Comparisons Of Impervious Surface Mapping Using Multiple Indices From Tm, Etm Plus And Oli-Tirs

Spectral built-up indices are considered promising to map impervious surface area (ISA) distribution at regional and global scales due to their easy implementation, parameter-free and convenience in practical applications. The objective of this study is to explore and compare the potential of different impervious surface indices for mapping urban area from Landsat imagery. By sharpening a thermal-band image and integrating it in a current index, a modified normalized difference impervious surface index (MNDISI) is proposed. Additionally, an automatic Gaussian-based threshold selection method is proposed to identify the optimal MNDISI threshold for separating impervious surface from background features. To evaluate the effectiveness of MNDISI, comparison analysis is conducted between MNDISI and other built-up indices using Landsat TM/ETM+/OLI-TIRS imagery acquired in the four different seasons. With reduced uncertainties from automatic threshold selection, the MNDISI has highest performance of ISA mapping with an overall accuracy of 87% and an overall Kappa coefficient of 0.74. This study reveals that the proposed MNDISI with automatic threshold selection is an effective index for impervious surface extraction, which could be applied for rapid and automatic ISA mapping at regional and global scales.