Deforestation is a permanent change of forest cover area to non-forest cover area. Social factors contribute more to the occurrence of deforestation, so this study was directed to examine the social factors that drive deforestation. Research location selected based on the key vulnerability of deforestation profiles. This study only used moderately vulnerability and vulnerability profile. Data analysis in this research using PCA (Principal Component Analysis) Method. The results explained that the Spatial Deforestation Model in South Sulawesi and West Sulawesi have differences based on the vulnerability profile. The dominant deforestation profiles affected were population density, productive age and employment. Population density affects deforestation because the site is always experiencing an increase in population and is not balanced with the extent of its territory, especially on vulnerable profiles. Productive age is very influential and increasing. The employment is also one of the most influencing of deforestation. The field of education itself does not give a significant effect. The spatial model of deforestation based on social factors in South Sulawesi shows that in the same profile different influences were found. In West Sulawesi, social involvement tends to be the same for each profile. The influence of population, productive age and availability of regions has a significant influence on the incidence of deforestation.
One of the major obstacles in increasing the agricultural production yields is the inappropriate management of land use due to the differences in land biophysical characteristics in each region. Therefore, it is necessary to have spatial-based land use management that is appropriate for handling agricultural land. This research aims at structuring geospatial information of agricultural land biophysical characteristics and agricultural land appropriateness (potential and limiter) for food plants development in Pangkep Regency. This research uses the up-to-date approach of multi-scale observation, so the problems becoming the restricting factors of productivity can immediately be overcome. The method used consists of 2 stages, namely stage 1, analysis of agricultural land (biophysical) climate and land characteristics through land survey, laboratory analysis, and land characteristic spatialization; stage 2, analysis of agricultural land appropriateness (potential and limiter) using land appropriateness method offuzzy set/FAO, satellite image information extraction, ground truth, and ground sampling. The results of the research are in the form of geospatial information on agricultural land biophysical characteristics and agricultural land appropriateness (potential and limiter) for food plants development in Pangkep Regency. With the information, decision makers will have more ease and they integrate into making policies for agricultural land use management in Pangkep Regency that will end up aiming to increase food production.
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