Geographic Information Science and Remote Sensing Techniques for Sustainable Urban and Regional Planning

The ensemble of GI methodologies—mainly Geographic Information Science (GIS) and Remote Sensing (RS)—are fundamental tools for observing and investigating the dynamics of territorial phenomena. Such phenomena include urban sprawl, soil degradation and consumption, changes in land cover patterns, landscape fragmentation, etc. Thus, these methodologies enrich the geographical information available and support the development of more exhaustive environmental assessments. The aforementioned phenomena to be studied touch upon issues that are critical in our current “anthropocene” age. The world population is growing at an unprecedented pace, and the rural-to-urban population shift does not seem to be stopping anytime soon. Moreover, human activities are still the major cause of global environmental change. We believe GI technologies constitute an essential backbone for implementing interdisciplinary methodological workflows, so as to provide for and deepen our understanding of human/environment interrelations. GI techniques represent the core of this sort of analysis, and constitute an efficient way of correlating several dimensions (such as territorial, ecological, socio-economic, etc.). These techniques thus foster sustainable development planning and monitoring. The current wide diffusion of electronic devices that contain geo-referenced information has resulted in the mass production and availability of spatial data. In fact, Volunteered Geographic Information activities (e.g., OpenStreetMap, Wikimapia, etc.), public initiatives (e.g., Open data, Spatial Data Infrastructures, Geo-portals, etc.) and private projects (e.g., Google Earth, Bing Maps, etc.) have all contributed to an overabundance of spatial data. On the one hand, the base of information available has greatly expanded; but on the other hand, this might also result in increased system complexity, longer computing times, decreased efficiency for the research framework, and more complex decision-making processes. The increase of geographical data availability has not been fully coupled with an increase of knowledge to support spatial decisions. Spatial modelling, Geo-Computational techniques, and geographical analyses are therefore required for data analysis and for facilitating the decision-making process at all levels. This Special Issue aims to provide an innovative and original contribution to the on-going debate in regards to the above mentioned issues. Furthermore, it will focus on the process of geo-spatial knowledge acquisition, as accomplished through the development of new techniques and methods, which has the goal of efficiently supporting policy decision-making and urban/regional planning at all scales.