Land-cover classification in the Brazilian Amazon with the integration of Landsat ETM + and Radarsat data.

Land-cover classification with remotely sensed data in moist tropical regions in a challenge due to the complex biophysical conditions. This paper explores techniques to improve land-cover classification accuracy through a comparative analysis of different combinations of spectral signatures and textures from Landsat Enhanced Thematic Mapper Plus (ETM +) and Radarsat data. A wavelet-merging technique was used to integrate Landsat ETM + multispectral and panchromatic data or Radarsat data. Grey-level co-occurrence matrix (GLCM) textures based on Landsat ETM + panchromatic of Radarsat data and different sizes of moving windows were examined. A maximum-likelihood classifier was used to implement image classification for different combinations. This research indicates the important role of textures in improving land-cover classification accuracies in Amazonian environments. ...

Bibliographic Details

Main Authors:	LU, D., BATISTELLA, M., MORAN, E.
Other Authors:	D. Lu ( Indiana University); Batistella, M. (Embrapa Monitoramento por Satélite); E. Moran ( Indiana University Bloomington Indiana USA).
Format:	Artigo de periódico biblioteca
Language:	English eng
Published:	2008-04-22
Subjects:	Amazon, Landsat ETM+, land-cover,
Online Access:	http://www.alice.cnptia.embrapa.br/alice/handle/doc/17678
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