Articles | Volume 13, issue 1
https://doi.org/10.5194/essd-13-63-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-13-63-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A 30 m resolution dataset of China's urban impervious surface area and green space, 2000–2018
Wenhui Kuang
CORRESPONDING AUTHOR
Key Laboratory of Land Surface Pattern and Simulation, Institute of
Geographic Sciences and Natural Resources Research, Chinese Academy of
Sciences, Beijing 100101, China
Shu Zhang
Key Laboratory of Land Surface Pattern and Simulation, Institute of
Geographic Sciences and Natural Resources Research, Chinese Academy of
Sciences, Beijing 100101, China
College of Resources and Environment, University of Chinese Academy of
Sciences, Beijing 10049, China
Xiaoyong Li
College of Resources and Environment, University of Chinese Academy of
Sciences, Beijing 10049, China
State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
Dengsheng Lu
School of Geographical Sciences, Fujian Normal University, Fuzhou
350007, China
Fujian Provincial Key Laboratory of Subtropical Resources and
Environment, Fujian Normal University, Fuzhou 350007, China
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Binyuan Xu, Hanqin Tian, Shufen Pan, Xiaoyong Li, Ran Meng, Óscar Melo, Anne McDonald, María de los Ángeles Picone, Xiao-Peng Song, Edson Severnini, Katharine G. Young, and Feng Zhao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-527, https://doi.org/10.5194/essd-2024-527, 2025
Revised manuscript accepted for ESSD
Short summary
Short summary
This study focuses on land use change in South America, reconstructing the historical dynamics of four major crops (soybean, maize, wheat, and rice) from 1950 to 2020 by integrating multiple data sources. The results reveal a significant expansion in cropland, particularly for soybean, leading to a substantial reduction in natural vegetation such as forests and grasslands. The datasets can be used to assess the impacts of cropland expansion on carbon and nitrogen cycles in South America.
Xiaoyong Li, Hanqin Tian, Chaoqun Lu, and Shufen Pan
Earth Syst. Sci. Data, 15, 1005–1035, https://doi.org/10.5194/essd-15-1005-2023, https://doi.org/10.5194/essd-15-1005-2023, 2023
Short summary
Short summary
We reconstructed land use and land cover (LULC) history for the conterminous United States during 1630–2020 by integrating multi-source data. The results show the widespread expansion of cropland and urban land and the shrinking of natural vegetation in the past four centuries. Forest planting and regeneration accelerated forest recovery since the 1920s. The datasets can be used to assess the LULC impacts on the ecosystem's carbon, nitrogen, and water cycles.
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Environ., 219, 206–220, https://doi.org/10.1016/j.rse.2018.10.015, 2018.
Short summary
We propose a hierarchical principle for remotely sensed urban land use and land cover change for mapping intra-urban structure and component dynamics. China’s Land Use/cover Dataset (CLUD) is updated, delineating the imperviousness and green surface conditions in cities from 2000 to 2018. The newly developed datasets can be used to enhance our understanding of urbanization impacts on ecological and regional climatic conditions and on urban dwellers' environments.
We propose a hierarchical principle for remotely sensed urban land use and land cover change for...
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