Scenario simulation of land use and land cover change in mining area

Abstract In this study, we selected 11 townships with severe ground subsidence located in Weishan County as the study area. Based on the interpretation data of Landsat images, the Binary logistic regression model was used to explore the relationship between land use and land cover (LULC) change and...

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Autores principales:	Xiaoyan Chang, Feng Zhang, Kanglin Cong, Xiaojun Liu
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/728a996a729f45cb983ca05b65354614
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spelling	oai:doaj.org-article:728a996a729f45cb983ca05b653546142021-12-02T16:04:26ZScenario simulation of land use and land cover change in mining area10.1038/s41598-021-92299-52045-2322https://doaj.org/article/728a996a729f45cb983ca05b653546142021-06-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-92299-5https://doaj.org/toc/2045-2322Abstract In this study, we selected 11 townships with severe ground subsidence located in Weishan County as the study area. Based on the interpretation data of Landsat images, the Binary logistic regression model was used to explore the relationship between land use and land cover (LULC) change and the related 7 driving factors at a resolution of 60 m. Using the CLUE-S model, combined with Markov model, the simulation of LULC under three scenarios—namely, natural development scenario, ecological protection scenario and farmland protection scenario—were explored. Firstly, using LULC map in 2005 as input data, we predicted the land use spatial distribution pattern in 2016. By comparing the actual LULC map in 2016 with the simulated map in 2016, the prediction accuracy was evaluated based on the Kappa index. Then, after validation, the spatial distribution pattern of LULC in 2025 under the three scenarios was simulated. The results showed the following: (1) The driving factors had satisfactory explanatory power for LULC changes. The Kappa index was 0.82, which indicated good simulation accuracy of the CLUE-S model. (2) Under the three scenarios, the area of other agricultural land and water body showed an increasing trend; while the area of farmland, urban and rural construction land, subsided land with water accumulation, and tidal wetland showed a decreasing trend, and the area of urban and rural construction land and tidal wetland decreased the fastest. (3) Under the ecological protection scenario, the farmland decreased faster than the other two scenarios, and most of the farmland was converted to ecological land such as garden land and water body. Under the farmland protection scenario, the area of tidal wetland decreased the fastest, followed by urban and rural construction land. We anticipate that our study results will provide useful information for decision-makers and planners to take appropriate land management measures in the mining area.Xiaoyan ChangFeng ZhangKanglin CongXiaojun LiuNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Xiaoyan Chang Feng Zhang Kanglin Cong Xiaojun Liu Scenario simulation of land use and land cover change in mining area
description	Abstract In this study, we selected 11 townships with severe ground subsidence located in Weishan County as the study area. Based on the interpretation data of Landsat images, the Binary logistic regression model was used to explore the relationship between land use and land cover (LULC) change and the related 7 driving factors at a resolution of 60 m. Using the CLUE-S model, combined with Markov model, the simulation of LULC under three scenarios—namely, natural development scenario, ecological protection scenario and farmland protection scenario—were explored. Firstly, using LULC map in 2005 as input data, we predicted the land use spatial distribution pattern in 2016. By comparing the actual LULC map in 2016 with the simulated map in 2016, the prediction accuracy was evaluated based on the Kappa index. Then, after validation, the spatial distribution pattern of LULC in 2025 under the three scenarios was simulated. The results showed the following: (1) The driving factors had satisfactory explanatory power for LULC changes. The Kappa index was 0.82, which indicated good simulation accuracy of the CLUE-S model. (2) Under the three scenarios, the area of other agricultural land and water body showed an increasing trend; while the area of farmland, urban and rural construction land, subsided land with water accumulation, and tidal wetland showed a decreasing trend, and the area of urban and rural construction land and tidal wetland decreased the fastest. (3) Under the ecological protection scenario, the farmland decreased faster than the other two scenarios, and most of the farmland was converted to ecological land such as garden land and water body. Under the farmland protection scenario, the area of tidal wetland decreased the fastest, followed by urban and rural construction land. We anticipate that our study results will provide useful information for decision-makers and planners to take appropriate land management measures in the mining area.
format	article
author	Xiaoyan Chang Feng Zhang Kanglin Cong Xiaojun Liu
author_facet	Xiaoyan Chang Feng Zhang Kanglin Cong Xiaojun Liu
author_sort	Xiaoyan Chang
title	Scenario simulation of land use and land cover change in mining area
title_short	Scenario simulation of land use and land cover change in mining area
title_full	Scenario simulation of land use and land cover change in mining area
title_fullStr	Scenario simulation of land use and land cover change in mining area
title_full_unstemmed	Scenario simulation of land use and land cover change in mining area
title_sort	scenario simulation of land use and land cover change in mining area
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/728a996a729f45cb983ca05b65354614
work_keys_str_mv	AT xiaoyanchang scenariosimulationoflanduseandlandcoverchangeinminingarea AT fengzhang scenariosimulationoflanduseandlandcoverchangeinminingarea AT kanglincong scenariosimulationoflanduseandlandcoverchangeinminingarea AT xiaojunliu scenariosimulationoflanduseandlandcoverchangeinminingarea
_version_	1718385213890887680

Scenario simulation of land use and land cover change in mining area

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