Land cover discrimination at Brazilian Amazon using region based classifier and stochastic distance

Given the different nature of optical and radar data, it is reasonable the idea that each type of data can contribute in complementary ways for different applications. This paper aims at analyzing the potential joint usage of optical and Synthetic Aperture Radar (SAR) data for land use and land cove...

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Bibliographic Details
Main Authors: Silva, Wagner B., Pereira, Luciana O., Sant'Anna, Sidnei J. S., Freitas, Corina C., Guimaraes, Ricardo J. P. S., Frery, Alejandro C.
Format: Conference Proceeding
Language:English
Subjects:
Adaptive optics
Biomedical optical imaging
Brazilian Amazon
Fusion
Integrated optics
Laser radar
Optical imaging
Optical sensors
Region-based classification
Remote sensing
SAR
Stochastic Distances
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Summary:Given the different nature of optical and radar data, it is reasonable the idea that each type of data can contribute in complementary ways for different applications. This paper aims at analyzing the potential joint usage of optical and Synthetic Aperture Radar (SAR) data for land use and land cover classification in a region located in the Brazilian Amazon. To achieve this objective, we evaluated region-based classifications using separated and fused optical and SAR data. Data were images from the Landsat 5/TM sensor and amplitude multipolarized images from the ALOS/PALSAR sensor. The images were classified using a region-based classifier based on the Bhattacharyya distance between Gaussian distributions. The TM data alone is better for classify land cover classes with occurrence of trees or shrubs, while SAR data contribute to improve the classification results in low vegetated areas.
ISSN:2153-6996
2153-7003
DOI:10.1109/IGARSS.2011.6049821