GEDI DATA WITHIN GOOGLE EARTH ENGINE: PRELIMINARY ANALYSIS OF A RESOURCE FOR INLAND SURFACE WATER MONITORING
<p>Freshwater is one the most important renewable water resources of the planet but, due to climate change, surface freshwater available in the form of lakes, rivers, reservoirs, snow, and glaciers is becoming significantly threatened. As a result, surface water level monitoring is fundamental...
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2023-04-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://isprs-archives.copernicus.org/articles/XLVIII-M-1-2023/131/2023/isprs-archives-XLVIII-M-1-2023-131-2023.pdf |
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| author | A. Hamoudzadeh R. Ravanelli M. Crespi M. Crespi |
| author_facet | A. Hamoudzadeh R. Ravanelli M. Crespi M. Crespi |
| author_sort | A. Hamoudzadeh |
| collection | DOAJ |
| description | <p>Freshwater is one the most important renewable water resources of the planet but, due to climate change, surface freshwater available in the form of lakes, rivers, reservoirs, snow, and glaciers is becoming significantly threatened. As a result, surface water level monitoring is fundamental for understanding climatic changes and their impact on humans and biodiversity.</p><p>This study evaluates the accuracy of the Global Ecosystem Dynamics Investigation (GEDI) LiDAR (Light Detection And Ranging) instrument for monitoring inland water levels. Four lakes in northern Italy were selected for comparison with gauge station measurements. To evaluate the accuracy of GEDI altimetric data, two steps of outlier removal are proposed. The first stage employs GEDI metadata to filter out footprints with very low accuracy. Then, a robust version of the standard 3σ test using a 3NMAD (Normalized Median Absolute Deviation) test is iteratively applied.</p><p>After the outlier removal, which led to the elimination of between 80% to 87% of the data, the remaining footprints show an average standard deviation of 0.36 m, a mean NMAD of 0.38 m, and a Root Mean Square Error (RMSE) of 0.44 m, proving the promising potentialities of GEDI L2A altimetric data for inland water monitoring.</p> |
| first_indexed | 2024-04-09T16:50:17Z |
| format | Article |
| id | doaj.art-8009797a21e24c49a806e82b9713309b |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-04-09T16:50:17Z |
| publishDate | 2023-04-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-8009797a21e24c49a806e82b9713309b2023-04-21T14:40:17ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342023-04-01XLVIII-M-1-202313113610.5194/isprs-archives-XLVIII-M-1-2023-131-2023GEDI DATA WITHIN GOOGLE EARTH ENGINE: PRELIMINARY ANALYSIS OF A RESOURCE FOR INLAND SURFACE WATER MONITORINGA. Hamoudzadeh0R. Ravanelli1M. Crespi2M. Crespi3Sapienza University of Rome, DICEA, Geodesy and Geomatics Division, ItalySapienza University of Rome, DICEA, Geodesy and Geomatics Division, ItalySapienza University of Rome, DICEA, Geodesy and Geomatics Division, ItalySapienza School for Advanced Studies, Sapienza University of Rome, Italy<p>Freshwater is one the most important renewable water resources of the planet but, due to climate change, surface freshwater available in the form of lakes, rivers, reservoirs, snow, and glaciers is becoming significantly threatened. As a result, surface water level monitoring is fundamental for understanding climatic changes and their impact on humans and biodiversity.</p><p>This study evaluates the accuracy of the Global Ecosystem Dynamics Investigation (GEDI) LiDAR (Light Detection And Ranging) instrument for monitoring inland water levels. Four lakes in northern Italy were selected for comparison with gauge station measurements. To evaluate the accuracy of GEDI altimetric data, two steps of outlier removal are proposed. The first stage employs GEDI metadata to filter out footprints with very low accuracy. Then, a robust version of the standard 3σ test using a 3NMAD (Normalized Median Absolute Deviation) test is iteratively applied.</p><p>After the outlier removal, which led to the elimination of between 80% to 87% of the data, the remaining footprints show an average standard deviation of 0.36 m, a mean NMAD of 0.38 m, and a Root Mean Square Error (RMSE) of 0.44 m, proving the promising potentialities of GEDI L2A altimetric data for inland water monitoring.</p>https://isprs-archives.copernicus.org/articles/XLVIII-M-1-2023/131/2023/isprs-archives-XLVIII-M-1-2023-131-2023.pdf |
| spellingShingle | A. Hamoudzadeh R. Ravanelli M. Crespi M. Crespi GEDI DATA WITHIN GOOGLE EARTH ENGINE: PRELIMINARY ANALYSIS OF A RESOURCE FOR INLAND SURFACE WATER MONITORING The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | GEDI DATA WITHIN GOOGLE EARTH ENGINE: PRELIMINARY ANALYSIS OF A RESOURCE FOR INLAND SURFACE WATER MONITORING |
| title_full | GEDI DATA WITHIN GOOGLE EARTH ENGINE: PRELIMINARY ANALYSIS OF A RESOURCE FOR INLAND SURFACE WATER MONITORING |
| title_fullStr | GEDI DATA WITHIN GOOGLE EARTH ENGINE: PRELIMINARY ANALYSIS OF A RESOURCE FOR INLAND SURFACE WATER MONITORING |
| title_full_unstemmed | GEDI DATA WITHIN GOOGLE EARTH ENGINE: PRELIMINARY ANALYSIS OF A RESOURCE FOR INLAND SURFACE WATER MONITORING |
| title_short | GEDI DATA WITHIN GOOGLE EARTH ENGINE: PRELIMINARY ANALYSIS OF A RESOURCE FOR INLAND SURFACE WATER MONITORING |
| title_sort | gedi data within google earth engine preliminary analysis of a resource for inland surface water monitoring |
| url | https://isprs-archives.copernicus.org/articles/XLVIII-M-1-2023/131/2023/isprs-archives-XLVIII-M-1-2023-131-2023.pdf |
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