An integrated Geographical Information System for the Vale do Alto Tâmega (GISVAT)
During the last fifteen years the landscape of the Vale do Alto Tâmega, a region in Northern Portugal, has been subjected to environmental pressure leading to a change in land cover from predominantly forest to a mixture of shrub and rock outcrops. Both natural (e.g. wild fires) and anthropogenic (e.g. timber harvesting) factors have contributed to this change. Practical management techniques are necessary to preserve and manage this important environmental resource. New technologies, such as Geographical Information Systems (GIS), the Global Positioning System (GPS) and Remote Sensing (RS) provide tools that can be used for forest management and wild fire protection. This thesis explores the suitability of these technologies for managing forests located in the Vale do Alto Tamega region. It focuses on the development of data sets and models that can be used to assess the susceptibility of forests to fire hazards. The GIS analysis reveals that more than half of the study area presents a high fire hazard and nearly a third of the Pinus pinaster stands were burnt between 1986 and 1995. The GIS results also show that much forest land is occupied by unsuitable species (e.g. coniferous instead of deciduous trees), which contribute to restricted timber production and a high fire hazard. GPS was used to survey both the location of sampling plots and to map the boundaries of burnt areas or of post-fire recover areas, associated with traditional forest mapping and measurement techniques. These data were then used to update GIS and to support satellite image classification. Remote sensing derived data were used for mapping, providing up¬to-date land cover maps, and to derive predictive relationships which can be used to estimate forest biophysical variables (e.g. Leaf Area Index or Biomass) that can be used by forest managers. The results of the research demonstrate that GIS, GPS and RS could be used together in forest management and protection, such as in the classification of the land cover in order to calculate fire hazard indices or in the analysis of forests dynamics.