Please use this identifier to cite or link to this item:
http://www.alice.cnptia.embrapa.br/alice/handle/doc/17039
Title: | Comparison of land-cover classification methods in the Brazilian Amazon Basin. |
Authors: | LU, D.![]() ![]() MAUSEL, P. ![]() ![]() BATISTELLA, M. ![]() ![]() MORAN, E. ![]() ![]() |
Affiliation: | 1-2 e 4: Indiana University; 3: Embrapa Monitoramento por Satélite. |
Date Issued: | 2004 |
Citation: | Photogrammetric Engineering & Remote Sensing, v. 70, n. 6, p. 723-731, jun. 2004. |
Description: | Four distinctly different classifiers were used to analyze multispectral data. Which of these classifiers is most suitable for a specific study area is not always clear. This paper provides a comparison of minimum-distance classifier (MDC), maximumlikelihood classifier (MLC), extraction and classification of homogeneous objects (ECHO), and decision-tree classifier based on linear spectral mixture analysis (DTC-LSMA). Each of the classifiers used both Landsat Thematic Mapper data and identical field-based training sample datasets in a western Brazilian Amazon study area. Seven land-cover classes? mature forest, advanced secondary succession, initial secondary succession, pasture lands, agricultural lands, bare lands, and water?were classified. Classification results indicate that the DTC-LSMA and ECHO classifiers were more accurate than were the MDC and MLC. The overall accuracy of the DTCLSMA approach was 86 percent with a 0.82 kappa coefficient and ECHO had an accuracy of 83 percent with a 0.79 kappa coefficient. The accuracy of the other classifiers ranged from 77 to 80 percent with kappa coefficients from 0.72 to 0.75. |
Thesagro: | Bacia Hidrográfica Floresta Tropical Úmida Satélite |
Keywords: | Mapeamento Amazonia brasileira Amazonas |
Type of Material: | Artigo de periódico |
Access: | openAccess |
Appears in Collections: | Artigo em periódico indexado (CNPM)![]() ![]() |