Short Course 28: Application of Spatial Statistical Methods for Analysis and Modeling of Environmental Data

This short course presents and applies spatial analysis techniques in the context of remote sensing and geoprocessing studies for modeling environmental variables. Spatial analysis techniques describe existing patterns in spatial data, preferably establishing in a quantitative way the relationships between the different variables investigated, enabling the generation of new scenarios for monitoring, intervention and other purposes. The literature points to a diversity of spatial statistical methods, which are developed and applied to specific
situations. In this short course, some related methods will be presented for analyzing and modeling variables that are represented by pontual events, such as, for example, distribution of plant species, fire outbreaks, distribution of diseases, etc. Finally, specific methods will be presented for analyzing variables that are aggregated per unit area, such as, for example, vegetation cover rate, pollution index, deforestation rate, and others.