Remote-Sensing Extraction of Small Water Bodies on the Loess Plateau
The mixed pixel of low-resolution remote-sensing image makes the traditional water extraction method not effective for small water body extraction. This study takes the Loess Plateau with complex terrain as the research area and develops a multi-index fusion threshold segmentation algorithm (MFTSA)...
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| Veröffentlicht in: | Water (Basel) Jg. 15; H. 5; S. 866 |
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MDPI AG
01.03.2023
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| ISSN: | 2073-4441, 2073-4441 |
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| Abstract | The mixed pixel of low-resolution remote-sensing image makes the traditional water extraction method not effective for small water body extraction. This study takes the Loess Plateau with complex terrain as the research area and develops a multi-index fusion threshold segmentation algorithm (MFTSA) for a large-scale small water body extraction algorithm based on GEE (Google Earth Engine). MFTSA uses the AWEI (automated water extraction index), MNDWI (modified normalized difference water index), NDVI (normalized difference vegetation index) and EVI (enhanced vegetation index) for multi-index synergy to extract small water bodies. It also uses slope data generated by the SRTM (Shuttle Radar Topography Mission digital elevation model) and NIR band reflectance to eliminate suppressing high reflectivity noise and shadow noise. An MFTSA algorithm was proposed and the results showed that: (1) The overall extraction accuracy of the MFTSA algorithm on the Loess Plateau was 98.14%, and the correct extraction rate of small water bodies was 92.82%. (2) Compared with traditional water index methods and classification methods, the MFTSA algorithm could extract small water bodies with higher integrity and clearer and more accurate boundaries. (3) The MFTSA algorithm was used to extract a total of 69,900 small water bodies on the Loess Plateau, accounting for 97.63% of the total water bodies, and the area was 482.11 square kilometers, accounting for 16.50% of the total water bodies. |
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| AbstractList | The mixed pixel of low-resolution remote-sensing image makes the traditional water extraction method not effective for small water body extraction. This study takes the Loess Plateau with complex terrain as the research area and develops a multi-index fusion threshold segmentation algorithm (MFTSA) for a large-scale small water body extraction algorithm based on GEE (Google Earth Engine). MFTSA uses the AWEI (automated water extraction index), MNDWI (modified normalized difference water index), NDVI (normalized difference vegetation index) and EVI (enhanced vegetation index) for multi-index synergy to extract small water bodies. It also uses slope data generated by the SRTM (Shuttle Radar Topography Mission digital elevation model) and NIR band reflectance to eliminate suppressing high reflectivity noise and shadow noise. An MFTSA algorithm was proposed and the results showed that: (1) The overall extraction accuracy of the MFTSA algorithm on the Loess Plateau was 98.14%, and the correct extraction rate of small water bodies was 92.82%. (2) Compared with traditional water index methods and classification methods, the MFTSA algorithm could extract small water bodies with higher integrity and clearer and more accurate boundaries. (3) The MFTSA algorithm was used to extract a total of 69,900 small water bodies on the Loess Plateau, accounting for 97.63% of the total water bodies, and the area was 482.11 square kilometers, accounting for 16.50% of the total water bodies. |
| Audience | Academic |
| Author | Liu, Bin Wang, Chenfeng Liu, Ke Guo, Jia Wang, Xiaoping Zhang, Yong |
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| Cites_doi | 10.3390/rs12152413 10.5194/essd-13-3907-2021 10.1021/acs.est.8b07270 10.1080/01431169608948714 10.1007/s11269-005-3281-5 10.3390/rs5073212 10.1016/j.rse.2015.12.055 10.1029/2005RG000183 10.14358/PERS.75.11.1307 10.3390/rs12091374 10.1016/j.isprsjprs.2022.03.013 10.1007/s10750-016-3007-0 10.1080/01431160600589179 10.1016/j.rse.2013.08.029 10.3390/rs6065067 10.1007/BF00994018 10.1109/TSMC.1979.4310076 10.1016/j.rse.2015.01.004 10.1023/A:1010933404324 10.3390/rs13040787 10.1016/S0034-4257(02)00096-2 10.1073/pnas.1719275115 10.3390/w10050585 10.3390/rs11192213 10.1016/j.isprsjprs.2016.01.011 10.1016/j.jtusci.2016.04.005 |
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| References | McFeeters (ref_13) 1996; 17 Belgiu (ref_22) 2016; 114 Ji (ref_4) 2009; 75 Corcoran (ref_23) 2013; 5 Zou (ref_26) 2018; 115 ref_12 ref_19 ref_18 Dong (ref_17) 2015; 160 Farr (ref_11) 2007; 45 Feyisa (ref_15) 2014; 140 Otsu (ref_16) 1979; 9 Yang (ref_10) 2021; 13 Li (ref_28) 2022; 187 Jiang (ref_3) 2014; 6 Cortes (ref_25) 1995; 20 ref_24 Golden (ref_2) 2019; 53 Huete (ref_7) 2002; 83 Xu (ref_14) 2006; 27 Fisher (ref_6) 2016; 175 ref_27 ref_9 ref_8 Jain (ref_5) 2005; 19 Breiman (ref_21) 2001; 45 Biggs (ref_1) 2017; 793 Sarp (ref_20) 2017; 11 |
| References_xml | – ident: ref_12 doi: 10.3390/rs12152413 – volume: 13 start-page: 3907 year: 2021 ident: ref_10 article-title: The 30 m annual land cover dataset and its dynamics in China from 1990 to 2019 publication-title: Earth Syst. Sci. Data doi: 10.5194/essd-13-3907-2021 – volume: 53 start-page: 7203 year: 2019 ident: ref_2 article-title: Non-floodplain wetlands affect watershed nutrient dynamics: A critical review publication-title: Environ. Sci. Technol. doi: 10.1021/acs.est.8b07270 – volume: 17 start-page: 1425 year: 1996 ident: ref_13 article-title: The use of the normalized difference water index (NDWI) in the delineation of open water features publication-title: Inter. J. Remote Sens. doi: 10.1080/01431169608948714 – volume: 19 start-page: 333 year: 2005 ident: ref_5 article-title: Delineation of flood-prone areas using remote sensing techniques publication-title: Water Resour. Manag. doi: 10.1007/s11269-005-3281-5 – volume: 5 start-page: 3212 year: 2013 ident: ref_23 article-title: Influence of multi-source and multi-temporal remotely sensed and ancillary data on the accuracy of random forest classification of Wetlands in Northern Minnesota publication-title: Remote Sens. doi: 10.3390/rs5073212 – ident: ref_18 – volume: 175 start-page: 167 year: 2016 ident: ref_6 article-title: Comparing Landsat water index methods for automated water classification in eastern Australia publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2015.12.055 – volume: 45 start-page: RG2004 year: 2007 ident: ref_11 article-title: The shuttle radar topography mission publication-title: Rev. Geophys. doi: 10.1029/2005RG000183 – volume: 75 start-page: 1307 year: 2009 ident: ref_4 article-title: Analysis of dynamic thresholds for the normalized difference water index publication-title: Photogramm. Eng. Remote Sens. doi: 10.14358/PERS.75.11.1307 – ident: ref_9 doi: 10.3390/rs12091374 – volume: 187 start-page: 306 year: 2022 ident: ref_28 article-title: Water body classification from high-resolution optical remote sensing imagery: Achievements and perspectives publication-title: ISPRS J. Photogramm. Remote Sens. doi: 10.1016/j.isprsjprs.2022.03.013 – volume: 793 start-page: 3 year: 2017 ident: ref_1 article-title: The importance of small waterbodies for biodiversity and ecosystem services: Implications for policy makers publication-title: Hydrobiology doi: 10.1007/s10750-016-3007-0 – volume: 27 start-page: 3025 year: 2006 ident: ref_14 article-title: Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery publication-title: Inter. J. Remote Sens. doi: 10.1080/01431160600589179 – ident: ref_8 – volume: 140 start-page: 23 year: 2014 ident: ref_15 article-title: Automated water extraction index: A new technique for surface water mapping using Landsat imagery publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2013.08.029 – volume: 6 start-page: 5067 year: 2014 ident: ref_3 article-title: An automated method for Extracting Rivers and Lakes from Landsat Imagery publication-title: Remote Sens. doi: 10.3390/rs6065067 – volume: 20 start-page: 273 year: 1995 ident: ref_25 article-title: Support-vector networks publication-title: Mach. Learn. doi: 10.1007/BF00994018 – volume: 9 start-page: 62 year: 1979 ident: ref_16 article-title: A threshold selection method from gray-level histograms publication-title: IEEE Trans. Syst. Man Cybern. doi: 10.1109/TSMC.1979.4310076 – volume: 160 start-page: 99 year: 2015 ident: ref_17 article-title: Tracking the dynamics of paddy rice planting area in 1986-2010 through time series Landsat images and phenology-based algorithms publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2015.01.004 – volume: 45 start-page: 5 year: 2001 ident: ref_21 article-title: Random forests publication-title: Mach. Learn. doi: 10.1023/A:1010933404324 – ident: ref_24 doi: 10.3390/rs13040787 – volume: 83 start-page: 195 year: 2002 ident: ref_7 article-title: Overview of the radiometric and biophysical performance of the MODIS vegetation indices publication-title: Remote Sens. Environ. doi: 10.1016/S0034-4257(02)00096-2 – volume: 115 start-page: 3810 year: 2018 ident: ref_26 article-title: Divergent trends of open-surface water body area in the contiguous United States from 1984 to 2016 publication-title: Proc. Natl. Acad. Sci. USA doi: 10.1073/pnas.1719275115 – ident: ref_27 doi: 10.3390/w10050585 – ident: ref_19 doi: 10.3390/rs11192213 – volume: 114 start-page: 24 year: 2016 ident: ref_22 article-title: Random forest in remote sensing: A review of applications and future directions publication-title: ISPRS J. Photogram. Remote Sens. doi: 10.1016/j.isprsjprs.2016.01.011 – volume: 11 start-page: 381 year: 2017 ident: ref_20 article-title: Water body extraction and change detection using time series: A case study of Lake Burdur, Turkey publication-title: J. Taibah Univ. Sci. doi: 10.1016/j.jtusci.2016.04.005 |
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| SubjectTerms | Accuracy Algorithms Classification Datasets Loess Remote sensing Research methodology Rivers Topography Vegetation Water |
| Title | Remote-Sensing Extraction of Small Water Bodies on the Loess Plateau |
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