Wetlands Terrain Modeler IAP

Information about Wetlands Terrain Modeler IAP

Published on January 4, 2008

Author: Hannah

Source: authorstream.com

Content

Design and Performance Analysis of Terrain Modeling Framework for Wetlands:  Design and Performance Analysis of Terrain Modeling Framework for Wetlands Project Overview By Emmanuel Alonso, Ricardo Veguilla Overview:  Overview Introduction to Wetlands Project Description Project Status System Design Introduction to Wetlands:  Introduction to Wetlands A geographic area with characteristics of both dry land and bodies of water, occurring in low-lying areas at the edges of water bodies. A wetland is an environment "at the interface between truly terrestrial ecosystems...and truly aquatic systems...making them different from each yet highly dependent on both“ Mitsch & Gosselink, 1986 Wetlands as flood control and mitigation infrastructure.:  Wetlands as flood control and mitigation infrastructure. Wetlands absorb peak flood flows and later release them more slowly, reducing flood damage to property downstream. Wetlands vegetation help reduce the velocity of water currents. Wetlands preservation reduce the need to build dams, embankments and floodgates which are costly and are known to fail. Reason and consequences of wetlands loss::  Reason and consequences of wetlands loss: Reasons: Urban development Agricultural activities Mining Wetland Degradation Natural threats Consequences: Flooding Loss of wildlife habitat Declining water quality Examples:  Examples China’s Yangtze River 1998 Flood: Economic losses were estimated in 32,000 million dollars and 230 million persons were affected. Causes: The increase of settlements construction on flood-prone areas. The increase destruction of wetlands near lakes and river to accommodate more farming. The increase of river basin deforestation. Solutions: Wetland restoration. Stopping deforestation. Harnessing Technology for Wetlands Preservation:  Harnessing Technology for Wetlands Preservation Integrating Remote Sensing and Digital Terrain Modeling we can built a framework for developing more powerful analysis and visualization tools for the study Wetlands. Provide a synoptic view of the spatial-temporal distribution and dynamics of hydrological phenomena using visualization techniques. Digital Terrain Modeling (DTM):  Digital Terrain Modeling (DTM) The study of ground-surface relief and pattern using computer tools. Terrain topology is represented by a square-grid array of terrain heights, known as Digital Elevation Maps (DEMs). Topographic attributes can be computed from DEMs. DTMs are basic data pools for building comparative time series of topochronological change of terrain attributes. General Goals:  General Goals Terrain Modeling Tool Over Cyber-Infrastructure Incorporate Database Digital Elevation Maps Hydro-Ecological Models Signal Processing Algorithms Sensor Arrays Parallel and Distributed Computing Previous Developments:  Previous Developments Prototype Application: Developed in C using OpenGL Support for GNU Autotools for cross-platform development. Terrain image loading tested with a 200x200 Matlab generated input file. Terrain rendered with points or flat polygons. Full virtual camera. Memory manager subsystem for monitoring memory utilization. Preliminary lighting and multi-terrain rendering support. Features :  Features Development in Java using OpenGL Spatial-temporal modeling of terrain data. Database integration. Customizable data flow mechanism. Landmarking Animation scripting and recording. Data reduction, LOD rendering, and data caching. Features Comparison:  Features Comparison All Solutions provide client-side rendering, general data visualization and extensibility. Architecture:  Architecture TerrainView/TerrainModel Interraction:  TerrainView/TerrainModel Interraction 3D Model Data Acquisition Pipeline:  3D Model Data Acquisition Pipeline Five modular layers: Data Source Layer Filesystem, Database Data Conversion Layer DEM, TIN, GeoTIFF Data Downsampling Layer Average, bicubic, subsampling Tessellation Layer Triangles, Polygons, Points Rendering Layer Texture, Color, Composition, Transparency 3D Model Data Acquisition Pipeline - Implementation:  3D Model Data Acquisition Pipeline - Implementation Data Acquisition Pipeline Comments:  Data Acquisition Pipeline Comments Full pipeline required only for off-line use (local files). Pre-computed data could available on database. Each layer can benefit from data caching. Terrain Visualization capabilities:  Terrain Visualization capabilities One TerrainView per window, multiple windows. Multiple TerrainModel per view. Each TerrainModel is rendered by a 3DShader object. Possible TerrainView Combinations:  Possible TerrainView Combinations Terrain Data Visualization Capabilities:  Terrain Data Visualization Capabilities Considerable amount of information already obtainable from DEMs. Exploit 3D data visualization techniques to present terrain attributes and other aggregated data combined with the actual 3D terrain model. Possible Data Visualization Views:  Possible Data Visualization Views Additional Capabilities :  Additional Capabilities Animation: Camera movement recording and playback. Animated TerrainModel Transition Stereoscopic Rendering for Terrain and Data Visualization Concluding comments:  Concluding comments This design represent the foundation for building a terrain monitoring, visualization, and analysis application which unify different computing and information processing resources: Automated data acquisition Distributed storage Distributed processing Rendering References::  References: A statistical approach for the analysis of the relation between low-level performance information, the code and the environment. - Nayda G. Santiago, Diane T. Rover, Domingo Rodriguez - To appear in INFORMATION : An International Journal Terrain Analysis: Principles and Applications, Edited by John P. Wilson and John C. Gallant. ISBN 0-471-32188-5 © 2000 John Wiley & Sons, Inc. High Resolution Digital Terrain Models of Shallow Lake Basins – Toward Modeling Dynamics of Sedimentation for Multithematic Ecosystems Research. – Elmar Csaplovics. D. Frisch, M. Englich & M. Sester, eds, “IAPRS”, Vol 32/4, ISPRS Commisision IV Symposium on GIS - Between Vision and Applications, Stuttgartm, Germany. References::  References: Open Geospatial Consortium http://www.opengeospatial.org/ JOGL Project https://jogl.dev.java.net/ Computer Based Terrain Visualization Techniques http://astronomy.swin.edu.au/~pbourke/modelling/terrainvis/ Data reduction in terrain modeling http://astronomy.swin.edu.au/~pbourke/modelling/terraindata/ Remote Sensing Glossary http://www.casde.unl.edu/vn/glossary/intro.htm Wikipedia – The Free Encyclopedia http://www.wikipedia.org/ Wetland around the World http://www.lethsd.ab.ca/mmh/grade5/wetlands/page3.htm Puerto Rico, Humedales http://pr.water.usgs.gov/public/online_pubs/wsp_2425/ Los Humedales http://cremc.ponce.inter.edu/humedales.htm Natural History – Geography – Maps – Hydrology http://iprac.aspira.org/iprac_histnat.htm Ecosistemas de Puerto Rico http://www.ceducapr.com/ecosistemas.htm National Wetlands Inventory http://wetlandswms.er.usgs.gov/layer_info.html Building Wetlands http://www.epa.gov/region02/water/wetlands/prdf.pdf Questions:  Questions Ricardo Veguilla – [email protected] Emmanuel Alonso – [email protected]

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