The aims of the Laboratory of Geographic Information Systems and Remote Sensing serves are threefold:
Earth observation sensors provide data which can be used to map the materials on the Earth’s surface and generate maps depicting land cover types and their use. Employment of time series data allows for more accurate classification of land cover types and also enables the detection of changes occurring over short or longer periods of time. The methods employed for the extraction of such information at a range of scales and levels of spatial resolution, are constantly developed and refined, due to the advent of more elaborate sensors and the increasing demand for information by society.
Forest fires are a serious threat for the Mediterranean region and science can assist in the adoption of preventive and mitigation measures against such event. Study of forest fire characteristics under various conditions, using the facilities of the Fire Lab, provides useful information that can be incorporated into forest fire modeling. On the other hand, use of remote sensing data can provide information regarding fuel type mapping for planning of preventive measures and monitoring of fire spread for the performance of efficient mitigation actions.
The integration of GIS and remote sensing with ground base data for ecological mapping and predicting species distribution has become an important component of conservation planning. Habitat mapping and vegetation maps are essential in the formulation of environmental management plans. When digital imagery is combined with ancillary environmental factors over a period of time, more information can be derived regarding the spatial distribution of species, extent of habitats and the conditions that favor their growth and preservation.
Climate change and human activity have increased the risk of soil erosion in many areas of the Mediterranean, resulting in the near-desertification of previously rich soils. The variables that affect soil erosion and the calculation of the risk and the intensity of this process can be studied and monitored through the combined use of remote sensing and ancillary environmental data, in GIS.
Last update: Jan 12, 2017