城市遥感生态指数的创建及其应用

城市生态与人类生活息息相关，快速、准确、客观地了解城市生态状况已成为生态领域的一个研究重点。基于遥感技术，提出一个完全基于遥感技术，以自然因子为主的遥感生态指数（RSEI）来对城市的生态状况进行快速监测与评价。该指数利用主成分分析技术集成了植被指数、湿度分量、地表温度和建筑指数等4个评价指标，它们分别代表了绿度、湿度、热度和干度等4大生态要素。通过在福州主城区的应用表明，RSEI指数可以定量地评价和对比城市的生态质量，方便地进行时空动态变化分析。由于所选的指标完全基于遥感信息，容易获得，且计算过程无需人工干预，因此结果客观可靠、可比性强。

A remote sensing urban ecological index and its application

Urban ecological status is closely related to the quality of human life. Timely, precisely and objectively understanding urban ecological status has become an increasing concern in the world. To meet this requirement, this paper develops a remote sensing based ecological index (RSEI) for the measure of urban ecology. As an index for the assessment of urban ecological status, the RSEI aims to integrate four important ecological indicators which are frequently used in evaluating urban ecology. These are greenness, wetness, dryness, and heat. The four indicators can be represented respectively by four remote sensing indices or components, which are the normalized difference vegetation index (NDVI), normalized difference built-up and soil index (NDBSI), wetness component of the tasseled cap transformation (Wet), and land surface temperature (LST). Instead of a simple addition or weighted addition of the four indicators, the principal component analysis (PCA) was utilized to compress the four indicators into one to construct the index for assessing overall urban ecological status. After careful comparison of the four principal components (PC1 to PC4) derived from the four indicators, the first principal component (PC1) was found to have integrated most of the information of the four indicators. This suggested that the PC1 can more effectively represent the four indicators than any of the other three components, i.e., PC2, PC3 and PC4. Accordingly, the new index, RSEI, was formed using the PC1 derived from the four factors and thus can measure greenness, wetness, dryness and heat of an urban ecosystem. Obviously, the RSEI is entirely based on remote sensing data and mostly on natural ecological factors. The calculation of the index is totally free of artificial interference, such as assigning a threshold value or weight value during the computing procedure. Therefore, the RSEI can assess the urban ecological status more objectively and easily. With the change detection technique, the proposed index can also be used to monitor the change of the ecological status of an urban area between different years. In practice, the index was successfully applied in a multi-temporal ecological status assessment of Fuzhou's urban area in Fujian province, southeastern China. Results show that Fuzhou has witnessed ecological degradation during the study period from 2001 to 2009. This is indicated by a decline of the RSEI value from 0.579 in 2001 to 0.529 in 2009. The fast expansion of the Fuzhou's urban area was attributed to the ecological degradation in the study duration, which caused the increase in NDBSI and LST and the decrease in NDVI and Wet. This in turn resulted in the decline of the RSEI as the index is the function of the four factors. Nevertheless, a RSEI-based change detection has revealed that the ecological quality of the urban center of Fuzhou was improved in spite of the overall ecological degradation in the urban area during the study years.