Study on the driving mechanism of spatio-temporal non-stationarity of vegetation dynamics in the Taihangshan-Yanshan Region
As an important ecological barrier of the Beijing-Tianjin-Hebei region, the Taihang-Yanshan Region (TYR) plays a crucial role in maintaining the sustainable stability of the ecosystem. This study aims to investigate the spatio-temporal evolution of vegetation dynamics and elucidate the various drivi...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-01-01
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| Series: | Ecological Indicators |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X25000135 |
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| author | Jiao Pang Minli Wang Huicong Zhang Liyao Dong Jiarui Li Yanrui Ding Zhenzhou Zhu Feng Yan |
| author_facet | Jiao Pang Minli Wang Huicong Zhang Liyao Dong Jiarui Li Yanrui Ding Zhenzhou Zhu Feng Yan |
| author_sort | Jiao Pang |
| collection | DOAJ |
| description | As an important ecological barrier of the Beijing-Tianjin-Hebei region, the Taihang-Yanshan Region (TYR) plays a crucial role in maintaining the sustainable stability of the ecosystem. This study aims to investigate the spatio-temporal evolution of vegetation dynamics and elucidate the various driving forces behind these changes, and results indicate that: (1) kernel Normalised Vegetation Index (kNDVI) is effectively capable of reflecting the vegetation changes in the TYR. From 2001 to 2020, kNDVI in spring, summer and autumn showed a slow upward trend and a downward trend in winter. In terms of space, vegetation coverage in Yanshan region is generally higher than that in Taihang Mountain with significant spatial heterogeneity.(2) Theil-Sen Median trend and Hurst index analysis shows that about 70% of regions have shown an increasing trend in kNDVI throughout the year and will continue to increase in the future. (3) The analysis results of Optimal Parameter Geodetector Detectors (OPGD) show that evapotranspiration (ET) is the dominant driving factor of kNDVI, and the interactive enhancement benefits with other factors is significant. Population density and land surface temperature were negatively correlated with kNDVI. (4) Based on the analysis results of multi-scale geographic weighted regression (MGWR) kNDVI is positively correlated with annual cumulative precipitation and ET, and negatively correlated with annual mean temperature and altitude, and the other variables show spatial heterogeneity. Research results provide important references for the formulation of vegetation ecosystem protection and restoration policies in this region. |
| format | Article |
| id | doaj-art-2858c127256945949fc1efce1f568193 |
| institution | Kabale University |
| issn | 1470-160X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj-art-2858c127256945949fc1efce1f5681932025-01-31T05:10:48ZengElsevierEcological Indicators1470-160X2025-01-01170113084Study on the driving mechanism of spatio-temporal non-stationarity of vegetation dynamics in the Taihangshan-Yanshan RegionJiao Pang0Minli Wang1Huicong Zhang2Liyao Dong3Jiarui Li4Yanrui Ding5Zhenzhou Zhu6Feng Yan7Bohai College, Hebei Agricultural University, Huanghua 061100, ChinaSchool of Land Science and Technology, China University of Geosciences (Beijing), Beijing 100083, ChinaSchool of Land and Resources, Hebei Agricultural University, Baoding 071001, ChinaSchool of Land and Resources, Hebei Agricultural University, Baoding 071001, ChinaSchool of Land and Resources, Hebei Agricultural University, Baoding 071001, ChinaBohai College, Hebei Agricultural University, Huanghua 061100, ChinaChina Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing 100083, China; Corresponding authors.School of Land and Resources, Hebei Agricultural University, Baoding 071001, China; Corresponding authors.As an important ecological barrier of the Beijing-Tianjin-Hebei region, the Taihang-Yanshan Region (TYR) plays a crucial role in maintaining the sustainable stability of the ecosystem. This study aims to investigate the spatio-temporal evolution of vegetation dynamics and elucidate the various driving forces behind these changes, and results indicate that: (1) kernel Normalised Vegetation Index (kNDVI) is effectively capable of reflecting the vegetation changes in the TYR. From 2001 to 2020, kNDVI in spring, summer and autumn showed a slow upward trend and a downward trend in winter. In terms of space, vegetation coverage in Yanshan region is generally higher than that in Taihang Mountain with significant spatial heterogeneity.(2) Theil-Sen Median trend and Hurst index analysis shows that about 70% of regions have shown an increasing trend in kNDVI throughout the year and will continue to increase in the future. (3) The analysis results of Optimal Parameter Geodetector Detectors (OPGD) show that evapotranspiration (ET) is the dominant driving factor of kNDVI, and the interactive enhancement benefits with other factors is significant. Population density and land surface temperature were negatively correlated with kNDVI. (4) Based on the analysis results of multi-scale geographic weighted regression (MGWR) kNDVI is positively correlated with annual cumulative precipitation and ET, and negatively correlated with annual mean temperature and altitude, and the other variables show spatial heterogeneity. Research results provide important references for the formulation of vegetation ecosystem protection and restoration policies in this region.http://www.sciencedirect.com/science/article/pii/S1470160X25000135Kernel Normalised Vegetation Index (kNDVI)Spatio-temporal non-stationarityOptimal Parameter Geodetector Detectors (OPGD)Multi-scale Geographically Weighted Regression (MGWR)Taihangshan-Yanshan Region |
| spellingShingle | Jiao Pang Minli Wang Huicong Zhang Liyao Dong Jiarui Li Yanrui Ding Zhenzhou Zhu Feng Yan Study on the driving mechanism of spatio-temporal non-stationarity of vegetation dynamics in the Taihangshan-Yanshan Region Ecological Indicators Kernel Normalised Vegetation Index (kNDVI) Spatio-temporal non-stationarity Optimal Parameter Geodetector Detectors (OPGD) Multi-scale Geographically Weighted Regression (MGWR) Taihangshan-Yanshan Region |
| title | Study on the driving mechanism of spatio-temporal non-stationarity of vegetation dynamics in the Taihangshan-Yanshan Region |
| title_full | Study on the driving mechanism of spatio-temporal non-stationarity of vegetation dynamics in the Taihangshan-Yanshan Region |
| title_fullStr | Study on the driving mechanism of spatio-temporal non-stationarity of vegetation dynamics in the Taihangshan-Yanshan Region |
| title_full_unstemmed | Study on the driving mechanism of spatio-temporal non-stationarity of vegetation dynamics in the Taihangshan-Yanshan Region |
| title_short | Study on the driving mechanism of spatio-temporal non-stationarity of vegetation dynamics in the Taihangshan-Yanshan Region |
| title_sort | study on the driving mechanism of spatio temporal non stationarity of vegetation dynamics in the taihangshan yanshan region |
| topic | Kernel Normalised Vegetation Index (kNDVI) Spatio-temporal non-stationarity Optimal Parameter Geodetector Detectors (OPGD) Multi-scale Geographically Weighted Regression (MGWR) Taihangshan-Yanshan Region |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X25000135 |
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