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Improving distributed runoff prediction in urbanized catchments with remote sensing based estimates of impervious surface cover

(2008) SENSORS. 8(2). p.910-932
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Abstract
The amount and intensity of runoff on catchment scale are strongly determined by the presence of impervious land-cover types, which are the predominant cover types in urbanized areas. This paper examines the impact of different methods for estimating impervious surface cover on the prediction of peak discharges, as determined by a fully distributed rainfall-runoff model (WetSpa), for the upper part of the Woluwe River catchment in the southeastern part of Brussels. The study shows that detailed information on the spatial distribution of impervious surfaces, as obtained from remotely sensed data, produces substantially different estimates of peak discharges than traditional approaches based 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 useful alternative for more expensive high-resolution mapping for rainfall-runoff modelling at catchment scale.
Keywords
LAND-COVER, MODEL, GIS, INFORMATION, IMAGERY, SYSTEM, distributed runoff modeling, impervious surfaces, remote sensing, sub-pixel classification

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Citation

Please use this url to cite or link to this publication:

MLA
Chormanski, Jaroslaw, et al. “Improving Distributed Runoff Prediction in Urbanized Catchments with Remote Sensing Based Estimates of Impervious Surface Cover.” SENSORS, vol. 8, no. 2, 2008, pp. 910–32.
APA
Chormanski, J., Van de Voorde, T., De Roeck, T., Batelaan, O., & Canters, F. (2008). Improving distributed runoff prediction in urbanized catchments with remote sensing based estimates of impervious surface cover. SENSORS, 8(2), 910–932.
Chicago author-date
Chormanski, Jaroslaw, Tim Van de Voorde, Tim De Roeck, Okke Batelaan, and Frank Canters. 2008. “Improving Distributed Runoff Prediction in Urbanized Catchments with Remote Sensing Based Estimates of Impervious Surface Cover.” SENSORS 8 (2): 910–32.
Chicago author-date (all authors)
Chormanski, Jaroslaw, Tim Van de Voorde, Tim De Roeck, Okke Batelaan, and Frank Canters. 2008. “Improving Distributed Runoff Prediction in Urbanized Catchments with Remote Sensing Based Estimates of Impervious Surface Cover.” SENSORS 8 (2): 910–932.
Vancouver
1.
Chormanski J, Van de Voorde T, De Roeck T, Batelaan O, Canters F. Improving distributed runoff prediction in urbanized catchments with remote sensing based estimates of impervious surface cover. SENSORS. 2008;8(2):910–32.
IEEE
[1]
J. Chormanski, T. Van de Voorde, T. De Roeck, O. Batelaan, and F. Canters, “Improving distributed runoff prediction in urbanized catchments with remote sensing based estimates of impervious surface cover,” SENSORS, vol. 8, no. 2, pp. 910–932, 2008.
@article{8645242,
  abstract     = {The amount and intensity of runoff on catchment scale are strongly determined by the presence of impervious land-cover types, which are the predominant cover types in urbanized areas. This paper examines the impact of different methods for estimating impervious surface cover on the prediction of peak discharges, as determined by a fully distributed rainfall-runoff model (WetSpa), for the upper part of the Woluwe River catchment in the southeastern part of Brussels. The study shows that detailed information on the spatial distribution of impervious surfaces, as obtained from remotely sensed data, produces substantially different estimates of peak discharges than traditional approaches based 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 useful alternative for more expensive high-resolution mapping for rainfall-runoff modelling at catchment scale.},
  author       = {Chormanski, Jaroslaw and Van de Voorde, Tim and De Roeck, Tim and Batelaan, Okke and Canters, Frank},
  issn         = {1424-8220},
  journal      = {SENSORS},
  keywords     = {LAND-COVER,MODEL,GIS,INFORMATION,IMAGERY,SYSTEM,distributed runoff modeling,impervious surfaces,remote sensing,sub-pixel classification},
  language     = {eng},
  number       = {2},
  pages        = {910--932},
  title        = {Improving distributed runoff prediction in urbanized catchments with remote sensing based estimates of impervious surface cover},
  url          = {http://dx.doi.org/10.3390/s8020910},
  volume       = {8},
  year         = {2008},
}

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