Tree species diversity is a key parameter to describe forest ecosystems. It is, for example,
important for issues such as wildlife habitat modeling and close-to-nature forest …

Since the publishing of the first edition of Classification Methods for Remotely Sensed Data
in 2001, the field of pattern recognition has expanded in many new directions that make use …

Total phosphorus (TP) is an important factor of eutrophication. The accurate monitoring of TP
concentration is conducive to the management of water environments. To improve the …

Hyperspectral images have considerable information content and are becoming common.
Analysis tools must keep up with the changing demands and opportunities posed by the …

This work proposes a new method to classify multi-spectral satellite images based on
multivariate adaptive regression splines (MARS) and compares this classification system …

This study evaluated the potential of an object-oriented approach to forest type classification
as well as volume and biomass estimation using small-footprint, multiple return lidar data …

Classification based on Fisher's linear discriminant analysis (FLDA) is challenging when the
number of variables largely exceeds the number of given samples. The original FLDA needs …

É de conhecimento geral que, em alguns casos, as classes são espectralmente muito
similares e que não é possível separá-las usando dados convencionais em baixa …

Loss and deterioration of habitats are major threats for Tetrao urogallus in central Europe,
where forests are highly fragmented and forest practices have distinctly changed during the …

Woodlands constitute the subsistence base of the majority of people in the Sudano-Sahelian
zone (SSZ). Trees and grasses provide key ecosystem goods and services, including soil …