Remote Sensing and Machine Learning in Conservation: Applications and Techniques (English Edition) baixar o livro de graça

Remote Sensing and Machine Learning in Conservation: Applications and Techniques presents a structured, decision-oriented guide to the responsible use of Earth observation, geospatial analysis, and artificial intelligence in biodiversity conservation and ecosystem management. It connects conservation questions with appropriate evidence, data preparation, model development and validation, uncertainty communication, ecological interpretation, and decision-ready outputs.Beginning with the foundations of remote sensing, it explains major machine-learning and deep-learning approaches, from supervised classification to Vision Transformers and reinforcement learning. Chapters then show how remote sensing and GeoAI support habitat mapping, species distribution modeling, biodiversity assessment, ecosystem-change detection, water and coastal conservation, wildlife monitoring, climate adaptation, invasive-species detection, restoration planning, and threat monitoring.Dedicated chapters translate theory into practice through project design, cloud-based platforms, open data, reproducible workflows, validation, dashboards, and operational monitoring, and address data governance, privacy, bias, accountability, Indigenous and local knowledge, participation, and responsible use. The closing chapter examines foundation models, multimodal GeoAI, ecosystem digital twins, real-time and edge AI, participatory monitoring, and future research priorities, helping readers move from tool-driven analysis toward scientifically grounded and actionable conservation evidence.
- Connects remote sensing and machine learning within a complete, decision-oriented conservation workflow
- Covers optical, thermal, radar, LiDAR, hyperspectral, UAV, satellite, camera-trap, acoustic, and telemetry data
- Explains classical machine learning, deep learning, Vision Transformers, generative models, reinforcement learning, and multimodal GeoAI
- Provides applied guidance for habitat, biodiversity, wildlife, water, coastal, climate-risk, invasive-species, restoration, and threat-monitoring applications
- Emphasizes validation, uncertainty, explainability, reproducibility, quality control, governance, ethics, and decision-ready communication
- Includes practical project-design guidance, case-study structures, learning objectives, key takeaways, exercises, and references in every chapter
- Examines emerging directions including foundation models, ecosystem digital twins, real-time sensing, edge AI, citizen science, and human-in-the-loop conservation intelligence

Procurando Remote Sensing and Machine Learning in Conservation: Applications and Techniques (English Edition)? Aqui você encontra tudo sobre este livro de Alireza Sharifi PhD, publicado por Academic Press. Nesta página estão a descrição da obra, os detalhes da edição e os formatos disponíveis para baixar: pdf, mp3, áudio-livro, kindle. Se você gosta de Inglês e Outras Línguas, Por Idioma, eBooks em inglês, Ciência e Tecnologia, explore também outros títulos da mesma categoria no LivrosQualidade. Veja ainda as outras obras de Alireza Sharifi PhD em nosso catálogo.