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A comparative study of landsat TM and SPOT HRG images of vegetation classification in the brazilian Amazon. Repositório Alice
LU, D.; BATISTELLA, M.; MIRANDA, E. E. de.
Complex forest structure and abundant tree species in the moist tropical regions often couse difficulties in classifying vegetation classes with remotely sensed data. This paper explores improvement in vegetation classification accuracies through a comparative study of different image combinations based on the integration of Landsat Thematic Mapper (TM) and SPOT High Resolution Geometric (HRG) instrument data, as well as the combination of spectral signatures and textures. A maximum likelihood classifier was used to classify the different image combinations into thematic maps. This research indicated that data fusion based on HBG multispectral and panchromatic data slightly improved vegetation classification accuracies: a 3.1 to 4.6 percent increase in the...
Tipo: Artigo em periódico indexado (ALICE) Palavras-chave: Comparative study; Landsat TM and SPOT HRG Images; Brazilian Amazon; Moist tropical regions; Machadinho d´Oeste.
Ano: 2008 URL: http://www.alice.cnptia.embrapa.br/handle/doc/31577
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