Possible climatic impacts of tropical deforestation

Large-scale conversion of tropical forests into pastures or annual crops will likely lead to changes in the local microclimate of those regions. Larger diurnal fluctuations of surface temperature and humidity deficit, increased surface runoff during rainy periods and decreased runoff during the dry season, and decreased soil moistrue are to be expected.It is likely that evapotranspiration will be reduced because of less available radiative energy at the canopy level since grass presents a higher albedo than forests, also because of the reduced availability of soil moisture at the rooting zone primarily during the dry season. Recent results from general circulation model (GCM) simulations of Amazonian deforestation seem to suggest that the equilibrium climate for a grassy vegetation in Amazonia would be one in which regional precipitation would be significantly reduced.Global climate changes probably will occur if there is a marked change in rainfall patterns in tropical forest regions as a result of deforestation. Besides that, biomass burning of tropical forests is likely adding CO₂ into the atmosphere, thus contributing to the enhanced greenhouse warming.     

Lithological mapping and fuzzy set theory: Automated extraction of lithological boundary from ASTER imagery by template matching and spatial accuracy assessment

Lithological boundaries provide information useful for activities such as mineral and hydrocarbon exploration, water resource surveys, and natural hazard evaluation. Automated detection of lithological boundaries reduces bias inherent in expert interpretation of boundaries and thus improves the reliability of lithological mapping. The Rotation Variant Template Matching (RTM) algorithm was applied to ASTER imagery to detect pre-defined lithological boundaries. Templates incorporating the mineral combinations gypsum–calcite and calcite–illite were designed to detect boundaries between evaporites, marly limestone, and sandstone. The RTM algorithm successfully detected lithological boundaries by rotating the templates over the ASTER imagery. The accuracy of the detected boundaries was spatially assessed using fuzzy set theory. Boundaries from a published geological map and boundaries interpreted from a stereo pair of aerial photos by five experts were used as references for assessing the accuracy. A confidence region unifying spatial errors was defined for the geological map and stereo-pair interpretation to provide boundary zones from these references. The correspondence between detected boundaries and the boundary zones of the aerial photo was better than between detected boundaries and boundary zones of the geological map.