Use of impervious surface data obtained from remote sensing in distributed hydrological modelling of urban areas.

Frank Canters, Okke Batelaan, Tim Van De Voorde, J. Chormanski, Boud Verbeiren

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

While the increase of impervious surface cover in urbanised areas has a clear impact on urban hydrological processes, the relationship between flood conditions and urban development has been poorly studied. This chapter focuses on a case study demonstrating the impact of different remote sensing methods for characterizing the distribution of impervious surfaces on runoff estimation, and how this affects the assessment of peak discharges in an urbanized watershed in the Brussels Capital Region, Belgium. In the study use is made of WetSpa, a grid-based spatially distributed hydrological model adapted to incorporate information on the proportion of different types of land cover at grid cell level. The study shows that use of detailed information on the spatial distribution of impervious surfaces, as obtained from remotely sensed data, strongly affects local runoff estimation and has a clear impact on the modeling of peak discharges. Little difference, however, is observed between results obtained with impervious surface maps derived from high-resolution remote sensing data (Ikonos, 4m resolution) and sub-pixel estimates of impervious surface cover derived from satellite data matching the model's resolution (Landsat, 30m resolution).
Original languageEnglish
Title of host publicationUrban Remote Sensing: Monitoring, Synthesis and Modelling in the Urban Environment.
EditorsX. Yang
PublisherBlackwell-Wiley
Pages255-274
Number of pages408
ISBN (Print)978-0-470-74958-6
Publication statusPublished - 1 Apr 2011

Bibliographical note

X. Yang

Keywords

  • impervious surfaces
  • distributed hydrological modeling
  • remote sensing
  • sub-pixel classification

Fingerprint

Dive into the research topics of 'Use of impervious surface data obtained from remote sensing in distributed hydrological modelling of urban areas.'. Together they form a unique fingerprint.

Cite this