Dynamic Analysis and Pattern Visualization of Forest Fires

This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

Forest management: different criteria – equal sustainability

From the forest management perspective, many definitions have been proposed for the concept of forest sustainability. Despite this apparent diversity, most of them converge on the same aspects. In this work we developed a comparative approach of two distinct forest management methodologies used in Europe, more precisely in Slovenia and in Portugal. Although in each case study differences in vegetation, climate and pedological characteristics are evident, we were able to show some peculiar aspects of both the Slovenian and the Portuguese examples. This study also dealt with the evolution of the term sustainability in the last decades and how it played an important role for forest management options.