Rice crop mapping using radar imagery: comparison of classification accuracy of different Envisat ASAR modes and classifiers
Paper
Paper/Presentation Title | Rice crop mapping using radar imagery: comparison of classification accuracy of different Envisat ASAR modes and classifiers |
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Presentation Type | Paper |
Authors | Lam-Dao, Nguyen (Author), Apan, Armando (Author), Le-Toan, Thuy (Author), Bouvet, Alexandre (Author), Young, Frank (Author) and Le-Van, Trung (Author) |
Editors | Ostendorf, Bertram, Baldock, Penny, Bruce, David, Burdett, Michael and Corcoran, Paul |
Journal or Proceedings Title | Proceedings of the 2009 Surveying and Spatial Sciences Institute Biennial International Conference (SSC 2009) |
Number of Pages | 13 |
Year | 2009 |
Place of Publication | Adelaide, Australia |
ISBN | 9780958136686 |
Web Address (URL) of Paper | http://www.ssc2009.com/ |
Conference/Event | 2009 Surveying and Spatial Sciences Institute Biennial International Conference (SSC 2009): Spatial Diversity |
Spatial Sciences Institute Biennial Conference (SSC) | |
Event Details | 2009 Surveying and Spatial Sciences Institute Biennial International Conference (SSC 2009): Spatial Diversity Parent Surveying and Spatial Sciences Institute Biennial International Conference Event Date 28 Sep 2009 to end of 02 Oct 2009 Event Location Adelaide, Australia |
Event Details | Spatial Sciences Institute Biennial Conference (SSC) |
Abstract | Food security has become a key global issue due to rapid population growth in many parts of Asia, as well as the effect of climate change. For this reason, there is a need to develop spatio-temporal monitoring system that can accurately assess rice area planted. In the Mekong Delta, Vietnam, the changes in cultural practices have been gradually adopted in the last ten years. These changes have impacts on remote sensing methods developed for rice monitoring, particularly on the accuracy of the resulting classified image. Thus, the aim of this study was to compare the accuracy obtained by different Envisat ASAR modes (APP and WS) and the classifiers used. Using Envisat ASAR APP data, the study showed that the radar backscattering behaviour is much different from that of the traditional rice previously reported in the literature, due to changes brought by modern cultural practices. The polarisation ratio (HH, VV) of rice fields at a single date during a long period of the rice season could be used to derive the rice/non-rice mapping algorithm. The results of this thresholding algorithm achieved higher and consistent accuracies between seasons and districts (i.e. maximum accuracy of 99% and 98%, respectively) across the study site when compared to other classifiers, such as the minimum-distance-to-means, maximum likelihood, spectral angle mapper (SAM), ISODATA and K-Means. Regarding the ASAR modes of data acquisition, the ASAR APP data yielded higher and consistent classification accuracy. However, the ASAR WS product proved to be a potential data for rice mapping at regional scale. |
Keywords | food security; spatio-temporal monitoring; rice crop mapping; rice; monitoring; rice monitoring; radar imagery; classification accuracy; Envisat ASAR modes; classifiers; Vietnam |
ANZSRC Field of Research 2020 | 469999. Other information and computing sciences not elsewhere classified |
409902. Engineering instrumentation | |
401304. Photogrammetry and remote sensing | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Australian Centre for Sustainable Catchments |
Centre for the Study of the Biosphere from Space, France | |
GIS and Remote Sensing Research Centre, Vietnam |
https://research.usq.edu.au/item/9z989/rice-crop-mapping-using-radar-imagery-comparison-of-classification-accuracy-of-different-envisat-asar-modes-and-classifiers
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