Dynamic Creation of Bump Images and Profile Generation from DEM Gaurav Dongre 1 Ms. Pratibha M. Umale 2

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1 International Journal for Research in Technological Studies Vol. 1, Issue 6, May 2014 ISSN (online): Dynamic Creation of Bump Images and Profile Generation from DEM Gaurav Dongre 1 Ms. Pratibha M. Umale 2 1 M.Tech Scholar 2 Lecturer 1, 2 School of Electronics, 1, 2 Devi Ahilya Vishwavidyalaya (DAVV), Indore, Madhya Pradesh Abstract The report discusses in detail the learnings at different departments of the spatial and geo-spatial technologies for the planning and developmental activities pertaining to Agriculture, Land and Water Resource Management, Wasteland/Watershed Development, Forestry, Disaster Management, Infrastructure and Education. Later part of the report discusses in brief the project DYNAMIC CREATION OF BUMP IMAGES AND PROFILE NERATION FROM DEM. DEM Profile Generator is a utility to facilitate the use of spatial and geo-spatial technologies. It generates graphs of the height-intensity as per the pixel values as well as a map of instrumentally derived seismic intensities. These maps provide an elevation of the extent of damage following an earthquake. They can be used for emergency response, loss estimation, and for public information through the media. For example, maps of shaking intensity can be combined with databases of inventories of buildings and lifelines to rapidly produce maps of estimated damage. Keywords: -Indian Remote Sensing Satellite (IRS), Cartosat, LISS-IV Data, Digital Elevation Model (DEM), Geographic Information system (GIS), AWIFS, satellite Data. I. INTRODUCTION A digital elevation model is a digital model or 3D representation of a terrain's surface commonly for a planet (including Earth), moon, or asteroid created from terrain elevation data.there is no common usage of the terms digital elevation model (DEM), digital terrain model (DTM) and digital surface model (DSM) in scientific literature. In most cases the term digital surface model represents the earth's surface and includes all objects on it. In contrast to a DSM, the digital terrain model represents the bare ground surface without any objects like plants and buildings. A DEM can be represented as a raster (a grid of squares, also known as a height map when representing elevation) or as a vector-based triangular irregular network (TIN). The TIN DEM dataset is also referred to as a primary (measured) DEM, whereas the Raster DEM is referred to as a secondary (computed) DEM. The DEM could be acquired through techniques such as photogrammetry, LiDAR, IfSAR, land surveying, etc. (as per 2005). DEMs are commonly built using data collected using remote sensing techniques, but they may also be built from land surveying. DEMs are used often in geographic information systems, and are the most common basis for digitally-produced relief maps. The quality of a DEM is a measure of how accurate elevation is at each pixel (absolute accuracy) and how accurately is the morphology presented (relative accuracy). Several factors play an important role for quality of DEMderived products: Terrain roughness Sampling density (elevation data collection method) Grid resolution or pixel size Interpolation algorithm Vertical resolution Terrain analysis algorithm II. METHODS FOR OBTAINING ELEVATION DATA USED TO CREATE DEMS INVENTORY MANAGEMENT LIDAR Stereo photogrammetry from aerial surveys Block adjustment from optical satellite imagery Interferometry from radar data Real Time Kinematic GPS Topographic maps Focus variation Inertial surveys Surveying and mapping drones III. IMAGE FILES USED WITH THEIR SPECIFICATIONS TIFF has emerged as one of the world's most popular raster file formats. But TIFF remains limited in cartographic applications, since no publicly available, stable structure for conveying geographic information presently exists in the public domain. GeoTIFF is a public domain metadata standard. The potential additional information includes map projection, coordinate systems, ellipsoids, datum, and everything else necessary to establish the exact spatial reference for the file. GeoTIFF uses a small set of reserved TIFF tags to store a broad range of geo - referencing information, catering to geographic as well as projected coordinate system s needs. GeoTIFF uses a "Meta Tag" (Geo Key) approach to encode dozens of information elements into just 6 tags, taking advantage of TIFF platform-independent data format representation to avoid cross-platform interchange difficulties. Fig.1: Sample GeoTIFF Image (Dimensions-3447x3178 Px) Copyright IJRTS 105

2 IV. PROFILE GENERATOR BACKGROUND AND WORKING The Profile Generator is a utility for working with maps and geographic information. It is used for using maps, compiling geographic data; analyzing mapped information; sharing and discovering geographic information, using the geo-spatial data in a range of applications; and managing geographic information in a database. Our project mainly deals with Elevation Plotting and creating ShakeMaps with given Magnitude, Epicenter and Depth of a possible earthquake. reflection of light on any given surface. Using the light source and intensity values of every pixel of the image, a 3D model is generated. Fig.2 : Snapshot of the main Window of Application The graph plotting feature takes the intensity along the user plotted line, and plots a graph with intensity (which is actually the height of the point above sea level) from the raster data of original image along Y-axis and the length of the virtual line along the X-axis. Fig.4: Elevation produced by a single Light Source on a GeoTIFF image Thus the BUMP MAP so created is used as the source image for Shake Mapping. Fig.3 : Graph Plotting Utility The ShakeMap feature extensively uses vector 3D (field of mathematics) and some basic principles of Fig.5 : 3D Bump Map created with light source at bottom right corner A properly selected band of colors is then used to color the 3d bump map to distinctly identify the regions of high elevation and the dips in the nearby terrain. Copyright IJRTS 106

3 Fig.6 : Orange-Red colors represent heights and vice-versa With the given magnitude, epicenter and depth of the earthquake, each pixel of the bump map is colored according to the color mapping defined by standards. Equation used for calculating instrumental instensity for India is Intensity = (( (1.06 * Mag)) + ((( ) * Rad) + ((- 3.37) * Log 10 (Rad)))) Mag = magnitude of earthquake Rad = distance from [ (Lat, Lang) origin of earthquake ] Fig. 8: Color interpolation technique is used to assign perfect color to every pixel to give gradual change from high intensity to lower ones. Fig.7 : Color Pallet for ShakeMaps Intensity Scale ShakeMap is thus generated with a given Magnitude (in Richter scale), Epicenter (Latitude, Longitude), and Depth of Origin of earthquake. The distinct rings clearly depict the region affected by earthquake as per the instrumental-intensity. Fig.9: A 300 x 300 Kms of area of ShakeMap (Location - Madhya Pradesh) All the GeoTIFF images of complete India are then positioned in a 2D array with their latitude and longitudes stored in objects. Copyright IJRTS 107

4 Fig.10: Snapshot of the 2D array.9999 Blank Tiles The Number represent the Tile Index. After enumerating all the tiles of India, the application asks for the details of the Earthquake. Manual Mode allows you enter them manually. Automatic Mode read a text file named InputParameters.txt. Fig.9 : Image showing Area affected With the epicenter, magnitude and depth of earthquake, the individual tiles are generated in the user defined directory, with the same file name and a JGW file containing latitude and longitude of upper left corner of each tile. Fig.8 : Scaling Level Ratio of output to Original Dimensions. After Reading the Details of Earthquake (Magnitude, Epicenter, Depth) only some tiles are selected to be processed with given specifications: Fig. 11: Sample Images of areas affected Copyright IJRTS 108

5 V. FUTURE PROSPECTS The current standalone application supports a GeoTIFF file for Profile Generation task and with the application of technologies like Parallel Computing and Distributed Computing; it can be made to handle a larger number of files. With the data available from databases containing population density and settlement orientation, this application can used to estimate losses and carry out evacuation plans. Remotely Sensed Data And Geographical Information Systems. Asian Conference On Remote Sensing Taipei, Taiwan, [12] Ludwig, R. And P. Schneider (2006). Validation Of Digital Elevation Models From SRTM X-SAR For Applications In Hydrologic Modeling. ISPRS Journal Of Photogrammetry And Remote Sensing 60(5): ACKNOWLEDGMENTS Gaurav Dongre and Rakesh Aditya would like to express our gratitude to all those who gave the possibility to complete this research work. I would like to thank Dr. Raj Kamal, Dr. Abhay Kumar,Head, and School of Electronics, Dr. Sumant Katiyal, Senior Professors of School of Electronics, Devi Ahilya University, Indore (M.P) and Mrs. Pratibha M. Umale (Class Coordinator of SIT) for giving me an opportunity to work in such a prestigious Institute like BISAG. I am grateful to all our faculty members of School of Electronics Department for their suggestions and constant encouragement. Last but not least, I would like to pay high regards to my Parents, Family Members, and all Friends for their sincere encouragement and inspiration throughout my research work. REFERENCES [1] Raja Mani V (2005). Digital Elevation Assessment: Is It A Solution The Hindu, 26th August [2] Majunu S And Sumanth Kumar G (2006). Gis Building Development Using Geographic Information System: Ecologists Wake Up! Curr. Sci., 87(8): [3] Jacobsen,K. Bump Image Generation From Satellite Data.Germany. [4] En.Cartosat Study.KETCHUM, B. H The Land Edge: Critical Problems Of The Coastal Zone. In: Coastal Zone Workshop, [5] Rajiv K. Gupta (2004). Land Governance In Madhya Pradesh State, India, International Journal Of Land Resources Development, 20(2): [6] Van Deursen, W.P.A. &Kwadijk, J.C.J (1993) RHINEFLOW: An Integrated GIS. In: Application Of Geographic Information Systems In Hydrology And Land Resources (Ed, By K. Kovar&H. P. Snachtnebel) (Proc, Int. Conf. LAND-GIS 93, Vienna, April 1993), IAHS Publ. No [7] Alumini Association, CEG Anna University, Proceedings Of The Seminar On Integrated Coastal Zone Management System, February, [8] Baban, S. (1999). Use Of Remote Sensing And Geographical Information Systems In Developing Land Management Strategies. Land (0): [9] Dasmunsi, P. R. (2005). Digital Elevation Model. International Journal Of Environmental Consumerism 1 (1): [10] Wu, S., J. Li, Et Al. (2007). Characterization And Resources Modeling With LISS-III Imagess. Environmental Resources Management. [11] Yusuf, K. W. And S. M. J. Baban (2000). Identifying Optimum Sites For Locating Industries Employing Copyright IJRTS 109