4.7 Article

Land use/land cover prediction and analysis of the middle reaches of the Yangtze River under different scenarios

期刊

SCIENCE OF THE TOTAL ENVIRONMENT
卷 833, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.scitotenv.2022.155238

关键词

Remote sensing; Random forest; Patch generated land use simulation model; SSP-RCP; Yangtze River basin

资金

  1. Open Fund of National Engineering Research Center for Geographic Information System, China University of Geosciences
  2. State Key Laboratory of Water Resources and Hydropower Engineering Science [2020SWG01]
  3. Strategic Priority Research Program of the Chinese Academy of Sciences [XDA23040504]

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This study predicts and analyzes land use and land cover changes in the middle reaches of the Yangtze River basin under different future scenarios. The findings show that forests and farmland exhibit significant changes, and factors such as GDP, population, temperature, and precipitation play crucial roles in driving these changes.
Land use and land cover (LULC) projections are critical for climate models to predict the impacts of LULC change on the Earth system. Different assumptions and policies influence LULC changes, which are a key factor in the decisions of planners and conservationists. Therefore, we predicted and analyzed LULC changes in future scenarios (SSP1-26, SSP2-45, SSP5-85) in the middle reaches of the Yangtze River basin (MYRB). We obtain historical (i.e., 2005-2020) LULC data from the Google Earth Engine (GEE) platform using the random forest (RF) classification method. LULC data for different future scenarios are also obtained by the driving factors of LULC changes in future shared socioeconomic pathways (SSPs), representative concentration pathways (RCPs) (SSP-RCP) scenarios (i.e., 2035-2095) and the patch-generated land use simulation (PLUS) model. The major findings are as follows: (1) simulation using the PLUS model based on the acquired classification data and the selected drivers can obtain accurate land use data in MYRB and a Kappa coefficient of 89.6% and 0.82, respectively; (2) as for the LULC changes in the MYRB, forests increased by 3.9% and decreased by 1.2% in the SSP1-26 and SSP5-85 scenarios, respectively, while farmland decreased by 9.2% and increased by 13.4% in SSP 1-26 and SSP 2-45, respectively, during 2080-2095; and (3) the main conversions in LULC in the MYRB were farmland to forest, forests/water bodies to farmland, and forests/grasslands to farmland/buildings in SSP1-2.6, SSP2-4.5, and SSP 5-8.5, respectively. This can be mainly attributed to gross domestic product (GDP), population (POP), temperature, and precipitation. Overall, this study not only contributes to the understanding of the mechanisms of LULC changes in the MYRB but also provides a basis for ecological and climatic studies.

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