SUB-PIXEL ESTIMATION OF TREE COVER AND BARE SURFACE DENSITIES USING REGRESSION TREE ANALYSIS

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Carlos Augusto Zangrando Toneli Luís Marcelo Tavares de Carvalho

Abstract

Sub-pixel analysis is capable of generating continuous fields, which represent the spatial variability of certain thematic classes. The aim of this work was to develop numerical models to represent the variability of tree cover and bare surfaces within the study area. This research was conducted in the riparian buffer within a watershed of the São Francisco River in the North of Minas Gerais, Brazil. IKONOS and Landsat TM imagery were used with the GUIDE algorithm to construct the models. The results were two index images derived with regression trees for the entire study area, one representing tree cover and the other representing bare surface. The use of non-parametric and non-linear regression tree models presented satisfactory results to characterize wetland, deciduous and savanna patterns of forest formation. 

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How to Cite
TONELI, Carlos Augusto Zangrando; CARVALHO, Luís Marcelo Tavares de. SUB-PIXEL ESTIMATION OF TREE COVER AND BARE SURFACE DENSITIES USING REGRESSION TREE ANALYSIS. CERNE, [S.l.], v. 17, n. 3, p. 411-416, may 2015. ISSN 2317-6342. Available at: <http://cerne.ufla.br/site/index.php/CERNE/article/view/63>. Date accessed: 23 sep. 2019.
Keywords
Remote sensing, mapping, cerrado
Section
Article