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The Center for Transportation Research and Education (CTRE) issued a report in July 2003, based on a sample study of the application of remote sensed image land use change detection to the methodology of traffic monitoring in Blackhawk County, Iowa. In summary, the results indicated a strong correlation and a statistically significant regression coefficient between the identification of built-up land use change areas from remote sensed data and corresponding changes in traffic patterns, expressed as vehicle miles traveled (VMT). Based on these results, the Iowa Department of Transportation (Iowa DOT) requested that CTRE expand the study area to five counties in the southwest quadrant of the state. These counties are scheduled for traffic counts in 2004, and the Iowa DOT desired the data to 1) evaluate the current methodology used to place the devices; 2) potentially influence the placement of traffic counting devices in areas of high built-up land use change; and 3) determine if opportunities exist to reduce the frequency and/or density of monitoring activity in lower trafficked rural areas of the state. This project is focused on the practical application of built-up land use change data for placement of traffic count data recording devices in five southwest Iowa counties.
The conformal predictions framework is a recent development in machine learning that can associate a reliable measure of confidence with a prediction in any real-world pattern recognition application, including risk-sensitive applications such as medical diagnosis, face recognition, and financial risk prediction. Conformal Predictions for Reliable Machine Learning: Theory, Adaptations and Applications captures the basic theory of the framework, demonstrates how to apply it to real-world problems, and presents several adaptations, including active learning, change detection, and anomaly detection. As practitioners and researchers around the world apply and adapt the framework, this edited volume brings together these bodies of work, providing a springboard for further research as well as a handbook for application in real-world problems. - Understand the theoretical foundations of this important framework that can provide a reliable measure of confidence with predictions in machine learning - Be able to apply this framework to real-world problems in different machine learning settings, including classification, regression, and clustering - Learn effective ways of adapting the framework to newer problem settings, such as active learning, model selection, or change detection
Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.
Dedicated to remote sensing images, from their acquisition to their use in various applications, this book covers the global lifecycle of images, including sensors and acquisition systems, applications such as movement monitoring or data assimilation, and image and data processing. It is organized in three main parts. The first part presents technological information about remote sensing (choice of satellite orbit and sensors) and elements of physics related to sensing (optics and microwave propagation). The second part presents image processing algorithms and their specificities for radar or optical, multi and hyper-spectral images. The final part is devoted to applications: change detection and analysis of time series, elevation measurement, displacement measurement and data assimilation. Offering a comprehensive survey of the domain of remote sensing imagery with a multi-disciplinary approach, this book is suitable for graduate students and engineers, with backgrounds either in computer science and applied math (signal and image processing) or geo-physics. About the Authors Florence Tupin is Professor at Telecom ParisTech, France. Her research interests include remote sensing imagery, image analysis and interpretation, three-dimensional reconstruction, and synthetic aperture radar, especially for urban remote sensing applications. Jordi Inglada works at the Centre National d’Études Spatiales (French Space Agency), Toulouse, France, in the field of remote sensing image processing at the CESBIO laboratory. He is in charge of the development of image processing algorithms for the operational exploitation of Earth observation images, mainly in the field of multi-temporal image analysis for land use and cover change. Jean-Marie Nicolas is Professor at Telecom ParisTech in the Signal and Imaging department. His research interests include the modeling and processing of synthetic aperture radar images.
Wildland fires are occurring more frequently and affecting more of Earth's surface than ever before. These fires affect the properties of soils and the processes by which they form, but the nature of these impacts has not been well understood. Given that healthy soil is necessary to sustain biodiversity, ecosystems and agriculture, the impact of fire on soil is a vital field of research. Fire Effects on Soil Properties brings together current research on the effects of fire on the physical, biological and chemical properties of soil. Written by over 60 international experts in the field, it includes examples from fire-prone areas across the world, dealing with ash, meso and macrofauna, smouldering fires, recurrent fires and management of fire-affected soils. It also describes current best practice methodologies for research and monitoring of fire effects and new methodologies for future research. This is the first time information on this topic has been presented in a single volume and the book will be an important reference for students, practitioners, managers and academics interested in the effects of fire on ecosystems, including soil scientists, geologists, forestry researchers and environmentalists.
Reconstruction and Restoration of Architectural Heritage 2020 includes contributions on the protection, and restoration of architectural monuments and the reconstruction of major historical urban development sites, as well as various complex issues and aspects of engineering reconstruction of monuments and preservation of historical heritage. The contributions were presented at the eponymous conference (RRAH 2020, St Petersburg, Russia, 25-28 March 2020), and cover a wide range of topics: - Historical, architectural and urban planning research and restoration of monuments - Urban and regional planning - Engineering reconstruction, performance of repair and reconstruction works on monuments - Training of architects and restorers Reconstruction and Restoration of Architectural Heritage 2020 will be of interest to academics and professionals involved in the history and restoration of nature reserves, estates, cities and monuments.
Contains an inventory of evaluation reports produced by and for selected Federal agencies, including GAO evaluation reports that relate to the programs of those agencies.
This volume provides international case studies of practical and advanced methods using satellite images integrated with other airborne, drone images and field data to monitor infrastructure. The book is timely, as infrastructure spending by national governments is increasing and robust monitoring techniques are needed to keep pace with climate change impacts affecting infrastructures globally. The expert international contributions that comprise the book provide examples of advanced methods using InSAR, high-resolution optical and radar images, LIDAR, UAV, geophysical techniques and their applications to civil infrastructure. The case studies focus on high-resolution, rapid time-series radar interferometry to monitor highways, railways, pipelines, bridges, urban, and water conveyance infrastructures. Other case studies use optical and radar images to characterize urban infrastructure and monitor damages from floods, oil spills and conflicts. The case studies are global focusing on infrastructure projects in Canada, Dominica Guyana, India Italy, Syria Taiwan, United States and the United Kingdom. This compilation of selected case studies will provide useful guidelines for the civil infrastructure characterization and monitoring communities. The book will be of interest to infrastructure consultants and professionals, scientific communities in earth observation and advanced imaging methods, and researchers and professors in earth sciences, climate change, and civil and geoengineering.