Buch, Englisch, 452 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 946 g
Buch, Englisch, 452 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 946 g
Reihe: Advances in Geographic Information Science
ISBN: 978-3-032-03713-8
Verlag: Springer
This edited volume brings together leading experts and researchers from diverse disciplines to provide insights into how geospatial data and AI technologies can be leveraged to tackle pressing environmental issues, ranging from climate change mitigation to natural resource management. By combining geospatial analysis with AI algorithms such as machine learning and deep learning, the book showcases innovative approaches for monitoring, modelling, and managing environmental systems at various scales.
The chapters in this book bridge the gap between theory and practice,offering practical guidance and real-world case studies to readers interested in harnessing the potential of geospatial and AI technologies for sustainability and resilience initiatives. Through a series of chapters covering topics such as remote sensing, spatial data analysis, environmental modelling, and decision support systems, the book equips readers with the knowledge and tools necessary to address complex environmental challenges in an increasingly interconnected world. The book fills an important gap by providing a timely and authoritative resource that not only explores the theoretical foundations of geospatial and AI applications but also offers practical insights into their implementation and potential impact.
Ultimately this volume seeks to empower readers with the knowledge and tools needed to address environmental challenges effectively and promote sustainable resilience in an ever-changing world. The contents here offer valuable insights and guidance for leveraging the transformative power of geospatial and AI technologies to create a more sustainable future.
Zielgruppe
Research
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Weitere Infos & Material
Using geospatial technologies and machine learning to map and mitigate urban heat islands and improve urban livability.- Urban expansion and thermal environment in a medium size city role of urban green and blue spaces in mitigating surface urban heat island intensity.- Identification of on road and roadside objects using random forest-based prediction model.- Analyzing the role of geospatial technologies and al in urban infrastructure planning and the development of smart cities, including transportation systems utilities, and public services.- Assessing the impact of night time light as proxy for climate change a geospatial approach in himachal pradesh.- Decadal study on supraglacial debris cover of kaer glacier eastern himalayas.- Sessing the impact of climate change on glaciers through region wise mass balance and ai tools contributing to our understanding of environmental changes in high mountain asia.- Climate change impacts on various ecosystems a geospatial and ai perspective.- Early identification and pathogenesis of leaf diseases in magnifera indica using transfer learning.- Examining the role of geospatial data and ai in conducting comprehensive forestry inventories and mapping to support sustainable forest management.- Prioritization of erosion prone watersheds of the song river basin using morphometric indices coupled with ahp-topsis and geospatial technology.- Application of geospatial technologies and ai to detect and analyze the shoreline change of Visakhapatnam a coastal district.- A systematic and structured review on groundwater contamination sources prevalence health risk and mitigation strategies in relation with land use land cover in bihar state of india.- A systematic and structured review on groundwater contamination, sources, prevalence health risk and mitigation strategies in relation with land use land cover in bihar state of india.- Examining the role of geospatial technologies and ai in disaster risk management and response including hazard mapping vulnerability assessment and real-time monitoring.- Gis based landslide susceptibility assessment for coonoor taluk nilgiris district south india tamil nadu using machine learning algorithm.- Forecasting drought from satellite imagery comparing stochastic classical machine learning and deep learning approaches.- Smart geospatial intelligence and ai for a resilient environment a review.- Uncovering air pollution risks in indian scenario with explainable ai a case study perspective.
