Spatial Analysis for Complex Territorial Systems : Geo-information Technologies and European Official Statistics (Earth Observation)

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Spatial Analysis for Complex Territorial Systems : Geo-information Technologies and European Official Statistics (Earth Observation)

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 526 p.
  • 言語 ENG
  • 商品コード 9780443441332
  • DDC分類 910.285

Full Description

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 applications in 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, the book 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, and environmental vision, then continues with a set of studies with stricter 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. Conclusions 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 that reflect local conditions and spatially explicit background contexts.

Contents

Spatial analysis, statistical indicators and the accountability of complex socio-environmental processes: a challenge for sustainable development



Optimal resource management, environmental-economic impact assessment and social dynamics



Climate change and geo-statistical indicators for landscape analysis



Quantifying 'wood capital' through remote sources: a spatial comparison of multiple forest cover indicators



Sampling (infinite) populations in a geo-spatial framework: an operational perspective



Toward 'natural farming systems'? Identifying 'Intensive' and 'Extensive' Agricultural Landscapes in Italy from official statistics



Socio-environmental resilience and applied economics: from theory to indicators



Integrating externalities into economic systems for long-term environmental sustainability



Spatial distribution and settlement patterns of foreign population in Italy and Spain: a comparative multi-scale approach



A Research Design Modeling of the Migrant-Refugee Issue: lessons from an integrated large-scale survey in Greece



Residential mobility of older population: recent dynamics across Italian and Spanish municipalities



Assessing multidimensional influence of social media on consumer behavior using indicators: economic forces, cognitive perceptions, and social mechanisms in the contemporary digital era



Monitoring socio-demographic behaviours through indicators from primary surveys: the attitude of female students towards cohabitation in Greece



Toward a global analysis of wealth concentration: the case of per-land income distribution



Enhancing Disaster Resilience: Hellenic National Civil Protection Mechanism and Local Government Participation in Risk and Disaster Management



The Forest Map of Italy: an innovative tool for comprehensive planning of Italian woods



Insights into Italy's National Recovery and Resilience Plan: a performance index for municipal administrations using spatial data



Monitoring local resilience of health financing systems: Evidence from Covid-19 pandemic in Northern Italy



The complex interplay among land, access, infrastructure, and (sustainable) real estate: a spatial critique



Lights of change: what Nighttime Light data reveal about metropolitan dynamics

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