Open-source digital elevation model (DEMs) evaluation with gps and lidar data
Advanced Spaceborne Thermal Emission and Reflection Radiometer-Global Digital Elevation Model (ASTER GDEM), Shuttle Radar Topography Mission (SRTM), and Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010) are freely available Digital Elevation Model (DEM) datasets for environmental model...
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International Society for Photogrammetry and Remote Sensing
2016
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my.utm.730452017-11-28T05:01:13Z http://eprints.utm.my/id/eprint/73045/ Open-source digital elevation model (DEMs) evaluation with gps and lidar data Khalid, N. F. Din, A. H. M. Omar, K. M. Khanan, M. F. A. Omar, A. H. Hamid, A. I. A. Pa'Suya, M. F. G70.212-70.215 Geographic information system Advanced Spaceborne Thermal Emission and Reflection Radiometer-Global Digital Elevation Model (ASTER GDEM), Shuttle Radar Topography Mission (SRTM), and Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010) are freely available Digital Elevation Model (DEM) datasets for environmental modeling and studies. The quality of spatial resolution and vertical accuracy of the DEM data source has a great influence particularly on the accuracy specifically for inundation mapping. Most of the coastal inundation risk studies used the publicly available DEM to estimated the coastal inundation and associated damaged especially to human population based on the increment of sea level. In this study, the comparison between ground truth data from Global Positioning System (GPS) observation and DEM is done to evaluate the accuracy of each DEM. The vertical accuracy of SRTM shows better result against ASTER and GMTED10 with an RMSE of 6.054 m. On top of the accuracy, the correlation of DEM is identified with the high determination of coefficient of 0.912 for SRTM. For coastal zone area, DEMs based on airborne light detection and ranging (LiDAR) dataset was used as ground truth data relating to terrain height. In this case, the LiDAR DEM is compared against the new SRTM DEM after applying the scale factor. From the findings, the accuracy of the new DEM model from SRTM can be improved by applying scale factor. The result clearly shows that the value of RMSE exhibit slightly different when it reached 0.503 m. Hence, this new model is the most suitable and meets the accuracy requirement for coastal inundation risk assessment using open source data. The suitability of these datasets for further analysis on coastal management studies is vital to assess the potentially vulnerable areas caused by coastal inundation. International Society for Photogrammetry and Remote Sensing 2016 Conference or Workshop Item PeerReviewed Khalid, N. F. and Din, A. H. M. and Omar, K. M. and Khanan, M. F. A. and Omar, A. H. and Hamid, A. I. A. and Pa'Suya, M. F. (2016) Open-source digital elevation model (DEMs) evaluation with gps and lidar data. In: 2016 International Conference on Geomatic and Geospatial Technology, GGT 2016, 3 October 2016 through 5 October 2016, Kuala Lumpur; Malaysia. https://www.scopus.com/inward/record.uri?eid=2-s2.0-84994026371&doi=10.5194%2fisprs-archives-XLII-4-W1-299-2016&partnerID=40&md5=040b06e0c00b04ea16c94d86b93229f7 |
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G70.212-70.215 Geographic information system Khalid, N. F. Din, A. H. M. Omar, K. M. Khanan, M. F. A. Omar, A. H. Hamid, A. I. A. Pa'Suya, M. F. Open-source digital elevation model (DEMs) evaluation with gps and lidar data |
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Advanced Spaceborne Thermal Emission and Reflection Radiometer-Global Digital Elevation Model (ASTER GDEM), Shuttle Radar Topography Mission (SRTM), and Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010) are freely available Digital Elevation Model (DEM) datasets for environmental modeling and studies. The quality of spatial resolution and vertical accuracy of the DEM data source has a great influence particularly on the accuracy specifically for inundation mapping. Most of the coastal inundation risk studies used the publicly available DEM to estimated the coastal inundation and associated damaged especially to human population based on the increment of sea level. In this study, the comparison between ground truth data from Global Positioning System (GPS) observation and DEM is done to evaluate the accuracy of each DEM. The vertical accuracy of SRTM shows better result against ASTER and GMTED10 with an RMSE of 6.054 m. On top of the accuracy, the correlation of DEM is identified with the high determination of coefficient of 0.912 for SRTM. For coastal zone area, DEMs based on airborne light detection and ranging (LiDAR) dataset was used as ground truth data relating to terrain height. In this case, the LiDAR DEM is compared against the new SRTM DEM after applying the scale factor. From the findings, the accuracy of the new DEM model from SRTM can be improved by applying scale factor. The result clearly shows that the value of RMSE exhibit slightly different when it reached 0.503 m. Hence, this new model is the most suitable and meets the accuracy requirement for coastal inundation risk assessment using open source data. The suitability of these datasets for further analysis on coastal management studies is vital to assess the potentially vulnerable areas caused by coastal inundation. |
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Conference or Workshop Item |
author |
Khalid, N. F. Din, A. H. M. Omar, K. M. Khanan, M. F. A. Omar, A. H. Hamid, A. I. A. Pa'Suya, M. F. |
author_facet |
Khalid, N. F. Din, A. H. M. Omar, K. M. Khanan, M. F. A. Omar, A. H. Hamid, A. I. A. Pa'Suya, M. F. |
author_sort |
Khalid, N. F. |
title |
Open-source digital elevation model (DEMs) evaluation with gps and lidar data |
title_short |
Open-source digital elevation model (DEMs) evaluation with gps and lidar data |
title_full |
Open-source digital elevation model (DEMs) evaluation with gps and lidar data |
title_fullStr |
Open-source digital elevation model (DEMs) evaluation with gps and lidar data |
title_full_unstemmed |
Open-source digital elevation model (DEMs) evaluation with gps and lidar data |
title_sort |
open-source digital elevation model (dems) evaluation with gps and lidar data |
publisher |
International Society for Photogrammetry and Remote Sensing |
publishDate |
2016 |
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http://eprints.utm.my/id/eprint/73045/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-84994026371&doi=10.5194%2fisprs-archives-XLII-4-W1-299-2016&partnerID=40&md5=040b06e0c00b04ea16c94d86b93229f7 |
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1643656560205889536 |
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13.160551 |