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Impervious surface area (ISA) is an important parameter for many studies such as urban climate, urban environmental change, and air pollution; however, mapping ISA at the regional or global scale is still challenging due to the complexity of impervious surface features. The Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) data have been used for ISA mapping, but high uncertainty existed due to mixed-pixel and data-saturation problems. This paper presents a new index called normalized impervious surface index (NISI), which is an integration of DMSP-OLS and Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data, in order to reduce these problems. Meanwhile, this newly developed index is compared with previously used indices--Human Settlement Index (HSI) and Vegetation Adjusted Nighttime light Urban Index (VANUI)--in ISA mapping performance. We selected China as an example to map fractional ISA distribution through a support vector regression approach based on the relationship between the index and Landsat-derived ISA data. The results indicate that the proposed NISI provided better ISA estimation accuracy than HSI and VANUI, especially when the fractional ISA in a pixel is relatively large (i.e., >0.6) or very small (i.e., <0.2). This approach can be used to rapidly update ISA datasets at regional and global scales. [ABSTRACT FROM AUTHOR]

Analysis of urban distribution and its expansion using remote sensing data has received increasing attention in the past three decades, but little research has examined spatial patterns of urban distribution and expansion with buffer zones in different directions. This research selected Hangzhou metropolis as a case study to analyze spatial patterns and dynamic changes based on time-series urban impervious surface area (ISA) datasets. ISA was developed from Landsat imagery between 1991 and 2014 using a hybrid approach consisting of linear spectral mixture analysis, decision tree classifiers, and post-processing. The spatial patterns of ISA distribution and its dynamic changes in eight directions--east, southeast, south, southwest, west, northwest, north, and northeast--at the temporal scale were analyzed with a buffer zone-based approach. This research indicated that ISA can be extracted from Landsat imagery with both producer and user accuracies of over 90%. ISA in Hangzhou metropolis increased from 146 km² in 1991 to 868 km² in 2014. Annual ISA growth rates were between 15.6 km² and 48.8 km² with the lowest growth rate in 1994-2000 and the highest growth rate in 2005-2010. Urban ISA increase before 2000 was mainly due to infilling within the urban landscape, and, after 2005, due to urban expansion in the urban-rural interfaces. Urban expansion in this study area has different characteristics in various directions that are influenced by topographic factors and urban development policies. [ABSTRACT FROM AUTHOR]