Please use this identifier to cite or link to this item: https://doi.org/10.1109/IGARSS.2010.5652027
Title: Mangrove detection from high resolution optical data
Authors: Christophe, E. 
Wong, C.M. 
Liew, S.C. 
Keywords: Classification
Detection
Feature selection
Mangroves
SVM
Issue Date: 2010
Citation: Christophe, E., Wong, C.M., Liew, S.C. (2010). Mangrove detection from high resolution optical data. International Geoscience and Remote Sensing Symposium (IGARSS) : 437-440. ScholarBank@NUS Repository. https://doi.org/10.1109/IGARSS.2010.5652027
Abstract: Mangroves are an important part of the ecosystem in tropical region. Unfortunately, they are also under intense ecological pressure from fishing, tourism or logging. As they are often in not easily accessible places and scattered over large areas, satellite observation is an ideal solution to monitor the mangrove evolution over the past few years. However, the mapping of mangrove from satellite images is a difficult task and mostly done manually. Here we propose a detection method based on support vector machine, exploring more than 100 features, provinding a good accurary, enabling the mangrove expert to focus on the most difficult areas. © 2010 IEEE.
Source Title: International Geoscience and Remote Sensing Symposium (IGARSS)
URI: http://scholarbank.nus.edu.sg/handle/10635/112879
ISBN: 9781424495658
DOI: 10.1109/IGARSS.2010.5652027
Appears in Collections:Staff Publications

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