Geographic information system (gis)

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basic concept of geographic data,GIS and its component,data acquisition ,raster, vector formats,spatial data,topology and data model data output ,GIS applications

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Geographic information system (gis)

  1. 1. UNIT IV GEOGRAPHIC INFORMATION SYSTEM (GIS) Geographic Information System is a System containing Information which is geographic in nature. GIS can be defined as - A System which involves collecting/capturing, storing, processing and manipulating, analyzing, managing, retrieving and displaying data (information) which is, essentially, referenced to the real-world or the earth (i.e. geographically referenced). Explanation of the Definition 1. Collection/Capturing The dataset collected for GIS may be in the form of hard copy maps, satellite images, survey data or other data obtained from other primary and secondary sources. Collection of data depends on the objective of the assignment. Data capturing involves digitization of hard copy maps and satellite images. 2. Storage In GIS Storage means not merely storing whatever data we have collected. The collected data is converted in usable GIS format and then finally stored for further use either on computer hard disk or in other storage devices (CD, DVD, magnetic tapes etc.)
  2. 2. …….Cont. 3. Processing and Manipulation The collected and stored dataset is imported and converted into layers. Then required attributes are attached. Then data is processed for refinement, removing errors and preparing it for further GIS-based analysis. Data manipulation is essential so that it can be represented in proper understandable form. 4. Analysis Analysis of GIS data is required to convert it into desired outputs. There are many type of analysis in GIS which is (or are) to be done is objective dependant. The analysis may be statistical, spatial or specialized (like network analysis, utility analysis etc. Need not to say GIS analysis requires skilled professionals. 5. Management Data management is essential and very important part of GIS for storing, managing and properly maintaining GIS database. 6. Retrieval In GIS, data can be retrieved through SQL or spatial queries. Some software provide tools to retrieve data by simply selecting the features. Retrieval is used for getting information about the features of our interest. 7. Display Displaying of final output may in many forms. These may be hard copy printouts, on-screen display of maps, internet-based map display (through Internet Map Servers) or in the form of presentation (like power point).
  3. 3. GIS can create many different types of Maps
  4. 4. GIS components Spatial data GIS Computer hardware / software tools ? Specific applications / decision making objectives 8
  5. 5. GIS Components Following five essential components make a complete Geographic Information System. Even imagine about GIS is not possible if we remove one of these components. All components are important (however some may be more some may be less). 1. Hardware 2. Software 3. Data 4. Method 5. People
  6. 6. Types of GIS Data GIS data can be broadly described as 1. Spatial data and 2. Non-spatial data. Spatial data Spatial data is geographical representation of features. In other words, spatial data is what we actually see in the form of maps (containing real-world features) on a computer screen. Spatial data can further be divided into following two types; a). Vector data b) Raster data.
  7. 7. Spatial data
  8. 8. What makes data spatial? OR Features /Characteristic of Spatial Data Grid co-ordinate Place Name Latitude / Longitude Post Code Description Distance & bearing 12
  9. 9. Vector Data: It represent any geographical feature through point, line or polygon or combination of these. Point: A point in GIS is represented by one pair of coordinates (x & y). It is considered as dimension-less object. Most of the times a point represent location of a feature (like cities, wells, villages etc.). Line: A line or arc contains at least two pairs of coordinates (say- x1, y1 & x2, y2). In other words a line should connect minimum two points. Start and end points of a line are referred as nodes while points on curves are referred as vertices. Points at intersections are also called as nodes. Roads, railway tracks, streams etc. are generally represented by line. Polygon (or Area) : It is a closed line with area. It takes minimum three pairs of coordinates to represent an area or polygon. Extent of cities, forests, land use etc. is represented by polygon.
  10. 10. Raster Data Raster data is made up of pixels. It is an array of grid cells with columns and rows. Each and every geographical feature is represented only through pixels in raster data. There is nothing like point, line or polygon. If it is a point, in raster data it will be a single pixel, a line will be represented as linear arrangement of pixels and an area or polygon will be represented by contiguous neighboring pixels with similar values. In raster data one pixel contain only one value (unlike vector data where a point, a line or a polygon may have number of values or attributes) that’s why only one geographical feature can be represented by a single set of pixels or grid cells. Hence a number of raster layers are required if multiple features are to be considered (For example- land use, soil type, forest density, topography etc.). As discussed earlier digital satellite images are also in raster format.
  11. 11. NON-SPATIAL DATA Attributes attached to spatial data are referred to as non-spatial data. Whatever spatial data we see in the form of a colourful map on a computer screen is a presentation of information which remains stored in the form attribute tables. Attributes of spatial data must contain unique identifier for each object. There may be other field also containing properties/information related a spatial feature. Attribute table of spatial data also contains ‘x’ and ‘y’ location (i.e. latitude/longitude or easting/northing) of features; however in some GIS software these columns may remain ‘invisible’. For example- if we are doing demographic analysis of villages then attributes of each point (representing a village) must have a unique village ID and other demographic information like total population, number of males & females, number of children etc. In another example- if we are doing some GIS analysis related to road then each road must have its unique Road ID. Other attributes may include like road length, road width, current traffic volume, number of stations etc.
  12. 12. Input data for GIS
  13. 13. Input data for GIS (or Data sources/Data acquisition) Input data for GIS cover all aspects of capturing spatial data and attribute data. The sources of spatial data are existing maps, aerial photographs, satellite imageries, field observations, and other sources as shown in figure. The spatial data not in digital form are converted into standard digital form using digitizer or scanner for use in GIS. The entire process is reffered as data aquisition Maps Aerial Photo Satellite Imageries Field Observations Other Sources Digital Input Data Terrain data GIS Database
  14. 14. Working with GIS Database Data storage sub system GIS Database Data and analysis subsystem Modelling and analysis Reporting and output subsystem GIS Output as per User
  15. 15. Spatial Data Modelling To make geographic data useful, it should be encoded in digital form, and organized as a digital geographical database that creats a perception of the real world similar to the perception created by the paper maps. Type of spatial data modelling : 1. object based model. The geographic space is treated to be filled by discrete and identifiable objects. A object which is a spatial feature, has identifiable boundaries ,relevance to some intended application, and can be described by one or moor more characteristics known as attributes. spatial object such as • Exact objects (building ,roads etc) • Inexact objects(landform fearture , and wildlife habitat) 1. Field based model. The field based model treats geographic space as populated by one or more spatial phenomena of real world feartures varing continuously over space with no obvious or specific extend
  16. 16. Database Models Model is a set of plans for a building, therefore, modelling of database means a methodologies to be followed for some specified purpose. It specify the structure of database. Common approach for this purpose include; 1. Digital Elevation Model (DEM) 2. Triangulated Irregular Network (TIN) Digital Elevation Model (DEM) It is a sampled array of elevations (z) that are at regularly spaced intervals in the x and y directions. Two approaches for determining the surface z value of a location between sample points are followed. a). Lattice: each mesh point represents a value on the surface only at the center of the grid cell. The z-value is approximated by interpolation between adjacent sample points; it does not imply an area of constant value. b). Surface grid: considers each sample as a square cell with a constant surface value. Advantages • Simple conceptual model • Data cheap to obtain • Easy to relate to other raster data • Irregularly spaced set of points can be converted to regular spacing by interpolation • Linear features not well represented Disadvantages Does not conform to variability of the terrain
  17. 17. Representation of DEM After a satellite image has been combined with a DEM, one gets a representation like that shown here and known as Digital Terrain Model (DTM).
  18. 18. Triangulated Irregular Network (TIN) It is a set of adjacent, nonoverlapping triangles computed from irregularly spaced points, with x, y horizontal coordinates and z vertical elevations. • Advantages – Can capture significant slope features (ridges, etc) – Efficient since require few triangles in flat areas – Easy for certain analyses: slope, aspect, volume • Disadvantages – Analysis involving comparison with other layers difficult
  19. 19. GIS Data Models The real world can only be depicted in a GIS through the use of models that define phenomena in a manner that computer systems can interpret and perform meaningful analysis. There are two types of GIS Data Models 1. Vector Model 2. Raster Model Raster data model – location is referenced by a grid cell in a rectangular array (matrix) – attribute is represented as a single value for that cell – much data comes in this form • images from remote sensing (LANDSAT, SPOT) • scanned maps • elevation data from USGS – best for continuous features: • • • • elevation temperature soil type land use Vector data model – location referenced by x,y coordinates, which can be linked to form lines and polygons – attributes referenced through unique ID number to tables – much data comes in this form • DIME and TIGER files from US Census • DLG from USGS for streams, roads, etc • census data (tabular) – best for features with discrete boundaries • property lines • political boundaries • transportation
  20. 20. GIS Applications The application of geospatial sciences has spread very fast and wide over the past few decades. User's of GIS's range from indigenous people, communities, research institutions, environmental scientists, health organizations, land use planners, businesses, and government agencies at all levels. Environment 1. Conservation & Monitoring 2. Planning & Policy 3. Wetland Management 4. Wildlife Management 5. Forest Management 6. Water Pollution 7. Air Pollution 8. Climate Change Geology 1. Mineral & Mining 2. Geomorphology 3. Products Agriculture 1. Overview 2. Crop Production 3. Crop Pattern 4. Crop Yield 5. Irrigation 6. Soil Management Urban Planning 1. Urban Sprawl 2. Fringe Area Development 3. Urban Agglomeration 4. Emerging Technologies
  21. 21. GIS Applications Natural Resource Management 1. Mountain 2. Water Resources 3. Ocean 4. Coastal Zone Management Land Information System 1. Policy 2. Rural & Cadastral 3. Urban 5. Corporate Case Studies Natural Hazard Management 1. Earthquake 2. Drought 3. Fire 4. Flood & Cyclones 5. Landslide & Soil Erosion 6. Volcano …..cont. Utility 1. Power 2. Telecom 3. Transport

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