Title | Optimization of the Application of the Touzi Decomposition for Wetland Classification Using Polarimetric Radarsat-2 |
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Author | Gosselin, G; Touzi, R; Bhattacharya, A |
Source | 33rd Canadian Symposium on Remote Sensing, abstracts; by Canadian Symposium on Remote Sensing; 2012 p. 20 Open Access |
Links | Online - En ligne
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Links | Abstracts (PDF, 1.22 MB)
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Year | 2012 |
Alt Series | Earth Sciences Sector, Contribution Series 20140076 |
Meeting | 33rd Canadian Symposium on Remote Sensing; Ottawa; CA; June 11-14, 2012 |
Document | book |
Lang. | English |
Media | on-line; digital |
File format | pdf |
Subjects | geophysics; remote sensing; satellite imagery |
Program | Remote Sensing Science |
Released | 2012 01 01 |
Abstract | Canada's population is highly urbanized and its growth is reflected in rapid land use/ land cover around major cities. These factors highlight the need for frequent revisions of those topographic maps
containing significant urban attribute content (i.e. approximately 1500 1:50,000 mapsheets). To address this need, a 'hybrid', high throughput image processing system has been developed that utilizes moderate resolution SPOT imagery as its primary
data source. This paper describes the elements of the system used to map urban 'tint', i.e. those built-up areas (typically residential areas) characterized by structures too small to be represented as discrete map entities. A data-driven approach is
employed that exploits spectral indices to reduce data dimensionality and facilitate automation. Full scene interpretation can be completed in approximately 2-3 minutes on low-cost desktop computers while seamless large area mapping can be achieved
using classification compositing processing. Two major products have been generated (spanning theTorontotoWindsorandOttawatoMontrealcorridors) and assessed for consistency with map results generated with traditional labour-intensive means (i.e.
visual interpretation of aerial photography). Our results exhibit both high levels of agreement (>85%) with tint information on currently available maps and consistent results over a broad range of processing parameter values. Finally, it is argued
that the automated techniques described here have applicability in international urban mapping initiatives and the methodology can be applied to the mapping of natural features such as water bodies and forests. |
GEOSCAN ID | 294583 |
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