基于Google Earth Engine和遥感生态指数的拜泉县生态变化分析

Analysis of Ecological Changes in Baiquan County Based on Google Earth Engine and Remote Sensing Ecological Index

摘要: 随着现代城市化进程的加速，生态环境退化问题愈发突出。城市的快速发展与生态环境的变化密切相关，而生态环境质量的动态变化对区域的可持续发展有着极为重要的影响。遥感生态指数(Remote Sensing Ecological Index, RSEI)作为一种综合考虑绿度、湿度、干度与热度四个生态因子的指标体系，已广泛应用于生态监测研究中。本文以黑龙江省拜泉县为研究区域，利用Google Earth Engine (GEE)云平台，选取1990年至2022年间七个代表年份的Landsat遥感影像数据，构建归一化植被指数(Normalized Difference Vegetation Index, NDVI)、湿度指标(WET)、干度指标(Normalized Difference Built-up and Soil Index, NDBSI)与地表温度(Land Surface Temperature, LST)四个生态分量指标，采用主成分分析法(Principal Component Analysis, PCA)综合构建RSEI，并分析其时空演变规律。研究结果表明，拜泉县生态环境质量在整体上呈现“先波动、后恢复、逐步趋稳”的演变趋势。1990~2000年，受农业扩张与人类活动增强影响，RSEI显著下降；2000年后，随着植被恢复与生态保护措施的推进，生态质量逐渐改善。主成分分析结果显示，第一主成分PC1贡献率均超过60%，平均为72.67%，NDVI和WET为正向因子，对生态环境质量提升作用显著；而NDBSI和LST为负向因子，是生态退化的主导因素。本研究不仅验证了RSEI在区域生态质量评价中的有效性，也为拜泉县生态环境管理和土地利用规划提供了科学依据与技术支持。

Abstract: With the acceleration of modern urbanization, the problem of ecological environment degradation is becoming more and more prominent. The rapid development of the city is closely related to the change of the ecological environment, and the dynamic change of the ecological environment quality has a very important influence on the sustainable development of the region. As an indicator system that comprehensively considers four ecological factors of greenness, humidity, dryness and heat, Remote Sensing Ecological Index (RSEI) has been widely used in ecological monitoring research. This paper takes Baiquan County of Heilongjiang Province as the research area and uses Google Earth Engine (GEE) cloud platform to select Landsat remote sensing image data of seven representative years from 1990 to 2022. Four ecological component indexes of Normalized Difference Vegetation Index (NDVI), Humidity Index (WET), Normalized Difference Built-up and Soil Index (NDBSI) and Land Surface Temperature (LST) were constructed. Principal Component Analysis (PCA) was used to comprehensively construct RSEI and analyze its temporal and spatial evolution. The results show that the ecological environment quality of Baiquan County shows an evolution trend of “first fluctuation, then recovery, and gradually stabilizing” on the whole. From 1990 to 2000, RSEI decreased significantly due to the expansion of agriculture and the enhancement of human activities. After 2000, with the advancement of vegetation restoration and ecological protection measures, the ecological quality has gradually improved. The results of principal component analysis showed that the contribution rate of the first principal component PC1 was more than 60%, with an average of 72.67%. NDVI and WET were positive factors that had a significant effect on the improvement of ecological environment quality. NDBSI and LST are negative factors, which are the dominant factors of ecological degradation. This study not only verifies the effectiveness of RSEI in regional ecological quality evaluation, but also provides a scientific basis and technical support for ecological environment management and land use planning in Baiquan County.