Downscaling MODIS Surface Reflectance to Improve Water Body Extraction
Inland surface water is essential to terrestrial ecosystems and human civilization. Accurate mapping of surface water dynamic is vital for both scientific research and policy-driven applications. MODIS provides twice observation per day, making it perfect for monitoring temporal water dynamic. Altho...
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| Format: | Article |
| Language: | English |
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Wiley
2015-01-01
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| Series: | Advances in Meteorology |
| Online Access: | http://dx.doi.org/10.1155/2015/424291 |
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| author | Xianghong Che Min Feng Hao Jiang Jia Song Bei Jia |
| author_facet | Xianghong Che Min Feng Hao Jiang Jia Song Bei Jia |
| author_sort | Xianghong Che |
| collection | DOAJ |
| description | Inland surface water is essential to terrestrial ecosystems and human civilization. Accurate mapping of surface water dynamic is vital for both scientific research and policy-driven applications. MODIS provides twice observation per day, making it perfect for monitoring temporal water dynamic. Although MODIS provides two bands at 250 m resolution, accurately deriving water area always depends on observations from the spectral bands with 500 m resolution, which limits its discrimination ability over small lakes and rivers. The paper presents an automated method for downscaling the 500 m MODIS surface reflectance (SR) to 250 m to improve the spatial discrimination of water body extraction. The method has been tested at Co Ngoin and Co Bangkog in Qinghai-Tibet plateau. The downscaled SR and the derived water bodies were compared to SR and water body mapped from Landsat-7 ETM+ images were acquired on the same date. Consistency metrics were calculated to measure their agreement and disagreement. The comparisons indicated that the downscaled MODIS SR showed significant improvement over the original 500 m observations when compared with Landsat-7 ETM+ SR, and both commission and omission errors were reduced in the derived 250 m water bodies. |
| format | Article |
| id | doaj-art-db3eae6930de47919a01f6901bb9f5dd |
| institution | Kabale University |
| issn | 1687-9309 1687-9317 |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Meteorology |
| spelling | doaj-art-db3eae6930de47919a01f6901bb9f5dd2025-02-03T05:52:07ZengWileyAdvances in Meteorology1687-93091687-93172015-01-01201510.1155/2015/424291424291Downscaling MODIS Surface Reflectance to Improve Water Body ExtractionXianghong Che0Min Feng1Hao Jiang2Jia Song3Bei Jia4State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaGlobal Land Cover Facility, Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USAState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaCollege of Mining Engineering, Taiyuan University of Technology, Taiyuan 030024, ChinaInland surface water is essential to terrestrial ecosystems and human civilization. Accurate mapping of surface water dynamic is vital for both scientific research and policy-driven applications. MODIS provides twice observation per day, making it perfect for monitoring temporal water dynamic. Although MODIS provides two bands at 250 m resolution, accurately deriving water area always depends on observations from the spectral bands with 500 m resolution, which limits its discrimination ability over small lakes and rivers. The paper presents an automated method for downscaling the 500 m MODIS surface reflectance (SR) to 250 m to improve the spatial discrimination of water body extraction. The method has been tested at Co Ngoin and Co Bangkog in Qinghai-Tibet plateau. The downscaled SR and the derived water bodies were compared to SR and water body mapped from Landsat-7 ETM+ images were acquired on the same date. Consistency metrics were calculated to measure their agreement and disagreement. The comparisons indicated that the downscaled MODIS SR showed significant improvement over the original 500 m observations when compared with Landsat-7 ETM+ SR, and both commission and omission errors were reduced in the derived 250 m water bodies.http://dx.doi.org/10.1155/2015/424291 |
| spellingShingle | Xianghong Che Min Feng Hao Jiang Jia Song Bei Jia Downscaling MODIS Surface Reflectance to Improve Water Body Extraction Advances in Meteorology |
| title | Downscaling MODIS Surface Reflectance to Improve Water Body Extraction |
| title_full | Downscaling MODIS Surface Reflectance to Improve Water Body Extraction |
| title_fullStr | Downscaling MODIS Surface Reflectance to Improve Water Body Extraction |
| title_full_unstemmed | Downscaling MODIS Surface Reflectance to Improve Water Body Extraction |
| title_short | Downscaling MODIS Surface Reflectance to Improve Water Body Extraction |
| title_sort | downscaling modis surface reflectance to improve water body extraction |
| url | http://dx.doi.org/10.1155/2015/424291 |
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