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In this paper, a novel decision support system (DSS) will be introduced, based on geospatial data analyses that we developed for the Hungarian forestry and agricultural sectors. This work was part of a larger research project, whose goal is to evaluate the impacts of projected climate change on forestry and agriculture and to identify potential adaptation options. The proposed DSS integrates various environmental coverages, including topography, vegetation, climate, soils, and hydrology. It also processes time-series data such as meteorological variables. The novelty of the system is its geospatial and geostatistical capability to map species spatial and climate space distribution and yield data using machine learning techniques (Maximum likelihood and Fuzzy logic). The DSS can generate projections, as well as sensitivity and risk assessments, and in this way, it can help to develop adaptation and mitigation strategies. The web-based implementation of the DSS allows decision-makers to directly interact with both current and projected geoinformation. The mechanics and the benefits of the DSS will be demonstrated on a Hungarian county where the system was first implemented as a prototype.
Czimber et al. (Tue,) studied this question.