Title : 
Mangrove detection from high resolution optical data
         
        
            Author : 
Christophe, Emmanuel ; Wong, Choong Min ; Liew, Soo Chin
         
        
            Author_Institution : 
Centre for Remote Imaging, Sensing & Process., Nat. Univ. of Singapore, Singapore, Singapore
         
        
        
        
        
        
            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, providing a good accurary, enabling the mangrove expert to focus on the most difficult areas.
         
        
            Keywords : 
environmental monitoring (geophysics); geophysical signal processing; hydrological techniques; support vector machines; vegetation; vegetation mapping; detection method; ecosystem; high resolution optical data; mangrove detection; mangrove evolution monitoring; mangrove mapping; satellite observation; support vector machine; tropical region; Asia; Feature extraction; Image resolution; Indexes; Satellites; Support vector machines; Vegetation mapping; SVM; classification; detection; feature selection; mangroves;
         
        
        
        
            Conference_Titel : 
Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International
         
        
            Conference_Location : 
Honolulu, HI
         
        
        
            Print_ISBN : 
978-1-4244-9565-8
         
        
            Electronic_ISBN : 
2153-6996
         
        
        
            DOI : 
10.1109/IGARSS.2010.5652027