Identifying and monitoring the spatiotemporal patterns of potentially contaminated land(PCL) in China is a key concern of ecological governance. However, the dynamics of PCL’s expansion remain unclear nationwide. Int...Identifying and monitoring the spatiotemporal patterns of potentially contaminated land(PCL) in China is a key concern of ecological governance. However, the dynamics of PCL’s expansion remain unclear nationwide. Integrating high-resolution remote sensing images, a land-use/cover change database, crawler data from websites, and other multisource data, we produced a new dataset of China’s PCL in 1990, 2000, 2010, and 2020 using data fusion technology. Then we analyzed the spatiotemporal patterns of China’s PCL from 1990 to 2020. Our study shows that the acquired vector dataset of China’s PCL is of high quality and reliability, with an overall accuracy of 93.21%. The area of China’s PCL has kept growing for the past 30 years, and the growth rate was especially rapid during2000–2010, 2.32 and 6.13 times as rapid as that during 1990–2000 and 2010–2020, respectively. PCL has also been trending toward higher aggregation over markedly enlarged areas and has transferred progressively from north and southeast of China to northwest and southwest of China and Qinghai-Tibet Plateau. The patterns of China’s PCL have been driven by the joint factors of policies, mineral resources, economy, and others, among which policies and the economy have contributed more prominently to the long-term transition.Our study promotes the access to high-quality spatial data of PCL to facilitate environmental governance of mine wastes, pollution and land management.展开更多
High-resolution mapping and monitoring of national land use/cover changes contribute significantly to the knowledge of the interaction between human activities and environmental changes.China’s Land Use/cover Dataset...High-resolution mapping and monitoring of national land use/cover changes contribute significantly to the knowledge of the interaction between human activities and environmental changes.China’s Land Use/cover Dataset(CLUD)for 2020 and its dynamic changes in 2015-2020 were developed to extend the CLUD to over 30 years(i.e.,the 1980s to 2020 at 5-year intervals)by integrating remote sensing big data and knowledge-based human-computer interaction interpretation methods.This integrating method for CLUD 2020 improved the efficiency of national land use/cover mapping and the accuracy of land use pattern change detection compared to earlier CLUD products,with an overall accuracy of 95%.The intensity of land use change decreased across China in 2015-2020 compared to 2010-2015,although both characteristics of its spatial changes were similar.The cropland area continued to shrink at national scale in 2015-2020,with two regional hotspots including the widespread conversions from dry land into paddy land in Northeast China and the coexistence of widespread land cultivation and cropland abandonment in Xinjiang of Northwest China.Built-up land area continued to expand in China,showing consistency between 2015-2020 and 2010-2015,in which hotspots transited from the surroundings of coastal megacities to the city surroundings of the central and western zones.For natural land,although the woodland and grassland decreased in 2015-2020,its magnitude expanded compared to 2010-2015.In comparison,the water body area in Qinghai-Tibet Plateau increased significantly under the continuous impact of climate change.These characteristics of land use change were closely related to the development strategy of the top-level design of the 13th Five-Year Plan(2016-2020)(e.g.,ecological civilization construction and high-quality development).展开更多
基金Under the auspices of the National Key Research and Development Program (No. 2018YFC1800103, 2018YFC1800106)。
文摘Identifying and monitoring the spatiotemporal patterns of potentially contaminated land(PCL) in China is a key concern of ecological governance. However, the dynamics of PCL’s expansion remain unclear nationwide. Integrating high-resolution remote sensing images, a land-use/cover change database, crawler data from websites, and other multisource data, we produced a new dataset of China’s PCL in 1990, 2000, 2010, and 2020 using data fusion technology. Then we analyzed the spatiotemporal patterns of China’s PCL from 1990 to 2020. Our study shows that the acquired vector dataset of China’s PCL is of high quality and reliability, with an overall accuracy of 93.21%. The area of China’s PCL has kept growing for the past 30 years, and the growth rate was especially rapid during2000–2010, 2.32 and 6.13 times as rapid as that during 1990–2000 and 2010–2020, respectively. PCL has also been trending toward higher aggregation over markedly enlarged areas and has transferred progressively from north and southeast of China to northwest and southwest of China and Qinghai-Tibet Plateau. The patterns of China’s PCL have been driven by the joint factors of policies, mineral resources, economy, and others, among which policies and the economy have contributed more prominently to the long-term transition.Our study promotes the access to high-quality spatial data of PCL to facilitate environmental governance of mine wastes, pollution and land management.
基金The Strategic Priority Research Program of the Chinese Academy of Sciences,No.XDA23100201National Key R&D Program of China,No.2018YFC1800103The Second Tibetan Plateau Scientific Expedition and Research Program,No.2019QZKK0608。
文摘High-resolution mapping and monitoring of national land use/cover changes contribute significantly to the knowledge of the interaction between human activities and environmental changes.China’s Land Use/cover Dataset(CLUD)for 2020 and its dynamic changes in 2015-2020 were developed to extend the CLUD to over 30 years(i.e.,the 1980s to 2020 at 5-year intervals)by integrating remote sensing big data and knowledge-based human-computer interaction interpretation methods.This integrating method for CLUD 2020 improved the efficiency of national land use/cover mapping and the accuracy of land use pattern change detection compared to earlier CLUD products,with an overall accuracy of 95%.The intensity of land use change decreased across China in 2015-2020 compared to 2010-2015,although both characteristics of its spatial changes were similar.The cropland area continued to shrink at national scale in 2015-2020,with two regional hotspots including the widespread conversions from dry land into paddy land in Northeast China and the coexistence of widespread land cultivation and cropland abandonment in Xinjiang of Northwest China.Built-up land area continued to expand in China,showing consistency between 2015-2020 and 2010-2015,in which hotspots transited from the surroundings of coastal megacities to the city surroundings of the central and western zones.For natural land,although the woodland and grassland decreased in 2015-2020,its magnitude expanded compared to 2010-2015.In comparison,the water body area in Qinghai-Tibet Plateau increased significantly under the continuous impact of climate change.These characteristics of land use change were closely related to the development strategy of the top-level design of the 13th Five-Year Plan(2016-2020)(e.g.,ecological civilization construction and high-quality development).
