GIS and remote sensing methods in predicting the dissipation time of rural settlements under the influence of climate change in the Republic of Serbia

Abstract

In this research the specific methodology used to better analyzed rural settlements and they properties. The Geographical Information Systems and Remote Sensing approaches taken to connect rural settlements with the climate change effects in Serbia. For the first time the classification of settlements after approved methodology divided in accordance of new spatial relations within the situation in Serbia. Ten morphometric types of rural settlements were analyzed in terms of social, economic, transport, demographic and climatic factors. The effects of climate change, estimated in this study, will become even more noticeable by 2050. The results showed that the rural settlements (villages) in southern and eastern Serbia are very similar to the villages in central Banat in terms of resolution and low value of mitigation of the effects of climate change. In 2050, 35% of the villages in the south, 30% in the east, and 23% in other regions will be dissipated. The total number of dissipated rural settlements in the period from 2011 to 2050 is 680 or 15% in total. By means of GIS and remote sensing methods, all rural settlements were mapped and presented statistically, along with their characteristics. This method is useful for the analysis of rural settlements with 0–15,000 inhabitants. The shape of the settlements was also analyzed and the zones with the strongest impacts of climate change were marked. The hazardous events are divided into extreme rainfall, wind, drought and maximum temperatures and compared with the types of rural settlements. The climate factors included, together with other parameters such as socio-economic, demographic and urban planning factors, provide a complete overview and a better understanding of the survival of rural settlements in the future. The main contribution of this research is the creation of a new classification of rural settlements, taking into account the effects of climate change and new socio-economic theories. In this way, the old classifications and theories that were established fifty years ago will be improved.