Abstract
Land use and land cover (LULC) changes are dynamic and have been extensively studied; the change in LULC has become a crucial factor in decision making for planners and conservationists owing to its impact on natural ecosystems. Deriving accurate LULC data and analyzing their changes are important for assessing the energy balance, carbon balance, and hydrological cycle in a region. Therefore, we investigated the best classification method from the four methods and analyzed the change in LULC in the middle Yangtze River basin (MYRB) from 2001 to 2020 using the Google Earth Engine (GEE). The results suggest that (1) GEE platform enables to rapidly acquire and process remote sensing images for deriving LULC, and the random forest (RF) algorithm was able to calculate the highest overall accuracy and kappa coefficient (KC) of 87.7% and 0.84, respectively; (2) forestland occupied the largest area from 2001 to 2020, followed by water bodies and buildings. During the study period, there was a significant change in area occupied by both water bodies (overall increase of 46.2%) and buildings (decrease of 14.3% from 2001 to 2005); and (3) the simulation of LULC in the MYRB area was based on the primary drivers in the area, of which elevation changes had the largest effect on LULC changes. The patch generated land use simulation model (PLUS) was used to produce the simulation, with an overall accuracy and KC of 89.6% and 0.82, respectively. This study not only was useful for understanding the spatial and temporal characteristics of LULC in the MYRB, but also offered the basis for the simulation of ecological quality in this region.
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Data availability
The data that support the findings of this study are available in US Geological Survey at https://earthdata.nasa.gov. These data were derived from the following resources available in the public domain: Landsat 5, 7, and 8 surface reflectance images (available at: https://developers.google.com/earth-engine/datasets/catalog/landsat).
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Acknowledgements
Remote sensing image data used to calculate NDVI, NDBI, and MNDWI band were derived from https://developers.google.com/earth-engine/datasets/catalog/landsat. The PLUS model downloaded from https://github.com/HPSCIL/Patch-generating_Land_Use_Simulation_Model. We would like to express our sincere thanks to all data supporters and websites.
Funding
The research is supported by Supported by the Open Research Fund of State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin,China Institute of Water Resources and Hydropower Research (IWHR-SKL-202217), Strategic Priority Research Program of the Chinese Academy of Sciences (No. XDA23040504), and Open Fund of National Engineering Research Center for Geographic Information System, China University of Geosciences.
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All the authors contributed to the study conception and design. Shengqing Zhang: methodology, validation, investigation, writing–original draft, visualization. Peng Yang: writing–review and editing, supervision, funding acquisition. Jun Xia: project administration. Nengcheng Chen: formal analysis. WenYu Wang: Resources. Wei Cai: data Curation. Sheng Hu: data curation. Xiangang Luo: software. Jiang Li: investigation. Chesheng Zhan: conceptualization. All the authors commented on previous versions of the manuscript. All the authors read and approved the final manuscript.
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Zhang, S., Yang, P., Xia, J. et al. Remote sensing inversion and prediction of land use land cover in the middle reaches of the Yangtze River basin, China. Environ Sci Pollut Res 30, 46306–46320 (2023). https://doi.org/10.1007/s11356-023-25424-8
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DOI: https://doi.org/10.1007/s11356-023-25424-8