Cargando…

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

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 relat...

Descripción completa

Detalles Bibliográficos
Autores principales: Chang, Xiaoyan, Zhang, Feng, Cong, Kanglin, Liu, Xiaojun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8213712/
https://www.ncbi.nlm.nih.gov/pubmed/34145350
http://dx.doi.org/10.1038/s41598-021-92299-5
_version_ 1783709909798354944
author Chang, Xiaoyan
Zhang, Feng
Cong, Kanglin
Liu, Xiaojun
author_facet Chang, Xiaoyan
Zhang, Feng
Cong, Kanglin
Liu, Xiaojun
author_sort Chang, Xiaoyan
collection PubMed
description 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 Online
Article
Text
id pubmed-8213712
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-82137122021-06-21 Scenario simulation of land use and land cover change in mining area Chang, Xiaoyan Zhang, Feng Cong, Kanglin Liu, Xiaojun Sci Rep Article 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. Nature Publishing Group UK 2021-06-18 /pmc/articles/PMC8213712/ /pubmed/34145350 http://dx.doi.org/10.1038/s41598-021-92299-5 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Chang, Xiaoyan
Zhang, Feng
Cong, Kanglin
Liu, Xiaojun
Scenario simulation of land use and land cover change in mining area
title 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_short 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
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8213712/
https://www.ncbi.nlm.nih.gov/pubmed/34145350
http://dx.doi.org/10.1038/s41598-021-92299-5
work_keys_str_mv AT changxiaoyan scenariosimulationoflanduseandlandcoverchangeinminingarea
AT zhangfeng scenariosimulationoflanduseandlandcoverchangeinminingarea
AT congkanglin scenariosimulationoflanduseandlandcoverchangeinminingarea
AT liuxiaojun scenariosimulationoflanduseandlandcoverchangeinminingarea