title: Land use/cover classification in the Brazilian Amazon using satellite images.
abstract: 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 classification, especially for high spatial resolution images. Data fusion of multi-resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Of the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, has the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical-based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data.
authors.affiliation: Indiana University, Anthropological Center for Training and Research on Global Environmental Change, Student Building 331, 701 East Kirkwood Avenue, Bloomington, Indiana, 47405, USA. dlu@indiana.edu , ligu@indiana.edu , moran@indiana.edu , shetrick@indiana.edu.
authors.forename: Dengsheng
authors.initials: D
authors.lastname: Lu
authors.affiliation: Embrapa Monitoramento por Satélite, Avenida Soldado Passarinho, n⍛ 303, CEP 13070-115 Campinas, SP, Brazil. mb@cnpm.embrapa.br.
authors.forename: Mateus
authors.initials: M
authors.lastname: Batistella
authors.affiliation: Indiana University, Anthropological Center for Training and Research on Global Environmental Change, Student Building 331, 701 East Kirkwood Avenue, Bloomington, Indiana, 47405, USA. dlu@indiana.edu , ligu@indiana.edu , moran@indiana.edu , shetrick@indiana.edu.
authors.forename: Guiying
authors.initials: G
authors.lastname: Li
authors.affiliation: Indiana University, Anthropological Center for Training and Research on Global Environmental Change, Student Building 331, 701 East Kirkwood Avenue, Bloomington, Indiana, 47405, USA. dlu@indiana.edu , ligu@indiana.edu , moran@indiana.edu , shetrick@indiana.edu.
authors.forename: Emilio
authors.initials: E
authors.lastname: Moran
authors.affiliation: Indiana University, Anthropological Center for Training and Research on Global Environmental Change, Student Building 331, 701 East Kirkwood Avenue, Bloomington, Indiana, 47405, USA. dlu@indiana.edu , ligu@indiana.edu , moran@indiana.edu , shetrick@indiana.edu.
authors.forename: Scott
authors.initials: S
authors.lastname: Hetrick
authors.affiliation: Instituto Nacional de Pesquisas Espaciais, Avenida dos Astronautas, n⍛ 1.758, CEP 12245-010 São José dos Campos, SP, Brazil. corina@dpi.inpe.br , dutra@dpi.inpe.br , sidnei@dpi.inpe.br.
authors.forename: Corina da Costa
authors.initials: CD
authors.lastname: Freitas
authors.affiliation: Instituto Nacional de Pesquisas Espaciais, Avenida dos Astronautas, n⍛ 1.758, CEP 12245-010 São José dos Campos, SP, Brazil. corina@dpi.inpe.br , dutra@dpi.inpe.br , sidnei@dpi.inpe.br.
authors.forename: Luciano Vieira
authors.initials: LV
authors.lastname: Dutra
authors.affiliation: Instituto Nacional de Pesquisas Espaciais, Avenida dos Astronautas, n⍛ 1.758, CEP 12245-010 São José dos Campos, SP, Brazil. corina@dpi.inpe.br , dutra@dpi.inpe.br , sidnei@dpi.inpe.br.
authors.forename: Sidnei João Siqueira
authors.initials: SJ
authors.lastname: Sant'anna
keywords: data fusion; multiple sensor data; nonparametric classifiers; texture