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Remote Sensing and GIS MODULE GIS Surface Models and Terrain Subject Geology Paper No and Remote Sensing and GIS Title Module No GIS Surface Models and Terrain Analysis and Title Module Tag RS & GIS XXVI Principal Investigator Co-Principal Investigator Co-Principal Investigator Prof. Talat Ahmad Prof. Devesh K Sinha Prof. P. P. Chakraborty Vice-Chancellor Department of Geology Department of Geology Jamia Millia Islamia University of Delhi University of Delhi Delhi Delhi Delhi Paper Coordinator Content Writer Reviewer Dr. Atiqur Rahman Dr. Manika Gupta Dr. Atiqur Rahman Department of Geography Department of Geology Department of Geography Jamia Millia Islamia University of Delhi Jamia Millia Islamia Delhi Delhi Delhi PAPER: Remote Sensing and GIS GEOLOGY 1 MODULE GIS surface models and terrain analysis Page 1. Learning Outcomes After studying this module you shall be able to: Understand the role of GIS in terrain mapping Learn about computation of terrain variables and approaches to model the terrain learn basic methods to derive the most important parameters of geomorphometry (slope, aspect) 2. Introduction Earth surface or terrain represents a continuous and undulating feature. It is critical to study terrain as it influences the hydrological cycle, which is interlinked with extreme environmental events like floods and drought. In high relief areas, variables such as altitude strongly influence both human and physical environments. The terrain can change the precipitation quantity due to elevation and rain shadow effect, causing the climatic variations among the different geographical regions. The surface water direction is also significantly based on the terrain and terrain study can help in understanding of drainage characteristics. The performance of radar can be affected by the terrain of the region as signal may be blocked by higher terrain. Lastly, human colonization has been critically based on the terrain of the region. The topography is usually analyzed through consideration of elevation, slope and orientation of the physical features. Terrain mapping and analysis has become easier with advent of geographical information systems(GIS). The mapping in GIS allows considering the terrain and a 3D data model is essential to derive information like - altitude, aspect, slope, watershed delineation etc. traditionally surveying was utilized to collect the elevation data, which is extremely PAPER: Remote Sensing and GIS GEOLOGY 2 MODULE GIS surface models and terrain analysis Page expensive and time consuming. With technological enhancements, stereogrammetry techniques and radar data has been successfully applied in collection of elevation data, where in optical data is not utilized. However, in GIS models the elevation data is not treated as third co-ordinate, z with x and y co- ordinates, instead it is either an attribute value for vector data or grid value in raster data. The data in vector format uses a series of irregularly spaced elevation points connected to form triangulated irregular network (TIN) based on Delaunay triangulation, while the raster data considers the topographic surface as equally spaced cells or grids to form a digital elevation model(DEM).Thus, the digital terrain models are actually referred to as 2.5d models, which can be visualized in 3d in GIS. 3. Terrain models 3.1 Digital elevation model (DEM) DEM represents topographic surface or elevation through equally spaced rectangular grid cells, with elevation as the cell value, as given in Fig 1. The grid is created by interpolating elevation data available for known finite points through aerial photographs or radar altimeter. Since spatial information is available in a regular grid, the altitude data stores implicit information, which can extracted through appropriate methods. The data can be utilized to estimate steep slopes, the profile between two points, upstream cells etc. Thus, the data finds its use in hydrological modeling, terrain stability etc. The grid format is the most widely used as it is simple. However, the grid is non-adaptive and density of the grid cannot be adjusted based on increase of complexity of the topographic features. 3.2 Triangulated Irregular Network (TIN) TIN consists of irregularly distributed points forming a vector data. The triangles are built up on these points, where in the corner of each triangle is equal to the elevation of the terrain as given in Fig 1. The edges of the triangles provide PAPER: Remote Sensing and GIS GEOLOGY 3 MODULE GIS surface models and terrain analysis Page information of slope and its direction. This data structure allows for the efficient storage of terrain information as the triangulation allows a variable density and distribution of points. It can be adapted to more complex terrain with higher number data points at high relief terrains and less data points in flat regions of the terrain. Several algorithms allow for selection of significant points like the maximum-z tolerance algorithm. This algorithm allows selection of points based on elevation difference between two successive points. So the only points that are selected are above the threshold value, z given. A TIN can be created from a set of points (x,y,z) or isolines and also from the DEM. The TIN compared to DEM can include features such as peaks, slope breaks and conic pits, and may give a more accurate structure for terrain. However, TIN can have distortions at the edges due to sudden drop of elevations and is more complicated to implement than to implement algorithms based on raster data. PAPER: Remote Sensing and GIS GEOLOGY 4 MODULE GIS surface models and terrain analysis Page Fig 1. Illustration of DEM and TIN Other than DEM and TIN, a digital surface model (DSM) can also be utilized to represent the terrain. This model includes features above the ground, such as buildings and vegetation, and is used to distinguish a bare-earth elevation model. That is the difference in DEM and DSM would provide the height of the feature like the forest canopy or building. Both the gridded as well as the vector format are known as DSM. 4. Terrain mapping 4.1 Contours from DEM and vertical profiling Contours are the isolines of elevation that reflect topography. These lines do not intersect. Usually contours are available from the survey maps. However, with the PAPER: Remote Sensing and GIS GEOLOGY 5 MODULE GIS surface models and terrain analysis Page advent of GIS software, contours can be automatically obtained from the available DEM or TIN data. The contours are closely spaced in steep slopes and are curved in upstream direction along a stream. On the other hand, we can have vertical profiling, which shows changes in elevation along a line. For example, a slope gradient along a road or stream can be estimated from the elevation data available from the DEM or TIN. 4.3 Hill shading Hill shading is also known as the shaded relief, which helps in visualization of the terrain with the interaction of sunlight with surface features. Thus, hill shading ability of GIS software, helps in computation of the relative radiance of each raster cell based on the sun's azimuth, direction of incoming light, sun' s altitude, angle of incoming light, surface slope and surface aspect. The surface slope and aspect derivation is considered in next section. Thus, the equation for calculating relative radiance value of raster cell is- R f cos(Af As )sin(H f )cos(H s ) sin(H s )cos(H f ) where, Af is aspect of surface, As is sun azimuth, Hf is the slope and Hs is the sun altitude. 4.4 Hypsometric tinting and perspective viewing Helps in visualizing the progression in elevation and the perspective viewing based on the distance, angle, elevation difference provide a 3-d visualization of the terrain. The 3d viewing thus help in visualization of high and low terrain. 5. DEM for terrain analysis The following section provides the various information that can be extracted from the DEM and applied for various applications. PAPER: Remote Sensing and GIS GEOLOGY 6 MODULE GIS surface models and terrain analysis Page 5.1 Slope and aspect Slope measures the rate of change in elevation at the surface either as percentage or degree while aspect provides the directional orientation of the slope. Slope and aspect are important information for hydrological applications and morphometric studies. So, slope as percent is defined as 100 times of rise divided by run or can be represented for Fig 2 as Slope in percent =(A/B)*100 or slope in degrees= tan- 1(A/B). Fig. 2 Illustration of calculating slope Now, for the raster slope needs to be calculated in both the x-and y-direction and is expressed using the finite difference approach as the first derivative of the elevation in that direction. Therefore, the slope in both the directions separately can be expressed as h S x x x h S y y x Thus, the total slope is 2 2 hx hy S x y Now, if we consider an example raster, Fig 3, with pixel values being h1...h9. PAPER: Remote Sensing and GIS GEOLOGY 7 MODULE GIS surface models and terrain analysis Page Fig 3. Raster example for calculating slope 2 2 h1 h5 h h The slope at center pixel, S 3 7 2a 2a Other than slope, aspect is based on directional angle and can be calculated for the Fig 3. as A= arctan((h3-h7)/(h1-h5)) and is calculated in radians (1Radian=57.296 degrees). Aspect gives the direction of slope at the raster pixel being considered. The aspect varies between 0 to 360 degrees, with 0 degree representing the North. Aspect is manipulated to representative of the four directions( N,S, E and W) or eight directions (N, S, E, W, NE, SE, SW and NW). Thus, once the directional angle is obtained, it is converted to direction as follows - If slope in x-direction is zero, then if slope in y-direction is less than zero, aspect is 180 else 360.
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