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Xu N, Zeng P, Guo Y, Siddique MA, Li J, Ren X, Tang F, Zhang R. The spatiotemporal evolution of rural landscape patterns in Chinese metropolises under rapid urbanization. PLoS One 2024; 19:e0301754. [PMID: 38709778 PMCID: PMC11073728 DOI: 10.1371/journal.pone.0301754] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 03/20/2024] [Indexed: 05/08/2024] Open
Abstract
Understanding the evolution of rural landscapes in metropolises during rapid urbanization is crucial for formulating policies to protect the rural ecological environment. In this study, remote sensing and geographical information system data, as well as applied landscape index analysis, are used to examine the spatiotemporal evolution of rural landscape patterns in the Beijing-Tianjin region of China, which has experienced rapid urbanization. The relationships between land use/land cover changes and changes in rural landscape patterns are explored. The results revealed significant spatial differences in the rural landscapes in the Beijing-Tianjin region; farmland and forestland were the main types of landscapes, creating a "mountain-field-sea" natural landscape pattern. The conversion of rural landscapes in the Beijing-Tianjin region involved mainly the conversion of farmland to urban areas, with few exchanges between other landscape types. The urban areas in the Beijing-Tianjin region increased by 3% per decade; farmland decreased at the same rate. Additionally, the rural landscape patterns in the Beijing-Tianjin region were dominated by fragmentation, dispersion, and heterogeneity and moved from complex to regular. Water bodies displayed the most fragmented natural landscape; their number of patches increased by 36%, though their network characteristics were maintained. Forestland was the most concentrated natural landscape. In this study, theoretical support and a scientific reference for the optimization of rural landscape patterns and the improvement in rural living environments in rapidly urbanizing areas are provided.
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Affiliation(s)
- Ninghan Xu
- Department of Urban Planning, School of Architecture, Tianjin University, Tianjin, China
| | - Peng Zeng
- Department of Urban Planning, School of Architecture, Tianjin University, Tianjin, China
| | - Yuanyuan Guo
- Department of Urban Planning, School of Architecture, Tianjin University, Tianjin, China
| | - Muhammad Amir Siddique
- Department of Urban Planning, School of Architecture, Tianjin University, Tianjin, China
| | - Jinxuan Li
- Department of Urban Planning, School of Architecture, Tianjin University, Tianjin, China
| | - Xiaotong Ren
- Department of Urban Planning, School of Architecture, Tianjin University, Tianjin, China
| | - Fengliang Tang
- Department of Urban Planning, School of Architecture, Tianjin University, Tianjin, China
| | - Ran Zhang
- Department of Urban Planning, School of Architecture, Tianjin University, Tianjin, China
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Chen X, Wu S, Wu J. Characteristics and formation mechanism of Land use conflicts in northern Anhui: A Case study of Funan county. Heliyon 2024; 10:e22923. [PMID: 38169810 PMCID: PMC10758732 DOI: 10.1016/j.heliyon.2023.e22923] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Revised: 11/21/2023] [Accepted: 11/22/2023] [Indexed: 01/05/2024] Open
Abstract
The rapid development of global urbanization and industrialization not only promotes a significant improvement in the level of socio-economic development, but also exacerbates the complexity and vulnerability of regional land resource utilization, resulting in frequent land use conflicts and seriously constraining the sustainable development of regional socio-economic and ecological environment. Taking Funan County as an example, based on interpretation data of Landsat TM/ETM remote sensing image data from 1980 to 2020, this paper analyses the temporal and spatial evolution characteristics of land use conflict in Funan County from 1980 to 2020 using the ArcGIS spatial analysis method, land use conflict measurement model, geographically weighted regression and geographical detector and then deeply analyses the main factors affecting land use conflict in Funan County and its driving mechanisms. In descending order, land use types undergoing the most change include cultivated land, urban and rural construction land, grassland, forestland and water area. The results of land use change are mainly the occupation of cultivated land by construction land, water area and forestland. Overall land use conflict in Funan County is serious with approximately 80 % of land use in the county in conflict, the severe land use conflict is mostly concentrated in urban and township built-up areas, and there is an increase trend year by year. Land use conflict is the result of multiple factors. Policy, economic development, and the social population and natural environment are the key driving factors behind land use conflict, which have a significant impact on the direction, location, scale and rate of land use transfer.Accurately identifying regional land use changes and conflicts and exploring the driving mechanism behind land use conflicts are of great significance for achieving the sustainable development of regional social economies and ecological environments.
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Affiliation(s)
- Xiaohua Chen
- School of Architecture and Planning, Anhui Jianzhu University, Hefei 230601, China
- Research Center of Urbanization Development in Anhui Province, Hefei 230601, China
| | - Shiqiang Wu
- School of Architecture and Planning, Anhui Jianzhu University, Hefei 230601, China
- Research Center of Urbanization Development in Anhui Province, Hefei 230601, China
| | - Jiang Wu
- School of Architecture and Planning, Anhui Jianzhu University, Hefei 230601, China
- Research Center of Urbanization Development in Anhui Province, Hefei 230601, China
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Waleed M, Sajjad M, Shazil MS, Tariq M, Alam MT. Machine learning-based spatial-temporal assessment and change transition analysis of wetlands: An application of Google Earth Engine in Sylhet, Bangladesh (1985–2022). ECOL INFORM 2023. [DOI: 10.1016/j.ecoinf.2023.102075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/29/2023]
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Zhang Y, Du J, Guo L, Fang S, Zhang J, Sun B, Mao J, Sheng Z, Li L. Long-term detection and spatiotemporal variation analysis of open-surface water bodies in the Yellow River Basin from 1986 to 2020. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 845:157152. [PMID: 35803420 DOI: 10.1016/j.scitotenv.2022.157152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 06/28/2022] [Accepted: 06/30/2022] [Indexed: 06/15/2023]
Abstract
Accurately investigating long-term information about open-surface water bodies can contribute to water resource protection and management. However, due to the limits of big-data calculations for remote sensing, there has been no specific study on the long-term changes in the water bodies in the Yellow River Basin. Thus, in this study, we developed a new combined extraction rule to build an entire annual-scale open-surface water body dataset for 1986-2020 with excellent effectiveness in eliminating the interference of shadows in the Yellow River Basin using all of the available Landsat images. For the first time, the spatial distribution, change trends, conversion processes, and the heterogeneity of the surface water bodies in the Yellow River Basin were analyzed comprehensively to the best of our knowledge. The extraction results had an overall accuracy of 99.70 % and a kappa coefficient of 0.90, which were validated using 34,073 verification points selected on high-resolution Google Earth images and random Landsat images. The total area of water bodies initially decreased (1986-2000) and then increased (2001-2020); however, only the size of the permanent water bodies increased in most areas, while the size of most of the seasonal water bodies decreased. In regions with human-made water bodies, the non-water areas were substantially converted to seasonal and permanent water bodies; however, in areas with natural water bodies, many permanent and seasonal water bodies were gradually converted to non-water areas. Thus, most of the increases in the water bodies occurred in the form of artificial lakes and reservoirs, while most of the decreases in the water body area occurred in natural wetlands and lakes. The areas of both the permanent and seasonal water bodies were positively correlated with precipitation, but only the area of the seasonal water bodies was negatively correlated with temperature.
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Affiliation(s)
- Yangchengsi Zhang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; State Environmental Protection Key Laboratory of Regional Eco-process and Function Assessment, Chinese Research Academy of Environmental Science, Beijing 100012, China.
| | - Jiaqiang Du
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; State Environmental Protection Key Laboratory of Regional Eco-process and Function Assessment, Chinese Research Academy of Environmental Science, Beijing 100012, China.
| | - Long Guo
- College of Resources and Environment, Huazhong Agricultural University, Wuhan 430070, China.
| | - Shifeng Fang
- State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
| | - Jing Zhang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; State Environmental Protection Key Laboratory of Regional Eco-process and Function Assessment, Chinese Research Academy of Environmental Science, Beijing 100012, China; School of Life Sciences, Lanzhou University, Lanzhou 730000, China.
| | - Bingqing Sun
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; State Environmental Protection Key Laboratory of Regional Eco-process and Function Assessment, Chinese Research Academy of Environmental Science, Beijing 100012, China.
| | - Jialin Mao
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; State Environmental Protection Key Laboratory of Regional Eco-process and Function Assessment, Chinese Research Academy of Environmental Science, Beijing 100012, China; School of Life Sciences, Lanzhou University, Lanzhou 730000, China.
| | - Zhilu Sheng
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; State Environmental Protection Key Laboratory of Regional Eco-process and Function Assessment, Chinese Research Academy of Environmental Science, Beijing 100012, China.
| | - Lijuan Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; State Environmental Protection Key Laboratory of Regional Eco-process and Function Assessment, Chinese Research Academy of Environmental Science, Beijing 100012, China.
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Li M, Liu S, Wang F, Liu H, Liu Y, Wang Q. Cost-benefit analysis of ecological restoration based on land use scenario simulation and ecosystem service on the Qinghai-Tibet Plateau. Glob Ecol Conserv 2022. [DOI: 10.1016/j.gecco.2022.e02006] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
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