of geographic phenomena.
In this regard it is straightforward to lose manage and knowledge of the relationships among factors.
Relational Model: -
The relational database organizes records in tables. Each desk is recognized with the aid of using a completely unique desk name, and is prepared with the aid of using rows and columns.
Each column inside a desk additionally has a completely unique name. Columns shop the values for a particular characteristic, e.g. Cowl group, tree height.
In GIS every row is generally related to a separate function, e.g. a forestry stand. Accordingly, every row might be constructed from numerous columns, every column containing a particular fee for that geographic function. In this version a key represents one or greater attributes whose fee can uniquely become aware of a file in a desk.
Therefore, a key not unusual place to 2 tables can set up connection among corresponding data with inside the tables.
Usually right here varieties of desk are defined- the supply desk & the vacation spot desk. If the reason is to feature characteristic records from a desk to the function characteristic desk, then the function characteristic desk is the vacation spot desk and the alternative one is the supply desk. Owing to this way, 3 varieties of relationships may be created.
Object Oriented Model: -
The item orientated records version manages records via item. An item is a group of records factors and operations that collectively are taken into consideration as unmarried entity. The item orientated database is an enormously new version.
This technique has the enchantment that querying could be very natural, as functions may be bundled collectively with attributes on the database. Today, just a few GIS applications are selling the usage of this characteristic records version. However, preliminary impressions imply that this technique can also additionally maintain many operational advantages with admire to geographic records processing.
Q12) What is remote sensing data in GIS?
A12)
Any region on earth has large quantities of facts tied to it, which now no longer most effective encompass bodily features, however political, monetary and social facts, as well. GIS allows the technique through which we will visualize, examine and recognize this facts.
Remote sensing is one of the techniques typically used for accumulating bodily facts to be incorporated into GIS.
Remote sensors acquire facts from gadgets on earth with none direct contact. They do that through detecting strength contemplated from the earth, and are generally established on satellites or aircraft.
Remote sensing generation has come to be a lot greater prevalent, correct and available in current years, and covers an extensive variety of engineering applications.
First, engineers use faraway sensing to assist them decide the topography of our earth. Three-dimensional pix of the earth’s floor (proven in Figure 1) may be generated the usage of LiDAR, which stands for Light Detection and Ranging.
LiDAR sensors use pulsed lasers blended with role and orientation facts to acquire dense agencies of elevation factors known as factor clouds.
These factor clouds can then be processed into contours and virtual elevation models (DEMs) representing the form of the earth.
Engineers can use a DEM to calculate a completely brief and pretty correct estimate of the extent of earth-transferring essential to expand a tract of land. Remote sensing is likewise used to screen land use, which aids engineers and planners in making choices at some point of the direction of a layout project.
Optical sensors degree the sun radiation contemplated from the floor of the earth. The distinctive wavelengths detected are blended, ensuing in a photograph that resembles a photo taken through a digital of the earth’s floor.
Remote sensing is a sort of geospatial generation that samples emitted and contemplated electromagnetic (EM) radiation from the Earth’s terrestrial, atmospheric, and aquatic ecosystems so one can stumble on and screen the bodily traits of a place without making bodily contact.
This approach of facts series generally entails aircraft-primarily based totally and satellite-primarily based totally sensor technologies, which might be categorized as either passive sensors or energetic sensors.
Passive sensors reply to outside stimuli, accumulating radiation this is contemplated or emitted through an item or the encompassing space.
The maximum not unusual place supply of radiation measured through passive faraway sensing is contemplated sunlight. Popular examples of passive faraway sensors encompass charge-coupled devices, movie photography, radiometers, and infrared.
Active sensors use inner stimuli to acquire facts, emitting strength so one can experiment gadgets and regions whereupon a sensor measures the strength contemplated from the target.
RADAR and LiDAR are traditional energetic faraway sensing equipment that degree the time postpone among emission and go back so one can set up the region, direction, and velocity of an item.
The faraway sensing facts amassed is then processed and analyzed with faraway sensing hardware and pc software that is to be had in quite a few proprietary and open supply applications.
Q13) Explain GIS database and database management system.
A13)
- A database is a dependent series of statistics documents. A database control gadget (DBMS) is a software program package deal that lets in for the creation, storage, maintenance, manipulation, and retrieval of big datasets which are disbursed over one or greater documents.
- A DBMS and its related capabilities are commonly accessed via industrial software program applications along with Microsoft Access, Oracle, FileMaker Pro, or Avenues My Database.
- Database control usually refers back to the control of tabular statistics in row and column layout and is often used for personal, business, authorities, and clinical endeavors.
- Geospatial database control structures, alternatively, encompass the capability of a DBMS however additionally include particular geographic statistics approximately every statistics factor along with identity, location, shape, and orientation.
- Integrating this geographic statistics with the tabular characteristic statistics of a classical DBMS offer customers with effective gear to visualize and solution the spatially express questions that stand up in an increasing number of technological society.
- Clarita’s and comparable groups use database control structures (DBMS) to create the "way of life segments" that I mentioned with inside the preceding section. Basic database ideas are vital considering the fact that GIS contains a great deal of the capability of DBMS.
- Digital statistics are saved in computer systems as documents. Often, statistics are arrayed in tabular form. For this reason, statistics documents are frequently known as tables.
- A database is a group of tables. Businesses and authorities companies that serve big clienteles, along with telecommunications groups, airlines, and credit score card firms, and banks, depend on sizeable databases for his or her billing, payroll, inventory, and advertising and marketing operations.
- Database control structures are statistics structures that human beings use to store, update, and examine non-geographic databases.
- Often, statistics documents are tabular in form, composed of rows and columns. Rows, additionally called information, correspond with person entities, along with consumer debts.
- Columns correspond with the diverse attributes related to every entity.
- Geographic statistics are a unique case: information correspond with places, now no longer human beings or debts. Columns constitute the attributes of places. The statistics with inside the following table, for example, encompass information for Pennsylvania counties.
- Columns include decided on attributes of every county, such as the county's ID code, name, and 1980 population.
- Database control structures are treasured due to the fact they offer stable manner of storing and updating statistics. Database directors can shield documents in order that most effective legal customers could make changes. DBMS offer transaction control capabilities that permit more than one customers to edit the database simultaneously.
- In addition, DBMS additionally offer state-of-the-art manner to retrieve statistics that meet person precise standards.
- In different words, they allow customers to pick statistics in reaction to specific questions. A query this is addressed to a database via a DBMS is known as a query.
- Database queries encompass fundamental set operations, such as union, intersection, and distinction. The manufactured from a union of or greater statistics documents is a unmarried report that consists of all information and attributes, without redundancy.
- An intersection produces a statistics report that incorporates most effective information found in all documents.
- A distinction operation produces a statistics report that removes information that seem in each authentic documents. (Try drawing Venn diagrams--intersecting circles that display relationships among or greater entities--to demonstrate the 3 operations. Then evaluate your cartoon to the Venn diagram example.)
- All operations that contain more than one statistics documents depend on the reality that each one documents include a not unusual place key.
- The key lets in the database gadget to narrate the separate documents. Databases that include several documents that proportion one or greater keys are known as relational databases.
- Database structures that allow customers to supply statistics from relational databases are known as relational database control structures. A not unusual place use of database queries is to become aware of subsets of information that meet standards hooked up via way of means of the person.
- For example, a credit score card organization can also additionally want to become aware of all debts which are 30 days or greater beyond due.
- A county tax assessor can also additionally want to list all residences now no longer assessed in the beyond 10 years. Or the U.S. Census Bureau can also additionally want to become aware of all addresses that want to be visited via way of means of census takers, due to the fact census questionnaires had been now no longer back via way of means of mail.
- DBMS software program companies have followed a standardized language known as SQL (Structured Query Language) to pose such queries.
Q14) Write a note on Case studies: demarcation of dam catchment and command area.
A14)
Surface water reassess are alternatively insufficient in peninsular India to fulfil the call for and need to be supplemented with groundwater. Productivity through groundwater is pretty excessive in comparison to floor water.
Cauvery basin is one of the high-satisfactory regulated and completely exploited basins and no documented estimates of groundwater are to be had for the basin with inside the critical a part of Tamil Nadu region.
Various geological and geo-morphological elements play a first-rate position with inside the prevalence, motion and capability of floor water reasserts. Survey of India (SOI) Topographic maps and LANDSAT TM satellite TV for pc pics had been used to put together diverse thematic layers along with geology, geomorphology, drainage pattern, lineaments, soil and slope, which impact the prevalence, motion, yield and nice of groundwater.
All those topics and their character functions had been then assigned weights in line with their relative significance in groundwater prevalence.
The thematic layers are then incorporated the use of ERDAS photograph processing software program and through using raster calculator equipment in ArcGIS platform, a composite groundwater capability index (GWPI) for the have a look at location become generated on the idea of which the general groundwater capability map become produced.
Three classes of groundwater capability zones had been delineated as poor; mild and excessive.
Groundwater prevalence is categorized as 'poor' in 63.34% of the have a look at location which substantiates synthetic recharge to reinforce groundwater with inside the region.
The institution extensively undertakes research in meteorology, carried out hydrology, physic-chemical strategies for water nice and hydraulics of surficial processes.
This laboratory includes 3 technical divisions viz., Hydrometeorology, Water Quality Analysis and Modelling and Surface Water Hydraulics.
The institution as a result conducts research in river and reservoir structures through area experimentations, mathematical modelling equipment and location precise table research.
Hydrometeorology Division
Hydrometeorology department become fashioned in 2012 through merging the erstwhile Physics (fashioned in 1947) and Statistics (fashioned in 1947) divisions to cater to the desires of the customers requiring precise research to be completed in carried out hydrology, meteorology carried out in hydrology and information.
In the preliminary segment of its functioning, the Physics department had contributed to water assets region through electric analogy method in supplying answers for PMF estimation, seepage, subsurface flows and flood routing.
With the utility of computer systems in hydrology and different fields, Physics department additionally inherited the mathematical modelling method and followed many a fashions and additionally advanced a few with inside the location of work.
On the opposite hand, the information department become conceived to cater to hydrology in addition to hydraulic modelling agencies in information evaluation of diverse initiatives adopting stochastic, probabilistic processes and optimization techniques.
Extreme Value Analysis (EVA) of Meteorological Parameters
Paperwork part of the technical and engineering investigations for designing Nuclear Power Plants (NPPs), which want to be safeguarded towards herbal hazards. (Madhya Pradesh), MythicVerdi (Gujarat) and Gorakhpur (Haryana), CWPRS completed EVA of meteorological parameters recorded on the meteorological stations, that are with inside the location of the NPPs and the effects received from the research might be beneficial to NPCIL for arriving at layout parameters for the proposed
Fig: Extreme Value analysis
Estimation of Probable Maximum Flood
The estimation of PMF for Narmada at numerous places i.e., Narmada Sager, Mahesh war, Omkareshwar and SardarSarovar turned into completed via way of means of this department beneath World Bank aide. The research had been completed adopting lumped conceptual version OPSET (changed model of Stanford Watershed Model). Flood moderation in river channel turned into modelled adopting Muskingum method. The version turned into advanced for the entire of Narmada catchment from its supply to SardarSarovar.
Evaluation of the version research carried out turned into made via way of means of World Bank specialists and PMF predicted via way of means of CWPRS turned into followed for layout.
Fig: Estimation of probable maximum flood
Flood Frequency Analysis
Estimation of most flood discharge (MFD) with a particular go back duration is vital for the layout of hydraulic structures. MFD may be correctly decided via way of means of becoming of chance distributions to the collection of recorded annual most discharge (AMD) data. An AMD is the best immediate discharge cost at a precise cross-phase of a herbal move at some stage in a whole hydrologic year (water year). CWPRS completed flood estimation research for rivers Krishna, Narmada, Godavari, Tapi, etc. The FFA approach turned into additionally followed via way of means of CWPRS to estimate the intense max/ min values of different meteorological parameters which include Rainfall, wind speed, temperatures, etc. Some of the tasks are NPPs of NPCIL in which the layout parameters had been derived and river valley tasks in which the rainfall turned into used to compute layout flood.
Fig: Flood Frequency Analysis