Monitoring of Land Subsidence and Analysis of Impact Factors in the Tianshan North Slope Urban Agglomeration
As one of the 19 key regions for comprehensive land development in China, the Tianshan North Slope urban agglomeration is significant for China’s urban development when calculating the land subsidence and analyzing the impact factors. This study focused on eight cities in the Tianshan North Slope ur...
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2025-01-01
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author | Xiaoqiang Yi Lang Wang Hui Ci Ran Wang Hui Yang Zhaojin Yan |
author_facet | Xiaoqiang Yi Lang Wang Hui Ci Ran Wang Hui Yang Zhaojin Yan |
author_sort | Xiaoqiang Yi |
collection | DOAJ |
description | As one of the 19 key regions for comprehensive land development in China, the Tianshan North Slope urban agglomeration is significant for China’s urban development when calculating the land subsidence and analyzing the impact factors. This study focused on eight cities in the Tianshan North Slope urban agglomeration, calculating the land subsidence rate from 18 January 2018 to 12 April 2023 using Sentinel-1A data and analyzing the spatiotemporal patterns and impact factors of land subsidence. The results showed that (1) the average land subsidence rate is mainly distributed between −30 and 10 mm/a, and the maximum subsidence rate can reach −358 mm/a. Land uplift mainly occurs in Hutubi County and Manas County. (2) From the transition matrix, landscape pattern index, and Moran’s I, the spatiotemporal patterns of the land subsidence rate are obvious, with a spatial positive correlation. During the monitoring period, each administration experienced varying degrees of land subsidence or uplift processes. (3) Using GeoDetector to perform quantitative analyses, it was found that the hydrological environment is significant to land subsidence, and human activities, such as road network density and nighttime lighting, contribute the least to land subsidence, suggesting that it is related to the arid climate of the study area. This paper aims to provide theoretical support for the stable development of and production activities in the study area. This approach not only offers technical support but also provides guidance for evaluating, monitoring, and the early warning of land subsidence in the region. |
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institution | Kabale University |
issn | 2073-445X |
language | English |
publishDate | 2025-01-01 |
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spelling | doaj-art-28c15e6a78ed49c8acd79891fac5f40d2025-01-24T13:38:19ZengMDPI AGLand2073-445X2025-01-0114120210.3390/land14010202Monitoring of Land Subsidence and Analysis of Impact Factors in the Tianshan North Slope Urban AgglomerationXiaoqiang Yi0Lang Wang1Hui Ci2Ran Wang3Hui Yang4Zhaojin Yan5School of Resources and Geosciences, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Resources and Geosciences, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Resources and Geosciences, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Resources and Geosciences, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Resources and Geosciences, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Resources and Geosciences, China University of Mining and Technology, Xuzhou 221116, ChinaAs one of the 19 key regions for comprehensive land development in China, the Tianshan North Slope urban agglomeration is significant for China’s urban development when calculating the land subsidence and analyzing the impact factors. This study focused on eight cities in the Tianshan North Slope urban agglomeration, calculating the land subsidence rate from 18 January 2018 to 12 April 2023 using Sentinel-1A data and analyzing the spatiotemporal patterns and impact factors of land subsidence. The results showed that (1) the average land subsidence rate is mainly distributed between −30 and 10 mm/a, and the maximum subsidence rate can reach −358 mm/a. Land uplift mainly occurs in Hutubi County and Manas County. (2) From the transition matrix, landscape pattern index, and Moran’s I, the spatiotemporal patterns of the land subsidence rate are obvious, with a spatial positive correlation. During the monitoring period, each administration experienced varying degrees of land subsidence or uplift processes. (3) Using GeoDetector to perform quantitative analyses, it was found that the hydrological environment is significant to land subsidence, and human activities, such as road network density and nighttime lighting, contribute the least to land subsidence, suggesting that it is related to the arid climate of the study area. This paper aims to provide theoretical support for the stable development of and production activities in the study area. This approach not only offers technical support but also provides guidance for evaluating, monitoring, and the early warning of land subsidence in the region.https://www.mdpi.com/2073-445X/14/1/202Tianshan North Slope urban agglomerationSentinel-1A dataland subsidencespatiotemporal patternsimpact factors |
spellingShingle | Xiaoqiang Yi Lang Wang Hui Ci Ran Wang Hui Yang Zhaojin Yan Monitoring of Land Subsidence and Analysis of Impact Factors in the Tianshan North Slope Urban Agglomeration Land Tianshan North Slope urban agglomeration Sentinel-1A data land subsidence spatiotemporal patterns impact factors |
title | Monitoring of Land Subsidence and Analysis of Impact Factors in the Tianshan North Slope Urban Agglomeration |
title_full | Monitoring of Land Subsidence and Analysis of Impact Factors in the Tianshan North Slope Urban Agglomeration |
title_fullStr | Monitoring of Land Subsidence and Analysis of Impact Factors in the Tianshan North Slope Urban Agglomeration |
title_full_unstemmed | Monitoring of Land Subsidence and Analysis of Impact Factors in the Tianshan North Slope Urban Agglomeration |
title_short | Monitoring of Land Subsidence and Analysis of Impact Factors in the Tianshan North Slope Urban Agglomeration |
title_sort | monitoring of land subsidence and analysis of impact factors in the tianshan north slope urban agglomeration |
topic | Tianshan North Slope urban agglomeration Sentinel-1A data land subsidence spatiotemporal patterns impact factors |
url | https://www.mdpi.com/2073-445X/14/1/202 |
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