Abstract

The distribution and dynamic changes in impervious surface areas (ISAs) are crucial to understanding urbanization and its impact on urban heat islands, earth surface energy balance, hydrological cycles, and biodiversity. Remotely sensed data play an essential role in ISA mapping, and numerous methods have been developed and successfully applied for ISA extraction. However, the heterogeneity of ISA spectra and the high similarity of the spectra between ISA and soil have not been effectively addressed. In this study, we selected data from the US Geological Survey (USGS) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) spectral libraries as samples and used blue and near-infrared bands as characteristic bands based on spectral analysis to propose a novel index, the perpendicular impervious surface index (PISI). Landsat 8 operational land imager data in four provincial capital cities of China (Wuhan, Shenyang, Guangzhou, and Xining) were selected as test data to examine the performance of the proposed PISI in four different environments. Threshold analysis results show that there is a significant positive correlation between PISI and the proportion of ISA, and threshold can be adjusted according to different needs with different accuracy. Furthermore, comparative analyses, which involved separability analysis and extraction precision analysis, were conducted among PISI, biophysical composition index (BCI), and normalized difference built-up index (NDBI). Results indicate that PISI is more accurate and has better separability for ISA and soil as well as ISA and vegetation in the ISA extraction than the BCI and NDBI under different conditions. The accuracy of PISI in the four cities is 94.13%, 96.50%, 89.51%, and 93.46% respectively, while BCI and NDBI showed accuracy of 77.53%, 93.49%, 78.02%, and 84.03% and 58.25%, 57.53%, 77.77%, and 64.83%, respectively. In general, the proposed PISI is a convenient index to extract ISA with higher accuracy and better separability for ISA and soil as well as ISA and vegetation. Meanwhile, as PISI only uses blue and near-infrared bands, it can be used in a wider variety of remote sensing images.

Highlights

  • Impervious surface areas (ISAs) have been experiencing dramatic expansion accompanied by rapid urbanization worldwide [1]

  • Remote sensing has been widely used for ISA mapping and dynamics monitoring at multiple spatial resolutions with different satellite data [11,12,13,14]

  • In this paper, based on the analysis of samples selected from US Geological Survey (USGS) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) spectral libraries, we propose a novel index using blue and near-infrared bands, the perpendicular impervious surface index (PISI)

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Summary

Introduction

Impervious surface areas (ISAs) have been experiencing dramatic expansion accompanied by rapid urbanization worldwide [1]. ISA expansion significantly alters land surface characteristics in a transformation from a natural landscape to an anthropogenic landscape, which presents serious problems for urban environmental quality, such as aggravating the urban heat island effect [2,3,4,5,6,7], enhancing the speed and volume of urban runoff, with increased pressure for municipal drainage and flood control [8], and reducing groundwater recharge [9]. Timely and accurate monitoring of ISA dynamics is becoming urgent for the strategic planning of urban development and the projection of ISA environmental impacts [10]. The classification-based method has produced unsatisfactory results in many applications, given the spectral and textural complexity of ISA and the extensive existence of mixed pixels with various combinations of ISA and other land cover types [20]

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