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(Reference retrieved automatically from SciELO through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Comparative analysis of digital classifiers of Landsat-8 images for thematic mapping procedures

Full text
Author(s):
Danilo Francisco Trovo Garofalo [1] ; Cassiano Gustavo Messias [2] ; Veraldo Liesenberg [3] ; Édson Luis Bolfe [4] ; Marcos César Ferreira [5]
Total Authors: 5
Affiliation:
[1] Universidade Estadual de Campinas - Brasil
[2] Universidade Estadual de Campinas - Brasil
[3] Universidade do Estado de Santa Catarina - Brasil
[4] Embrapa Monitoramento por Satélite - Brasil
[5] Universidade Estadual de Campinas - Brasil
Total Affiliations: 5
Document type: Journal article
Source: Pesquisa Agropecuária Brasileira; v. 50, n. 7, p. 593-604, 2015-07-00.
Abstract

Abstract: The objective of this work was to evaluate the performance of SVM and K-NN digital classifiers for the object-based classification on Landsat-8 images, applied to mapping of land use and land cover of Alta Bacia do Rio Piracicaba-Jaguari, in the state of Minas Gerais, Brazil. The pre-processing step consisted of using radiometric conversion and atmospheric correction. Then the multispectral bands (30 m) were merged with the panchromatic band (15 m). Based on RGP compositions and field inspection, 15 land-use and land-cover classes were defined. For edge segmentation, the bounds were set to 10 and 60 for segmentation configuring and merging in the ENVI software. Classification was done using SVM and K-NN. Both classifiers showed high values for the Kappa index (k): 0.92 for SVM and 0.86 for K-NN, significantly different from each other at 95% probability. A major improvement was observed for SVM by the correct classification of different forest types. The object-based classification is largely applied on high-resolution spatial images; however, the results of the present work show the robustness of the method also for medium-resolution spatial images. (AU)

FAPESP's process: 13/05081-9 - Characterizing secondary forest stages in different tropical rain forest environments under the recent REDD+ protocols: an attempt with multiple sources of remote sensing data
Grantee:Veraldo Liesenberg
Support Opportunities: Scholarships in Brazil - Post-Doctoral
FAPESP's process: 13/22185-2 - INFLUENCE OF GEOSYSTEMS SPATIAL STRUCTURE ON THE REGIONALIZATION OF THE WATER QUALITY PARAMETERS IN PIRACICABA- JAGUARI UPPER BASIN
Grantee:Danilo Francisco Trovo Garofalo
Support Opportunities: Scholarships in Brazil - Doctorate