Title :
A simple class-set based vegetation classification of a South Pacific volcanic island (Moorea Island, French Polynesia) using both AirSAR and MASTER data
Author :
Stoll, Benoît ; Capolsini, Patrick
Author_Institution :
Terre-Ocean Lab., French Polynesia Univ., Tahiti, French Polynesia
Abstract :
This paper addresses the vegetation mapping and land use of Opunohu Valley (Moorea Island, French Polynesia) using JPL-AirSAR and MASTER (MODIS/ASTER simulator) images. We first define an original set of classes based on the relative canopy-height of vegetation, out of a well-suited RGB SAR-composite image that visually discriminates our vegetation classes. An interesting "pineapple fields" class (an important economic resource in Moorea island) proves to discriminate particularly from the height-related "Low Vegetation" class. Two supervised maximum likelihood classification maps have been processed on both the AirSAR and the MASTER images, using aerial photographs as a ground truth training set. The vegetal species included in each class as well as the classification results are discussed. Comparison of the MASTER and AirSAR based classification results leads us to propose a fusion of AirSAR and MASTER classification maps keeping the best of both worlds in order to improve the overall accuracy of the AirSAR classification.
Keywords :
airborne radar; geophysical signal processing; image classification; radar imaging; remote sensing by radar; synthetic aperture radar; vegetation mapping; French Polynesia; JPL-AirSAR images; MASTER data; MODIS/ASTER simulator; Moorea Island; Opunohu Valley; RGB SAR-composite image; Society Archipelago; South Pacific volcanic island; aerial photographs; canopy height; class set based vegetation classification; image classification; land use; pineapple fields; supervised maximum likelihood classification; vegetal species; vegetation mapping; Cultural differences; Infrared imaging; L-band; Laboratories; Layout; MODIS; Multispectral imaging; Polarimetry; Radar imaging; Vegetation mapping;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004 IEEE International
Print_ISBN :
0-7803-8742-2
DOI :
10.1109/IGARSS.2004.1369854