Scattered gis handbook
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The document discusses various concepts related to remote sensing and geographic information systems (GIS). It defines key terms like digital and analog images, spatial and spectral resolution, data models, and data types used in GIS. It also describes common data formats, software, techniques for data input and management, and methods for spatial analysis and map making using GIS.
Scattered gis handbook
- 1. Tracking and Data Relay Satellite System (TDRSS) Analog image Images with continuous gray tone or color like a photograph is called analog image Digital image is the numerical record of the radiance leaving each of the pixel in each of the spectral bands Rayleigh Scattering: dominant scattering mechanism in the upper atmosphere ( 9-10 km), also called clear atmosphere scattering Mie scattering:Occurs when the particles are just about the same size as the wavelength of the radiation (Dust, pollen, smoke and water vapour), occurs in lower atmosphere. (0 – 5 KM) By measuring the energy that is reflected (or emitted) by targets on the Earth's surface over a variety of different wavelengths, we can build up a spectral response for that object, termed a spectral reflectance curve. Specular Reflection: angle of incidence is same as angle of reflection Diffused Reflection: angle of incidence is different from angle of reflection The spatial property defines the dimensions of the corresponding ground area. The spectral property defines the intensity of the spectral response for a pixel in a particular band Spatial resolution refers to the size of the smallest possible feature that can be detected by the sensor. Spectral resolution describes the wavelength intervals in the electromagnetic spectrum that a sensor can record or sense The ability of an imaging system to record many levels of Brightness is Radiometric Resolution. Geography - Pattern and process of human and physical phenomena on the surface of earth. URISA Urban and Regional Information Systems Association DIME Dual Independent Map Encoding TIGER Topologically Integrated Geographic Encoding And Referencing CAD: Computer Assisting Drawing, e.g. AutoCad, Micro station GDS: Graphic Design System, e.g. CorelDraw, Illustrator DBMS: Database Management System, e.g. Oracle, Sybase DIPS: Digital Image Processing System, e.g. PCI, Erdas GPS: Global Positioning Systems, e.g. Garmin, Trimble �Using the tools and helping to build the tools of geographic information systems (GISystems)
- 2. �Studying the theory and concepts that lie behind GIS and other geographic information technologies (GIScience) �Study the societal context of geographic information – legal context, issues of privacy, economics of geographic information (GIStudies) ESRI: Environmental Systems Research Institue Arcinfo uses Arc Macro Language (AML) ArcView uses Visual Basic and Python ArcGIS comes in three different versions based on the capabilities provided by the software: ArcView, ArcEditor and ArcInfo. Gis data types: Feature data Image data Grid data Attribute data A data model is a : Logical Construct for representing real world phenomenon and objects in a computer Coverages and shapefiles are examples of the Georelational Data Model Geodatabases are examples of the Object‐Based Data Model. The Georelational Data Model stores spatial and attribute data separately in a split system Spatial data in ‘graphic files’ Attribute data in ‘relational database files’. The link between the two ‘systems’ is usually a “Feature Label” or ID Object‐based data model stores spatial and attribute data of spatial features in a single system. Spatial data are stored in a field using a data type called “BLOB” (binary large object) Topology is the science and mathematics which defines the spatial or geometrical relationship between spatial features or vector objects in a GIS. Topology is the study of those properties of geometric objects that remain invariant under certain transformations such as bending or stretching. Adjacency and Incidence are two relationships that can be established between nodes and arc in digraphs. If a line joins two points, the points are said to be adjacent and incident with the line. Topological properties:-
- 3. Connectivity, Contiguity/Adjacency, Direction ,Containment Topological data model makes spatial analysis feasible, automatic corrections in plottings, faster processing of larger datasets. But it is expensive and time consuming. Updating topology becomes necessary once spatial data is updated. Complex data form making it difficult for developers to interpret. Spaghetti Data model is the simplest and direct vector representation of a real world object. Easy to produce, display and understand but no spatial analysis possible. TIGER- census data linked to boundary data of counties, block groups etc. ESRI Coverage model:- Point coverage: node ID + coordinates Line coverage: arc IDs + S and E node, arc ID + coordinates. Polygon coverage: arc IDs + L and R polygon, polygon + arc IDs, arc IDs + coordinates DIME:- Arc IDs + S and E node + L and R polygon, Coordinate file for nodes Composite features refer to those spatial features that are better represented as composites of points, lines, and polygons. TINS: Triangulated Irregular Networks Formed by using Delaunay Triangulation which is an iterative process of connecting points with their two nearest neighbors to form triangles. Raster data model:- Storage increases with the square of the resolution. Elements: 1. Cell value. Each cell in a raster carries a value, which represents the characteristic of a spatial phenomenon at the location denoted by its row and column. The cell value can be integer or floating-point. 2. Cell size. The cell size determines the resolution of the raster data model. 3. Raster bands. A raster may have a single band or multiple bands. 4. Spatial reference. Raster data must have the spatial reference information so that they can align spatially with other data sets in a GIS. Attribute data is stored logically in flat files. Cell by cell: row n: 0110 Run length encoding: 23 Quad tree or hierarchical encoding DOQ is a image prepared from an aerial photograph or other remotely sensed data, in which the displacement caused by camera tilt and terrain relief has been removed. DEM is a digital representation of a topographic surface. It is mutli-faceted. Data sources:
- 4. Data capture: Surveys,RS,Digitization Data inputs/ sources: Maps, orthophotos, statistical reports, Satellite Imagery,GPS Input is : - Time consuming - Labour intensive and error prone - Accuracy of GIS analysis rests on accuracy of input data - Expensive Selection of input data: depends on price, availability, spatial analysis required, scale, format, available skills and hardware and software • Federal Geographic Data Committee (FGDC) • Geospatial One‐Stop (GOS) • US Geological Survey (USGS) Metadata describes the characteristics, development and origin of the spatial data. FGDC - Identification Information (Title, geographic data covered) - Data Quality Information (positional, attribute, completeness, sources of information, methods to produce spatial data) - Spatial Data Organization Information (Raster or Vector) - Spatial Reference Information (Datum, Projections, Coord Sys) - Distribution Information (Information about obtaining dataset) - Metadata Reference Information (currency of the metadata and responsible party) Geodesy, is the scientific discipline that deals with the measurement and representation of the earth, its gravitational field, and other geodynamic phenomena, such as crustal motion, oceanic tides, and polar motion. Coordinate systems: PCS (Flat, inches feet metres), GCS( curved , Degrees minutes seconds). 60 N 45 E Conversion of polar to Cartesian:
- 5. Transformation is the projection of a digitized map or image, in some cases from its original coordinate system, onto a new coordinate system. Two main types :- map to map and image to map. 4 methods: Affine( angular distortions but parallelism preserved, similarity shape preserved not size, equiarea (area and shape preserved), projective( angular and shape distortions). Affine transformation allows: skew, rotation, differential scaling and translation Affine used for above mentioned trans. , aerial photos need projective trans. And satellite imagery needs polynomial or warping trans. A geometric transformation typically involves three steps.
- 6. •Step 1 updates the control points to real-world coordinates. •Step 2 uses the control points to run an affine transformation. •Step 3 creates the output by applying the transformation equations to the input features. A quantitative measure of the displacement (the deviation) between the actual (true) and estimated (digitized) locations of the control points is RMS. Resampling in this case means filling each pixel of the new image with a value or a derived value from the original image. – Nearest neighbor: fills each pixel of the new image with the nearest pixel value from the original image – Bilinear interpolation: uses the average of the four nearest pixel values from three linear interpolations – Cubic convolution: uses the average of the 16 nearest pixel values from five cubic polynomial interpolations Map algebra is a language specifically designed for geographic cell‐based systems and provides the basis for cartographic modeling. Uses mathematical expressions to create new grid themes. Arithmetic operators, relational operators, Boolean operators, Functions (trig,log) Raster functions (Output grid generated using input grid as argument): Zonal (cells chosen), local (more than one or one argument), global and focal (cells immediate neighbours only). Uses: Surface generation and analysis (hillshade, viewshed), Data reclassification, Transformations, Distance Analysis (shortest path, cost weighted). Buffer made. Layer of important features created, all queries applied and select by attributes for final results. Statistical local function Overlay functions: union , intersect , identity No data in cell no data in output ( set condition otherwise default value is -9999)
- 7. Raster data model Vector data model Advantages Can store photos Processing of large data sets is easier once topological relations between features are established Simple data structure Prints are aesthetically pleasing Easier Spatial analysis especially overlay (Grid based coincidence) - Can accurately represent continuous phenomena Can accurately represent discrete features Disadvantages Prints appear blocky Cannot store photos Processing of large datasets is time consuming Cannot represent continuous spatial variability accurately Quality and productivity largely depends on resolution Spatial Analysis is time consuming without a developed topology - Complex data structure Photo vs remote Quantitative and qualitative Geometry vs radiometry Visible vs invisible Small area coverage vs large area coverage Uses metadata: Identification of source, techniques of obtaining/ Projection and coordinate systems/ scale/cost/availability Organization of spatial data/ developmental history Data sharing possible Data interpretation techniques
- 8. Uses GIS: Monitoring weather, disaster management, traffic management, urban and regional planning, Crop yields, Effects of different phenomena on environment. Uses Spatial analysis: Identifying developmental patterns, trends , making predictions, modeling, monitoring changes in environments and their effects. Digitizing adva. And disadva.:- Automatic error detection vs error prone Enabling spatial analysis and easier interpretation vs Slow process Transformation possible vs need of digitizing equipment UTM: 84 n to 80 S, 60 zones (6 deg. Each) East –west, Transverse Mercator projection, Alphabet zones 20 north-south. Cartesian system. Clipping, dicing Mosiacing, raster bands AOI, Inquire box, Coordinates Annotations, dynamic labels Graduated color , graduated symbol, dot density, proportional symbol Discrete color, unique color, classified, Natural breaks is the default method. Developed by the cartographer George Jenks, it creates classes according to clusters and gaps in the data. Equal interval creates classes of equal va lue ranges. If the range of values is 1 to 100 and the number of classes is 4, this method will create classes from 1-25,26- 50,51-75, and 76-100. Defined interval resembles equal interval except that the interval determines the number of classes rather than the other way around. If the range of values is 1 (Q 100, and you choose an interval of 10, this method will create 10 classes: 1- 10, 11-20, 21-30, and so on.
- 9. Quantile creates classes containing equal numbers of features. If you choose five classes for a layer with 100 features, this method will create class breaks so that 20 features fall into each class. The value range varies from class to class. Standard deviation creates classes according (Q a specified number of standard deviations from the mean value. Geometric intervals creates classes based on class intervals that have a geometric series. A geometric series is a pattern where a constant coefficient multiplies each value in the series. It produces a result that is visually appealing, cartographically comprehensive, and minimizes variance within classes.