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Quantifying sub-pixel urban impervious surface through fusion of optical and inSAR imagery

GIScience and Remote Sensing
By: , , , and 
https://doi.org/10.2747/1548-1603.46.2.161

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Abstract

In this study, we explored the potential to improve urban impervious surface modeling and mapping with the synergistic use of optical and Interferometric Synthetic Aperture Radar (InSAR) imagery. We used a Classification and Regression Tree (CART)-based approach to test the feasibility and accuracy of quantifying Impervious Surface Percentage (ISP) using four spectral bands of SPOT 5 high-resolution geometric (HRG) imagery and three parameters derived from the European Remote Sensing (ERS)-2 Single Look Complex (SLC) SAR image pair. Validated by an independent ISP reference dataset derived from the 33 cm-resolution digital aerial photographs, results show that the addition of InSAR data reduced the ISP modeling error rate from 15.5% to 12.9% and increased the correlation coefficient from 0.71 to 0.77. Spatially, the improvement is especially noted in areas of vacant land and bare ground, which were incorrectly mapped as urban impervious surfaces when using the optical remote sensing data. In addition, the accuracy of ISP prediction using InSAR images alone is only marginally less than that obtained by using SPOT imagery. The finding indicates the potential of using InSAR data for frequent monitoring of urban settings located in cloud-prone areas.

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Publication type Article
Publication Subtype Journal Article
Title Quantifying sub-pixel urban impervious surface through fusion of optical and inSAR imagery
Series title GIScience and Remote Sensing
DOI 10.2747/1548-1603.46.2.161
Volume 46
Issue 2
Year Published 2009
Language English
Publisher Taylor & Francis
Contributing office(s) Earth Resources Observation and Science (EROS) Center
Description 11 p.
First page 161
Last page 171
Country United States
State China
City Hong Kong
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