Walid Al-Shaar earned his PhD in Geography (Urban Planning) from Université Saint Joseph de Beyrouth and PhD in Civil Engineering (Transport) from L'école doctorale des sciences et technologies de L'université Libanaise (2018-2021), with a research mobility period at Université Sorbonne Nouvelle (Paris 3) through Erasmus+. He holds a Master's degree in Highway Transportation and Traffic Engineering from Lebanese University and is a certified Project Management Professional (PMP). Served as Assistant Professor of Civil Engineering at the American University of the Middle East, Kuwait, Dr. AL-SHAAR currently holds the position of Research Director in Novum Research and Innovation center in Beirut, Lebanon as as well as the position of Associate Researcher (Data Scientist) at CNRS Lebanon's National Center for Remote Sensing, where he specializes in satellite image analysis and climate change impact detection. His extensive research portfolio encompasses urban planning, Autonomous Mobility, transportation engineering, geospatial analysis, land use dynamics, and climate vulnerability assessment. Dr. Al-Shaar has authored over 25 peer-reviewed research articles published in prestigious international journals, including Scientific Reports, and various Springer journals, along with two book chapters. He serves as an Editorial Board Member for PLOS One journal and maintains active GitHub repositories sharing his computational methodologies. His research expertise spans advanced spatial modeling techniques, including Multilayer-Perceptron Markov-Chain models, fractal analysis, and geographically weighted regression, with proficiency in R, Python, MATLAB, ArcGIS, and various geospatial analysis tools. With substantial teaching experience across multiple French and Lebanese universities, Dr. Al-Shaar has delivered courses on transportation engineering, geomatics, urban planning, research methodology, and smart mobility. Prior to his academic career, he accumulated significant professional experience as a design and proposal engineer, working on major infrastructure projects across Lebanon, Saudi Arabia, and the Gulf region, including the Riyadh Metro and various urban water master plans.
Dr. Mandal graduated from the University of Calcutta with a PhD in Climatology. Numerous research articles have been published in highly reputable national and international journals, and chapters in edited book volumes. He has been recognized by reputable scientific organizations with several prestigious scientific awards, including the Young Scientist Award, Best Research Article, Best Paper Presentation, and others. Dr. Mandal has an excellent academic record, having attended several premier institutions in India, such as Ramakrishna Mission, Presidency College, and Calcutta University. His current job involves being an Assistant Professor in the Geography Department at Banwarilal Bhalotia College, Asansol-713303, West Bengal, India.
Dr. Ghaleb Faour holds a Ph.D. in Engineering Science obtained in 1995 from the University of Marseille III - France. He held a Researcher position from 1996 at the Lebanese National Center for Remote Sensing (CNRS) until he got promoted to become a Director of Research and Director of the National Center for Remote Sensing in 2014. His main research interests focus on the development of applied remote sensing technology in the sector of environmental monitoring and natural resources management. He is a Lecturer in Remote Sensing and Geographic Information System at the Lebanese University and the Higher School of Surveyors and Topographers in Lebanon. He had supervised and co-advised more than Ten Ph.D. students and Twenty Master Thesis. He conducted several specialized training courses and consultancies in GIS and Remote Sensing applied to urban planning, management of protected areas, agriculture, desertification, drought, climate change, and integrated water resources with the German International Cooperation (GIZ), UNDP, FAO and the Arab Institute of Forestry and Rangeland. He is the author of more than 50 articles published in peer-reviewed international journals as well as the co-author of “Atlas of Lebanon: Territory and Society” published in 2007 in French language and translated to Arabic in 2012, “Space Atlas of Lebanon” published in 2014 and “Atlas of Lebanon: New Challenges” published in 2016. He is the member of the National GIS Committee in 2002, the National Committee “Delimitation of the Maritime Exclusive Economic Zone” in 2009 and Chairman of the National Committee “Unification of Geospatial Coding” in 2015, created by the Prime Minister Office. Also, he is the member of the Governing Board of the Regional Centre for Space Science and Technology Education for Western Asia located in Jordan. He is a national reference and representative of Lebanon in the United Nations Institutes UN SPIDER and UN Outer Space since 2010 in the sector of space research and activities.
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Paperback. Etat : new. Paperback. The twenty-first century faces a pressing paradox: while technological advancement accelerates, global food insecurity still threatens millions. Climate change, population growth, and resource constraints have exposed critical weaknesses in agricultural systems. Addressing these challenges requires a shift toward data-driven, resilient farming practices. Geospatial Artificial Intelligence (GeoAI), combining AI, machine learning, and geographic information science, enables the analysis of spatial data from satellites, drones, and IoT sensors. By providing real-time insights into soil, crops, water, and climate, GeoAI supports smarter decisions that improve productivity, reduce waste, and strengthen food system resilience. Transforming Global Food Security and Agricultural Sustainability With Geospatial AI (GeoAI) explores how GeoAI is redefining the agricultural landscape across scales, from local farms to global supply chains. Through interdisciplinary perspectives that blend data science, environmental policy, and sustainable development, this book bridges the gap between technological potential and real-world application. Covering topics such as plant disease detection, apple health monitoring, and precision crop mapping, this book is an excellent academic resource for graduate and doctoral students, agricultural research scientists, data scientists, AI engineers, policymakers, and more. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9798337380384
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Paperback. Etat : new. Paperback. The twenty-first century faces a pressing paradox: while technological advancement accelerates, global food insecurity still threatens millions. Climate change, population growth, and resource constraints have exposed critical weaknesses in agricultural systems. Addressing these challenges requires a shift toward data-driven, resilient farming practices. Geospatial Artificial Intelligence (GeoAI), combining AI, machine learning, and geographic information science, enables the analysis of spatial data from satellites, drones, and IoT sensors. By providing real-time insights into soil, crops, water, and climate, GeoAI supports smarter decisions that improve productivity, reduce waste, and strengthen food system resilience. Transforming Global Food Security and Agricultural Sustainability With Geospatial AI (GeoAI) explores how GeoAI is redefining the agricultural landscape across scales, from local farms to global supply chains. Through interdisciplinary perspectives that blend data science, environmental policy, and sustainable development, this book bridges the gap between technological potential and real-world application. Covering topics such as plant disease detection, apple health monitoring, and precision crop mapping, this book is an excellent academic resource for graduate and doctoral students, agricultural research scientists, data scientists, AI engineers, policymakers, and more. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9798337380384
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Taschenbuch. Etat : Neu. Transforming Global Food Security and Agricultural Sustainability With Geospatial AI (GeoAI) | Walid Al-Shaar (u. a.) | Taschenbuch | Englisch | 2026 | IGI GLOBAL SCIENTIFIC PUBLISHING | EAN 9798337380384 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. N° de réf. du vendeur 135919770
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The twenty-first century faces a pressing paradox: while technological advancement accelerates, global food insecurity still threatens millions. Climate change, population growth, and resource constraints have exposed critical weaknesses in agricultural systems. Addressing these challenges requires a shift toward data-driven, resilient farming practices. Geospatial Artificial Intelligence (GeoAI), combining AI, machine learning, and geographic information science, enables the analysis of spatial data from satellites, drones, and IoT sensors. By providing real-time insights into soil, crops, water, and climate, GeoAI supports smarter decisions that improve productivity, reduce waste, and strengthen food system resilience. Transforming Global Food Security and Agricultural Sustainability With Geospatial AI (GeoAI) explores how GeoAI is redefining the agricultural landscape across scales, from local farms to global supply chains. Through interdisciplinary perspectives that blend data science, environmental policy, and sustainable development, this book bridges the gap between technological potential and real-world application. Covering topics such as plant disease detection, apple health monitoring, and precision crop mapping, this book is an excellent academic resource for graduate and doctoral students, agricultural research scientists, data scientists, AI engineers, policymakers, and more. N° de réf. du vendeur 9798337380384
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