Omid Rahmati – författare
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5 produkter
5 produkter
Häftad, Engelska, 2023
1 570 kr
Skickas inom 10-15 vardagar
Remote Sensing of Soil and Land Surface Processes: Monitoring, Mapping, and Modeling couples artificial intelligence and remote sensing for mapping and modeling natural resources, thus expanding the applicability of AI and machine learning for soils and landscape studies and providing a hybridized approach that also increases the accuracy of image analysis. The book covers topics including digital soil mapping, satellite land surface imagery, assessment of land degradation, and deep learning networks and their applicability to land surface processes and natural hazards, including case studies and real life examples where appropriate.
This book offers postgraduates, researchers and academics the latest techniques in remote sensing and geoinformation technologies to monitor soil and surface processes.
Introduces object-based concepts and applications, enhancing monitoring capabilities and increasing the accuracy of mappingCouples artificial intelligence and remote sensing for mapping and modeling natural resources, expanding the applicability of AI and machine learning for soils and sediment studiesIncludes the use of new sensors and their applications to soils and sediment characterizationIncludes case studies from a variety of geographical areas
E-bok
Engelska, 20232 233 kr
Läs direkt efter köp
Remote Sensing of Soil and Land Surface Processes: Monitoring, Mapping, and Modeling couples artificial intelligence and remote sensing for mapping and modeling natural resources, thus expanding the applicability of AI and machine learning for soils and landscape studies and providing a hybridized approach that also increases the accuracy of image analysis. The book covers topics including digital soil mapping, satellite land surface imagery, assessment of land degradation, and deep learning networks and their applicability to land surface processes and natural hazards, including case studies and real life examples where appropriate.This book offers postgraduates, researchers and academics the latest techniques in remote sensing and geoinformation technologies to monitor soil and surface processes.- Introduces object-based concepts and applications, enhancing monitoring capabilities and increasing the accuracy of mapping- Couples artificial intelligence and remote sensing for mapping and modeling natural resources, expanding the applicability of AI and machine learning for soils and sediment studies- Includes the use of new sensors and their applications to soils and sediment characterization- Includes case studies from a variety of geographical areas
Häftad, Engelska, 2025
1 810 kr
Skickas inom 10-15 vardagar
Drought and the condition of water scarcity lead to several socio-economic, social and environmental impacts. Whatever the approaches of drought management, policymakers and planners require novel methods to analyze data and model drought processes and its connection with water scarcity. In recent years, artificial intelligence-based and earth observation approaches have been progressively developed and applied in domain of water-related disasters. The target of this book is to present new advances and achievements in the fields of drought monitoring, analyzing, and modeling using artificial intelligence algorithms (e.g., machine learning, deep learning, etc.), statistical indices, and a diverse range of satellite remote sensing and geo-spatial data sets. Water Scarcity Management: Towards the Application of Artificial Intelligence and Earth Observation Data will help students gain knowledge on drought prediction using new free-access earth observation data and machine learning models. It will also guide scientists, researchers, and urban planners with the monitoring of water resources and key elements of hydrological cycle.Covers application of a range of diverse artificial intelligence algorithms for spatial modeling of drought susceptibilityIncludes real case studies from large geographical areasOffers earth observation satellite data for spatio-temporal analysis of drought and water scarcityCombines geo-environmental and topo-hydrological factors with drought and water scarcity issues
E-bok
Engelska, 20252 290 kr
Läs direkt efter köp
Drought and the condition of water scarcity lead to several socio-economic, social and environmental impacts. Whatever the approaches of drought management, policymakers and planners require novel methods to analyze data and model drought processes and its connection with water scarcity. In recent years, artificial intelligence-based and earth observation approaches have been progressively developed and applied in domain of water-related disasters. The target of this book is to present new advances and achievements in the fields of drought monitoring, analyzing, and modeling using artificial intelligence algorithms (e.g., machine learning, deep learning, etc.), statistical indices, and a diverse range of satellite remote sensing and geo-spatial data sets. Water Scarcity Management: Towards the Application of Artificial Intelligence and Earth Observation Data will help students gain knowledge on drought prediction using new free-access earth observation data and machine learning models. It will also guide scientists, researchers, and urban planners with the monitoring of water resources and key elements of hydrological cycle. - Covers application of a range of diverse artificial intelligence algorithms for spatial modeling of drought susceptibility- Includes real case studies from large geographical areas- Offers earth observation satellite data for spatio-temporal analysis of drought and water scarcity- Combines geo-environmental and topo-hydrological factors with drought and water scarcity issues
Häftad, Engelska, 2026
1 185 kr
Kommande
Natural Disasters Under Changing Climate: Modeling Strategies, Predictions, and Management is an essential textbook within the natural disaster prediction domain, functioning as a comprehensive book on natural disasters, and focusing on floods, landslides, earthquakes, dust storms, land subsidence, wildfire, sea level rise, drought, snow avalanches, debris flow, desertification, sand dune migration, and heatwaves. In addition to taking a range of natural disasters into account, it covers novel approaches in artificial intelligence and remote sensing and provides an overview of the different concepts of natural disasters perception and how geo-environmental, topo-hydrological, and edaphic variables are connected with their occurrences.The initial chapters of the book shed light on the main principles and mechanisms of disasters prediction and the application of artificial intelligence algorithms in natural disasters domain. They discuss the applicability of the predictive models in the natural hazards domain and how the understanding of disaster management can happen with the help of disaster susceptibility maps. The book then pivots into landslide susceptibility modeling under climate change and details the use of DInSAR as a powerful tool for studying the effects of earthquakes in various regions. Following that, dust storm frequency and intensity, and how these are impacted by climatic factors, as well as water and land use management, is discussed at length.Functions as a comprehensive textbook on natural disasters, focusing on floods, landslides, earthquakes, dust storms, land subsidence, wildfire, sea level rise, drought, snow avalanches, debris flow, and desertificationProvides unique and cutting-edge research on natural disaster predictionExplores novel approaches in the field of artificial intelligence and remote sensingPresents scientific frameworks for the spatial prediction of a wide suite of natural disaster types, with a focus on their specific triggers and processesOffers study questions and case studies for students and instructors