Spatial Analysis for Complex Territorial Systems: Geo-information Technologies and European Official Statistics offers a multidisciplinary exploration of spatial analysis, geo-information technologies, and official statistics, focusing on their application to environmental, economic, and planning challenges in Europe and the Mediterranean. Comprising 16 insightful chapters authored by leading scholars from Southern and Eastern Europe, Ireland, and the United States, it delves into the complexities of socio-ecological monitoring through data integration and refined statistical indicators. Key topics include climate monitoring, land degradation, settlement patterns, and disaster resilience, providing a comprehensive understanding of local contexts and policy implications.
The book begins with contributions from a traditional ecological/agronomic/environmental vision, then continues with a set of studies having a more strict socio-demographic and economic focus. It then discusses how other quantitative approaches, e.g. based on big data and primary surveys, may clarify the role of policies and planning addressing sustainable development goals in the ‘kaleidoscopic’ European landscapes. The conclusions of this book confirm the urgent need of integrating the vast potential of geo-information techniques, together with spatial analysis and official statistics, into more flexible sustainable development strategies reflecting local conditions and spatially explicit background contexts, starting from the basic demands of local communities and topical environments.
Spatial Analysis for Complex Territorial Systems: Geo-information Technologies and European Official Statistics serves as an essential resource for academics, students, spatial planners, policymakers, architects, engineers, sociologists, and environmental demographers. It equips readers with practical tools and theoretical insights to inform data-driven approaches to sustainable development and regional planning, making it a vital addition to any academic curriculum in geographic information systems, applied statistics, and environmental science.
