Application of a normalized difference impervious index (NDII) to extract urban impervious surface features based on Landsat TM images

被引:63
作者
Wang, Zhaoqi [1 ]
Gang, Chencheng [1 ]
Li, Xueling [2 ]
Chen, Yizhao [1 ]
Li, Jianlong [1 ]
机构
[1] Nanjing Univ, Sch Life Sci, Nanjing 210008, Jiangsu, Peoples R China
[2] Univ Technol Sydney, Plant Funct Biol & Climate Change Cluster, Sydney, NSW 2007, Australia
基金
中国国家自然科学基金;
关键词
SPECTRAL MIXTURE ANALYSIS; OPEN WATER FEATURES; HEAT-ISLAND; SATELLITE PERSPECTIVE; VEGETATION ABUNDANCE; MULTISPECTRAL IMAGES; SPATIAL-RESOLUTION; BRAZILIAN AMAZON; THEMATIC MAPPER; URBANIZATION;
D O I
10.1080/01431161.2015.1007250
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
The ecological conditions of urban areas have been deteriorating in some aspects due to population growth and increasing expansion, with significant effects on human health. Impervious surface areas are an important indicator of urban ecological environmental change, therefore quickly and accurately estimating impervious surface areas is essential to monitoring the urban dynamics of change and human activities and their effects on urban environmental quality. Currently, few methods that are applied in estimating urban impervious surfaces are capable of providing results quickly and accurately. Accordingly, this study proposes a new index, named the normalized difference impervious index (NDII), based on Landsat TM images, which uses the visible (red, green, and blue) and thermal bands. The index was used to extract the impervious surface areas of Nanjing city, Jiangsu Province, China, and we assume that the average value of five times strict supervised classification is the true value of impervious surfaces. A combination of red and thermal bands extracted the impervious surfaces with a producer's accuracy of 86.9%, a user's accuracy of 84.6%, an overall accuracy of 91.4%, and a kappa coefficient of 0.8. The accuracy is 87.7% validated by high-resolution images. This method can rapidly extract urban impervious surface areas with promising accuracy.
引用
收藏
页码:1055 / 1069
页数:15
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