基于遥感的广州市城市绿地生态服务功能评价

利用TM卫星影像数据和野外观测数据,运用遥感定量反演模型和知识,提取影响广州市城市绿地生态服务功能的地表参数,如叶面积指数、植被指数、土壤水、地表反照率、地表温度等,然后利用神经网络技术实现对单一因子的城市绿地生态服务功能的评价与分级;在此基础上,利用模糊聚类法对广州市城市绿地生态服务功能进行综合评价。结果表明:广州市城市中心绿地生态服务功能偏弱;绿地在各区分布差异较大,空间布局不够合理。生态服务功能一级的城市绿地面积为2.1km2,仅占研究区域总面积的0.4%,生态服务功能二级、三级和四级的绿地面积占研究区域总面积的比例分别为2.4%、5.0%和2.9%。

Evaluation on ecological services of urban green space in Guangzhou City of South China based on remote sensing

Based on the TM image data and field observation data, and by using remote sensing quantitative inversion models, the land surface parameters affecting the ecological services of urban green space in Guangzhou City, e.g., leaf area index, vegetation index, soil moisture content, land surface albedo, and land surface temperature, were extracted. Each of these parameters was evaluated and graded by using Neural Network technology, and a multiple factor comprehensive evaluation of the urban ecosystem services in the City was conducted by fuzzy clustering. The results showed that the ecological services of the green space were weak. There was a great difference in the distribution of green space among each urban area, and the spatial arrangement was unreasonable. The area of the green space with the first degree ecological services was 2.1 km2, only accounted for 0.4% of the total, while the area of the green space with the second, third, and fourth degrees ecological services accounted for 2.4%, 5.0%, and 2.9%, respectively.