Using the Geodetector Method to Characterize the Spatiotemporal Dynamics of Vegetation and Its Interaction with Environmental Factors in the Qinba Mountains, China
文献类型：期刊论文
| 作者 | Zhang, Shuhui4; Zhou, Yuke5; Yu, Yong1; Li, Feng3; Zhang, Ruixin2; Li, Wenlong4 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2022-11-01 |
| 卷号 | 14期号:22页码:20 |
| 关键词 | vegetation dynamic Geodetector remote sensing environmental factors spatial heterogeneity Google Earth Engine (GEE) Qinba Mountains |
| DOI | 10.3390/rs14225794 |
| 通讯作者 | Yu, Yong(yuyong@cnemc.cn) |
| 英文摘要 | Understanding the driving mechanisms of vegetation development is critical for maintaining terrestrial ecosystem function in mountain areas, especially under the background of climate change. The Qinba Mountains (QBM), a critical north-south transition zone in China, is an environmentally fragile area that is vulnerable to climate change. It is essential to characterize how its ecological environment has changed. Currently, such a characterization remains unclear in the spatiotemporal patterns of the nonlinear effects and interactions between environmental factors and vegetation changes in the QBM. Here, we utilized the Normalized Difference Vegetation Index (NDVI), obtained from Google Earth Engine (GEE) platform, as an indicator of terrestrial ecosystem conditions. Then, we measured the spatiotemporal heterogeneity for vegetation variation in the QBM from 2003 to 2018. Specifically, the Geodetector method, a new geographically statistical method without linear assumptions, was employed to detect the interaction between vegetation and environmental driving factors. The results indicated that there is a trend of a general increase in vegetation growth amplitude (the average NDVI increased from 0.810 to 0.858). The areas with an NDVI greater than 0.8 are mainly distributed in the Qinling Mountains and the Daba Mountains, which account for more than 76.39% of the QBM area. For the entire region, the global Moran's index of the NDVI is greater than 0.95, indicating that vegetation is highly concentrated in the spatial domain. The Geodetector identified that landform type was the primary factor in controlling vegetation changes, contributing 24.19% to the total variation, while the explanatory powers of the aridity index and the wetness index for vegetation changes were 22.49% and 21.47%, respectively. Furthermore, the interaction effects between any two factors outperformed the influence of a single environmental variable. The interaction between air temperature and the aridity index was the most significant element, contributing to 47.10% of the vegetation variation. These findings can not only improve our understanding in the interactive effects of environmental forces on vegetation change, but also be a valuable reference for ecosystem management in the QBM area, such as ecological conservation planning and the assessment of ecosystem functions. |
| WOS关键词 | RIVER-BASIN ; CLIMATE |
| 资助项目 | National Key Research and Development Program[2021xjkk0303] ; National Key Research and Development Program[2018YFB0505301] |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000887720200001 |
| 出版者 | MDPI |
| 资助机构 | National Key Research and Development Program |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/187519]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Yu, Yong |
| 作者单位 | 1.China Natl Environm Monitoring Ctr, State Environm Protect Key Lab Qual Control Envir, Beijing 100012, Peoples R China 2.China Univ Min & Technol, Coll Geosci & Surveying Engn, Beijing 100083, Peoples R China 3.Informat Ctr, Dept Nat Resources Sichuan Prov, Chengdu 610072, Peoples R China 4.Lanzhou Univ, Coll Pastoral Agr Sci & Technol, State Key Lab Herbage Improvement & Grassland Agr, Lanzhou 730020, Peoples R China 5.Chinese Acad Sci, Inst Geog & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Shuhui,Zhou, Yuke,Yu, Yong,et al. Using the Geodetector Method to Characterize the Spatiotemporal Dynamics of Vegetation and Its Interaction with Environmental Factors in the Qinba Mountains, China[J]. REMOTE SENSING,2022,14(22):20. |
| APA | Zhang, Shuhui,Zhou, Yuke,Yu, Yong,Li, Feng,Zhang, Ruixin,&Li, Wenlong.(2022).Using the Geodetector Method to Characterize the Spatiotemporal Dynamics of Vegetation and Its Interaction with Environmental Factors in the Qinba Mountains, China.REMOTE SENSING,14(22),20. |
| MLA | Zhang, Shuhui,et al."Using the Geodetector Method to Characterize the Spatiotemporal Dynamics of Vegetation and Its Interaction with Environmental Factors in the Qinba Mountains, China".REMOTE SENSING 14.22(2022):20. |
入库方式： OAI收割
来源：地理科学与资源研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。