The NATO Science Committee and its subsidiary Programme Panels provide support for Advanced Research Institutes (ARI) in various fields. The idea is to bring together scientists of a chosen field with the hope that they will achieve a consensus on research direc tions for the future, and make recommendations for the benefit of a wider scientific community. Attendance is therefore limited to those whose experience and expertise make the conclusions significant and acceptable to the wider community. Participants are selected on the basis of substantial track records in research or in the synthesis of research results to serve mankind. The proposal for a one-week ARIon Earth Observation and In formation Systems was initiated by the NATO Special Programme Panel on Systems Science (SPPOSS). In approving the ARI, the senior NATO Science Committee identified the subject as one of universal impor tance, requiring a broad perspective on the development of opera tional systems based on successful experimental systems. The general purpose of this ARI was to address the critical problems of integrating the relatively new science and technology of remote sensing into operational earth observation and manage ment information systems. The main problems of concern were those related to systems design, organization, development of infrastruc ture, and use of information in decision processes. The main empha sis was on problems of transferring technologies and methods from experimental to operational systems.

The Earth Sciences industry faces a new challenge - the need for accurate, efficient, and reliable methods to monitor and predict geological phenomena and environmental changes. As climate change, earthquakes, and other natural disasters become more frequent and severe, the necessity for advanced tools and techniques is paramount. Traditional methods often fall short in providing the precision and speed required to address these critical issues. Geologists and earth scientists who are grappling with the urgent problem of utilizing artificial intelligence (AI) to revolutionize their field, will find the solution within the pages of Novel AI Applications for Advancing Earth Sciences. This book offers the research community concepts expanding upon the fusion of AI technology with earth sciences. By leveraging advanced AI tools, such as convolutional neural networks, support vector machines, artificial neural networks, and the potential of remote sensing satellites, this book transforms the identification of geological features, geological mapping, soil classification, and gas detection. Scientists can now predict earthquakes and assess the probability of climate change with unprecedented accuracy. Additionally, the book explains how the optimization of algorithms for specific tasks substantially reduces the time complexity of earth observations, leading to an unprecedented leap in accuracy and efficiency.

We live on a dynamic Earth shaped by both natural processes and the impacts of humans on their environment. It is in our collective interest to observe and understand our planet, and to predict future behavior to the extent possible, in order to effectively manage resources, successfully respond to threats from natural and human-induced environmental change, and capitalize on the opportunities â€" social, economic, security, and more â€" that such knowledge can bring. By continuously monitoring and exploring Earth, developing a deep understanding of its evolving behavior, and characterizing the processes that shape and reshape the environment in which we live, we not only advance knowledge and basic discovery about our planet, but we further develop the foundation upon which benefits to society are built. Thriving on Our Changing Planet presents prioritized science, applications, and observations, along with related strategic and programmatic guidance, to support the U.S. civil space Earth observation program over the coming decade.

The result of a workshop bringing together an international advisory board of experts in science, satellite technologies, industry innovations, and public policy, this book addresses the current and future roles of satellite Earth observations in solving large-scale environmental problems. The book showcases the results of engaging distinct communities to enhance our ability to identify emerging problems and to administer international regimes created to solve them. It also reviews the work of the Policy and Earth Observation Innovation Cycle (PEOIC) project, an effort aimed at assessing the impact of satellite observations on environmental policy and to propose a mission going forward that would launch an "innovation cycle". The achievements of such a mission would feed back to innovations in next-generation observation technology, thus contributing to global policy demand for policy-relevant information. This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.

Water systems are building blocks for poverty alleviation, shared growth, sustainable development, and green growth strategies. They require data from in-situ observation networks. Budgetary and other constraints have taken a toll on their operation and there are many regions in the world where the data are scarce or unreliable. Increasingly, remote sensing satellite-based earth observation is becoming an alternative. This book briefly describes some key global water challenges, perspectives for remote sensing approaches, and their importance for water resources-related activities. It describes eight key types of water resources management variables, a list of sensors that can produce such information, and a description of existing data products with examples. Earth Observation for Water Resources Management provides a series of practical guidelines that can be used by project leaders to decide whether remote sensing may be useful for the problem at hand and suitable data sources to consider if so. The book concludes with a review of the literature on reliability statistics of remote-sensed estimations.