Sub-pixel estimation of tree cover and bare surface densities using regression tree analysis

Carlos Augusto   Zangrando Toneli; Luis Marcelo   Tavares de Carvalho

Sub-pixel estimation of tree cover and bare surface densities using regression tree analysis

Autores

Carlos Augusto Zangrando Toneli

Luis Marcelo Tavares de Carvalho

Editor

Universidade Federal de Lavras

Descripción

Sub-pixel analysis is capable of generating continuous fi elds, 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 baresurface. The use of non-parametric and non-linear regression tree models presented satisfactory results to characterize wetland, deciduous and savanna patterns of forest formation.