| Title | Urban land use mapping using high resolution SAR data based on density analysis and contextual information |
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| Author | Chen, Z; Zhang, Y; Guindon, B; Esch, T; Roth, A; Shang, J |
| Source | Canadian Journal of Remote Sensing vol. 38, no. 6, 2012 p. 738-749, https://doi.org/10.5589/m13-002  Open Access |
| Image |  |
| Year | 2012 |
| Alt Series | Earth Sciences Sector, Contribution Series 20120394 |
| Publisher | Informa UK Limited |
| Document | serial |
| Lang. | English |
| Media | paper; on-line; digital |
| File format | pdf |
| Subjects | geophysics; remote sensing; mapping techniques; computer mapping; satellite imagery; land use; SAR |
| Illustrations | tables; flow charts; aerial photographs; satellite images |
| Program | Remote Sensing Science |
| Released | 2014 06 04 |
| Abstract | This paper presents a procedure for urban land use interpretation from a single high-resolution synthetic aperture radar (SAR) image. The approach involves two semi-automatic steps: urban extent
delineation and urban land use mapping. In the first step, two general classes (urban and nonurban) are mapped using an existing method that involves analysis of speckle characteristics and intensity information. In the second step, more detailed
urban land use classification is undertaken based on analysis of regional radar backscatter patterns in terms of density of dark linear features, density of bright features, and urban contextual information. Density analysis was conducted at three
levels: individual building\'02road, urban block, and suburban commercial\'02industrial. Contextual information, including density, building size, and distance between buildings and parking places, was used to quantify urban morphological patterns.
Tests were conducted for mapping Ottawa, Canada, using five Radarsat-2 images of different incidence angles and three TerraSAR-X images of the same incidence angles but different dates. The results show that the proposed method could be used to map
five urban land uses including low-density residential, commercial\'02industrial, high-density urban, open land, and nonurban with accuracies in the range from 74% to 82%. |
| GEOSCAN ID | 292218 |
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