长白山地区遥感生态指数时空变化及其气候响应

利用Google Earth Engine(GEE)云平台，在原有遥感生态指数（RSEI）基础上，选用增强型植被指数（EVI）代替原绿度指标中的NDVI，构建并计算2001—2020年长白山地区植被生长季RSEI，采用回归分析、波动分析、Hurst指数等方法，分析长白山地区RSEI时空变化特征并探讨其气候影响因素。研究表明：（1）2001—2020年长白山地区RSEI波动缓慢上升，生态环境质量整体呈上升趋势。RSEI多年均值空间分布具有明显的分异性，长白山保护开发区生态环境质量较好，通化市、白山市大部较差。（2）近20年长白山地区RSEI稳定性较差，生态环境质量较脆弱。未来生态环境趋势总体向好，但局部地区仍存在持续恶化态势。（3）长白山地区RSEI主要受降水影响较大，与降水呈显著正相关，与气温相关性不强。

Temporal and Spatial Variation of Remote Sensing Ecological Index and Its Climate Response in Changbai Mountains Regin

Based on the original remote sensing ecological index (RSEI), we used the Google Earth Engine (GEE) cloud platform, and selected the enhanced vegetation index (EVI) to replace the NDVI in the original greenness index to construct and calculate the RSEI of the vegetation growing season in Changbai mountains region from 2001 to 2020. We used regression analysis, fluctuation analysis, Hurst index and other methods to analyze the temporal and spatial variation characteristics of RSEI in Changbai mountains region and explored its climatic influencing factors. The research shows that: (1) From 2001 to 2020, the RSEI in Changbai mountains region rose slowly in the fluctuation, and the overall ecological environment quality showed an upward trend. The spatial distribution of RSEI average values for many years has obvious differentiation. The quality of the ecological environment in Changbai Mountain Protection and development zone was relatively good, and most of Tonghua and Baishan cities were poor. (2) In the past 20 years, the stability of RSEI in Changbai mountains region was relatively poor, and the quality of ecological environment was relatively fragile. In the future, the trend of ecological environment will be generally positive, but there will be still a continuous deterioration trend in some areas. (3) The RSEI in Changbai mountains region is mainly affected by precipitation, showing a significant positive correlation with precipitation, but not strong correlation with temperature.