Multi-Scale Remote Sensing Assessment of Ecological Environment Quality and Its Driving Factors in Watersheds: A Case Study of Huashan Creek Watershed in China
The Huashan Creek watershed is the largest water source and the main production area of honeydew in Pinghe County, whose extensive cultivation of honeydew has exacerbated soil and water pollution. However, the spatial application of remote sensing ecological index (RSEI) in this watershed and key dr...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-12-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/15/24/5633 |
| _version_ | 1797379480526782464 |
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| author | Yajing Liao Guirong Wu Zhenyu Zhang |
| author_facet | Yajing Liao Guirong Wu Zhenyu Zhang |
| author_sort | Yajing Liao |
| collection | DOAJ |
| description | The Huashan Creek watershed is the largest water source and the main production area of honeydew in Pinghe County, whose extensive cultivation of honeydew has exacerbated soil and water pollution. However, the spatial application of remote sensing ecological index (RSEI) in this watershed and key driving factors are not clear considering the applicability of data quality and the diversity of methodological scales. To explore the RSEI and driving factors at distinct scales in Huashan Creek watershed, this study constructed the RSEI based on the environmental balance matrix at seven scales in 2020, revealed its spatial response characteristics at different scales, and analyzed the key drivers. The results show that the 240 m grid as well as rural and watershed scale convergence analyses satisfy the assessment of RSEI, whose Moran indexes are 0.558, 0.595, and 0.146, respectively. The RSEIs at different scales have significant spatial aggregation characteristics, but the overall status is moderate. The central town–riparian area with poor RSEI contrasts with the western mountainous area, which has comparatively better quality. Population has a major influence on RSEI at multiple scales (0.8), with elevation and patch index acting significantly at the village and grid scales, respectively. These findings help to identify the spatial distribution of quality and control mechanisms of RSEI in the Huashan Creek watershed and provide new insights into key scales and drivers of ecological restoration practices in the watershed. |
| first_indexed | 2024-03-08T20:23:54Z |
| format | Article |
| id | doaj.art-38cd224a8a64408fa7694de235609dae |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-08T20:23:54Z |
| publishDate | 2023-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-38cd224a8a64408fa7694de235609dae2023-12-22T14:38:48ZengMDPI AGRemote Sensing2072-42922023-12-011524563310.3390/rs15245633Multi-Scale Remote Sensing Assessment of Ecological Environment Quality and Its Driving Factors in Watersheds: A Case Study of Huashan Creek Watershed in ChinaYajing Liao0Guirong Wu1Zhenyu Zhang2College of the Environment and Ecology, Xiamen University, Xiamen 361005, ChinaFujian Geologic Surveying and Mapping Institute, Fuzhou 351005, ChinaCollege of the Environment and Ecology, Xiamen University, Xiamen 361005, ChinaThe Huashan Creek watershed is the largest water source and the main production area of honeydew in Pinghe County, whose extensive cultivation of honeydew has exacerbated soil and water pollution. However, the spatial application of remote sensing ecological index (RSEI) in this watershed and key driving factors are not clear considering the applicability of data quality and the diversity of methodological scales. To explore the RSEI and driving factors at distinct scales in Huashan Creek watershed, this study constructed the RSEI based on the environmental balance matrix at seven scales in 2020, revealed its spatial response characteristics at different scales, and analyzed the key drivers. The results show that the 240 m grid as well as rural and watershed scale convergence analyses satisfy the assessment of RSEI, whose Moran indexes are 0.558, 0.595, and 0.146, respectively. The RSEIs at different scales have significant spatial aggregation characteristics, but the overall status is moderate. The central town–riparian area with poor RSEI contrasts with the western mountainous area, which has comparatively better quality. Population has a major influence on RSEI at multiple scales (0.8), with elevation and patch index acting significantly at the village and grid scales, respectively. These findings help to identify the spatial distribution of quality and control mechanisms of RSEI in the Huashan Creek watershed and provide new insights into key scales and drivers of ecological restoration practices in the watershed.https://www.mdpi.com/2072-4292/15/24/5633remote sensing ecological index (RSEI)Huashan Creek watershedspatiotemporalchangegeographically weighted regression |
| spellingShingle | Yajing Liao Guirong Wu Zhenyu Zhang Multi-Scale Remote Sensing Assessment of Ecological Environment Quality and Its Driving Factors in Watersheds: A Case Study of Huashan Creek Watershed in China Remote Sensing remote sensing ecological index (RSEI) Huashan Creek watershed spatiotemporalchange geographically weighted regression |
| title | Multi-Scale Remote Sensing Assessment of Ecological Environment Quality and Its Driving Factors in Watersheds: A Case Study of Huashan Creek Watershed in China |
| title_full | Multi-Scale Remote Sensing Assessment of Ecological Environment Quality and Its Driving Factors in Watersheds: A Case Study of Huashan Creek Watershed in China |
| title_fullStr | Multi-Scale Remote Sensing Assessment of Ecological Environment Quality and Its Driving Factors in Watersheds: A Case Study of Huashan Creek Watershed in China |
| title_full_unstemmed | Multi-Scale Remote Sensing Assessment of Ecological Environment Quality and Its Driving Factors in Watersheds: A Case Study of Huashan Creek Watershed in China |
| title_short | Multi-Scale Remote Sensing Assessment of Ecological Environment Quality and Its Driving Factors in Watersheds: A Case Study of Huashan Creek Watershed in China |
| title_sort | multi scale remote sensing assessment of ecological environment quality and its driving factors in watersheds a case study of huashan creek watershed in china |
| topic | remote sensing ecological index (RSEI) Huashan Creek watershed spatiotemporalchange geographically weighted regression |
| url | https://www.mdpi.com/2072-4292/15/24/5633 |
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