The use of WorldView-2 satellite imagery to model urban drainage system with low impact development (LID) Techniques. Issue 1 (2nd January 2016)

• Record Type: Journal Article
• Authors: Khin, Moh Moh Lin; Shaker, Ahmed; Joksimovic, Darko; Yan, Wai Yeung
• Is Part Of: Geocarto international. Volume 31:Issue 1(2016)
• Page Start: 92
• Page End: 108
• Publication Date: 2016-01-02
• Subjects: hydrologic modelling -- low-impact development -- object-based classification -- urban drainage -- WorldView-2; Remote sensing -- Periodicals; Geographic information systems -- Periodicals; Geology -- Periodicals; Cartography -- Periodicals; 621.3678
• DOI: 10.1080/10106049.2015.1041561
• Languages: English
• ISSNs: 1010-6049

Abstract

Abstract : Within a wide range of best management practices for stormwater management in urban areas, there has been an increasing interest in source control measures. Source controls such as low-impact development (LID) techniques are potentially attractive as retrofit options for older developed areas that lack available land to implement conventional measures such as stormwater management ponds. Hence, distributed urban drainage models requiring detailed representation of developed drainage areas should be developed to accurately estimate the benefits that LIDs may provide. This study (1) presents a two-stage classification process on a high-resolution WorldView-2 image, and (2) demonstrates how to use the extracted land cover information in the subsequent hydrologic modelling and assessment of different LIDs' performance. The proposed two-stage classification method achieved an overall accuracy of 80.6%, whereas a traditional pixel-based achieved 68.4% in classifying the same urban area into six land cover classes. From the classification results, the hydrologic properties of micro-subcatchments were imported in the United States Environmental Protection Agency Storm Water Management Model to assess the performance of LIDs. A reduction of run-off volume 18.2% and 37.1% was found with the implementation of porous pavement and bioretention, respectively, in a typical low-rise residential area located in the city of San Clemente, California, US. The study demonstrates the use of high-resolution remote sensing image to aid in evaluating LID retrofit options, and thus benefits in situations where detailed drainage area information is not available.