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Sensors (Basel). 2008 Feb 15;8(2):910-932.

Improving Distributed Runoff Prediction in Urbanized Catchments with Remote Sensing based Estimates of Impervious Surface Cover.

Author information

1
Warsaw Agricultural University, Department of Hydraulic Structures and Environmental Restoration, Warsaw, Poland. j.chormanski@levis.sggw.pl.
2
Vrije Universiteit Brussel, Cartography and GIS Research Unit, Department of Geography, Brussels, Belgium. tvdvoord@vub.ac.be.
3
Vrije Universiteit Brussel, Cartography and GIS Research Unit, Department of Geography, Brussels, Belgium. tim.de.roeck@vub.ac.be.
4
Vrije Universiteit Brussel, Department of Hydrology and Hydraulic Engineering, Brussels, Belgium. batelaan@vub.ac.be.
5
Vrije Universiteit Brussel, Cartography and GIS Research Unit, Department of Geography, Brussels, Belgium. fcanters@vub.ac.be.

Abstract

The amount and intensity of runoff on catchment scale are strongly determinedby the presence of impervious land-cover types, which are the predominant cover types inurbanized areas. This paper examines the impact of different methods for estimatingimpervious surface cover on the prediction of peak discharges, as determined by a fullydistributed rainfall-runoff model (WetSpa), for the upper part of the Woluwe Rivercatchment in the southeastern part of Brussels. The study shows that detailed informationon the spatial distribution of impervious surfaces, as obtained from remotely sensed data,produces substantially different estimates of peak discharges than traditional approachesbased on expert judgment of average imperviousness for different types of urban land use.The study also demonstrates that sub-pixel estimation of imperviousness may be a usefulalternative for more expensive high-resolution mapping for rainfall-runoff modelling atcatchment scale.

KEYWORDS:

distributed runoff modeling; impervious surfaces; remote sensing; sub-pixel classification

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