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| Lu,Dengsheng; Batistella,Mateus; Li,Guiying; Moran,Emilio; Hetrick,Scott; Freitas,Corina da Costa; Dutra,Luciano Vieira; Sant'Anna,Sidnei João Siqueira. |
| Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation‑based method are valuable ways to improve land use/cover... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Data fusion; Multiple sensor data; Nonparametric classifiers; Texture. |
| Ano: 2012 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2012000900004 |
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