Quantitatively exploring the influence of geographical conditions on ecological quality using a novel remote sensing model: a comparison between two geographical disparity regions in China
The ecological quality of a region is significantly influenced by its geographical conditions, which can yield different effects on ecosystems. Nevertheless, the lack of adequate technology has impeded quantitative investigations into these differences. Consequently, there is an increasing demand fo...
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Taylor & Francis Group
2025-05-01
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| Series: | Geo-spatial Information Science |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/10095020.2024.2380779 |
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| author | Hanqiu Xu Mengjing Lin Yifan Wang Huade Guan Fei Tang |
| author_facet | Hanqiu Xu Mengjing Lin Yifan Wang Huade Guan Fei Tang |
| author_sort | Hanqiu Xu |
| collection | DOAJ |
| description | The ecological quality of a region is significantly influenced by its geographical conditions, which can yield different effects on ecosystems. Nevertheless, the lack of adequate technology has impeded quantitative investigations into these differences. Consequently, there is an increasing demand for effective techniques to quantitatively measure differences in ecological quality resulting from variations in geographical conditions. This study applied the novel Remote Sensing-based Ecological Index (RSEI) concurrently to two distinct provincial-level regions in China, Fujian and Ningxia, to quantitatively detect their ecological differences. These two regions possess contrasting geographical conditions, with Fujian having high forest coverage and abundant rainfall, while Ningxia features low forest coverage and extensive loess plateau and desert terrain. By linking geographical factors with their corresponding ecological responses, we conducted a comprehensive analysis to determine whether the contrasting geographical conditions between the two regions had caused significant disparities in their ecological status. The results indicate that the contrasting geographical conditions have indeed led to marked ecological differences, with Fujian exhibiting excellent ecological status, while Ningxia lags behind due to unfavorable geographical conditions. In terms of RSEI scores, Fujian consistently achieved higher RSEI values (>0.8) in the study years, reaching an excellent ecological level, whereas Ningxia recorded scores lower than 0.45 during the comparable years, corresponding to a poor to moderate ecological level. Regarding the impact of geographical factors on ecological conditions, the positive contributions of greenness and wetness indicators to the ecology in Fujian were significantly greater than those in Ningxia (58% vs. 39%), whereas the contributions of negative indicators, dryness and hotness, were notably higher in Ningxia compared to Fujian (|–61|% vs. |–42|%). The successful concurrent application of RSEI to these two geographically distant regions also demonstrates the robustness of the RSEI technique. |
| format | Article |
| id | doaj-art-9cc5476b7f8740ae94bf4b13728ec86d |
| institution | Kabale University |
| issn | 1009-5020 1993-5153 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Geo-spatial Information Science |
| spelling | doaj-art-9cc5476b7f8740ae94bf4b13728ec86d2025-08-20T03:41:11ZengTaylor & Francis GroupGeo-spatial Information Science1009-50201993-51532025-05-0128384986610.1080/10095020.2024.2380779Quantitatively exploring the influence of geographical conditions on ecological quality using a novel remote sensing model: a comparison between two geographical disparity regions in ChinaHanqiu Xu0Mengjing Lin1Yifan Wang2Huade Guan3Fei Tang4College of Environment and Safety Engineering, Fuzhou University, Fuzhou, ChinaKey Laboratory of Spatial Data Mining and Information Sharing, Ministry of Education, Academy of Digital China (Fujian), Fuzhou University, Fuzhou, ChinaCollege of Environment and Safety Engineering, Fuzhou University, Fuzhou, ChinaCollege of Science and Engineering, Flinders University, Adelaide, AustraliaFujian Provincial Key Laboratory of Island Monitoring and Ecological Development, Island Research Center, Ministry of Natural Resources, Fujian, ChinaThe ecological quality of a region is significantly influenced by its geographical conditions, which can yield different effects on ecosystems. Nevertheless, the lack of adequate technology has impeded quantitative investigations into these differences. Consequently, there is an increasing demand for effective techniques to quantitatively measure differences in ecological quality resulting from variations in geographical conditions. This study applied the novel Remote Sensing-based Ecological Index (RSEI) concurrently to two distinct provincial-level regions in China, Fujian and Ningxia, to quantitatively detect their ecological differences. These two regions possess contrasting geographical conditions, with Fujian having high forest coverage and abundant rainfall, while Ningxia features low forest coverage and extensive loess plateau and desert terrain. By linking geographical factors with their corresponding ecological responses, we conducted a comprehensive analysis to determine whether the contrasting geographical conditions between the two regions had caused significant disparities in their ecological status. The results indicate that the contrasting geographical conditions have indeed led to marked ecological differences, with Fujian exhibiting excellent ecological status, while Ningxia lags behind due to unfavorable geographical conditions. In terms of RSEI scores, Fujian consistently achieved higher RSEI values (>0.8) in the study years, reaching an excellent ecological level, whereas Ningxia recorded scores lower than 0.45 during the comparable years, corresponding to a poor to moderate ecological level. Regarding the impact of geographical factors on ecological conditions, the positive contributions of greenness and wetness indicators to the ecology in Fujian were significantly greater than those in Ningxia (58% vs. 39%), whereas the contributions of negative indicators, dryness and hotness, were notably higher in Ningxia compared to Fujian (|–61|% vs. |–42|%). The successful concurrent application of RSEI to these two geographically distant regions also demonstrates the robustness of the RSEI technique.https://www.tandfonline.com/doi/10.1080/10095020.2024.2380779Remote sensing-based ecological index (RSEI)geographical contrastecological disparityassessmentcomparative analysischange detection |
| spellingShingle | Hanqiu Xu Mengjing Lin Yifan Wang Huade Guan Fei Tang Quantitatively exploring the influence of geographical conditions on ecological quality using a novel remote sensing model: a comparison between two geographical disparity regions in China Geo-spatial Information Science Remote sensing-based ecological index (RSEI) geographical contrast ecological disparity assessment comparative analysis change detection |
| title | Quantitatively exploring the influence of geographical conditions on ecological quality using a novel remote sensing model: a comparison between two geographical disparity regions in China |
| title_full | Quantitatively exploring the influence of geographical conditions on ecological quality using a novel remote sensing model: a comparison between two geographical disparity regions in China |
| title_fullStr | Quantitatively exploring the influence of geographical conditions on ecological quality using a novel remote sensing model: a comparison between two geographical disparity regions in China |
| title_full_unstemmed | Quantitatively exploring the influence of geographical conditions on ecological quality using a novel remote sensing model: a comparison between two geographical disparity regions in China |
| title_short | Quantitatively exploring the influence of geographical conditions on ecological quality using a novel remote sensing model: a comparison between two geographical disparity regions in China |
| title_sort | quantitatively exploring the influence of geographical conditions on ecological quality using a novel remote sensing model a comparison between two geographical disparity regions in china |
| topic | Remote sensing-based ecological index (RSEI) geographical contrast ecological disparity assessment comparative analysis change detection |
| url | https://www.tandfonline.com/doi/10.1080/10095020.2024.2380779 |
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