Inland water bodies,including ponds,lakes,reservoirs,and rivers,provide extensive ecosystem services for human beings.Among these,small water bodies(SWBs),such as ponds and small reservoirs,are more common landscape f...Inland water bodies,including ponds,lakes,reservoirs,and rivers,provide extensive ecosystem services for human beings.Among these,small water bodies(SWBs),such as ponds and small reservoirs,are more common landscape features and important biogeochemical reactors.SWBs can significantly influence biogeochemical processes and hydrologic cycles.However,due to their small size,SWBs(<10 ha)have been largely ignored in natural resource surveys,leading to a limited understanding of their spatial distribution in China.Insufficient geospatial datasets of SWBs limit the accurate assessments of resource utilization and fluxes of biogenic elements in both aquatic and terrestrial ecosystems.To address this,in this study,we applied a convolutional neural network and a visual interpretation approach to extract SWBs from high-resolution satellite images from Google Earth.The spatial distribution of SWBs in China was mapped,and drivers of the spatial pattern of SWBs were also identified.As a result,a total of 5.18 million water bodies with a surface area larger than 0.1 ha,including ponds,lakes,and reservoirs,were identified.These water bodies(>0.1 ha)cover approximately 179300 km^(2),which is approximately 1.8%of the land area in China.In addition,the combined shoreline length of the water bodies was approximately 2157400 km.Of these water bodies,96.85%were SWBs,accounting for 17.85%of the total water area and 76.4% of the total shoreline length.Precipitation,terrain,and human activity cumulatively explained 45% of the variance in SWB distribution,with precipitation being the strongest climatic explanatory factor.Our results provide important data for determining the roles of SWBs in biogeochemical cycles,habitat protection,and hydrological cycles.展开更多
基金supported by the Strategic Priority Research Program(A)of the Chinese Academy of 502 Sciences(Grant No.XDA23040303)the National Natural Science Foundation of China(Grant No.42071242)the West Light Foundation of the Chinese Academy of Sciences。
文摘Inland water bodies,including ponds,lakes,reservoirs,and rivers,provide extensive ecosystem services for human beings.Among these,small water bodies(SWBs),such as ponds and small reservoirs,are more common landscape features and important biogeochemical reactors.SWBs can significantly influence biogeochemical processes and hydrologic cycles.However,due to their small size,SWBs(<10 ha)have been largely ignored in natural resource surveys,leading to a limited understanding of their spatial distribution in China.Insufficient geospatial datasets of SWBs limit the accurate assessments of resource utilization and fluxes of biogenic elements in both aquatic and terrestrial ecosystems.To address this,in this study,we applied a convolutional neural network and a visual interpretation approach to extract SWBs from high-resolution satellite images from Google Earth.The spatial distribution of SWBs in China was mapped,and drivers of the spatial pattern of SWBs were also identified.As a result,a total of 5.18 million water bodies with a surface area larger than 0.1 ha,including ponds,lakes,and reservoirs,were identified.These water bodies(>0.1 ha)cover approximately 179300 km^(2),which is approximately 1.8%of the land area in China.In addition,the combined shoreline length of the water bodies was approximately 2157400 km.Of these water bodies,96.85%were SWBs,accounting for 17.85%of the total water area and 76.4% of the total shoreline length.Precipitation,terrain,and human activity cumulatively explained 45% of the variance in SWB distribution,with precipitation being the strongest climatic explanatory factor.Our results provide important data for determining the roles of SWBs in biogeochemical cycles,habitat protection,and hydrological cycles.
