With the widespread availability of satellite and aircraft remote sensing image data in digital form, and the ready access most remote sensing practitioners have to computing systems for image interpretation, there is a need to draw together the range of digital image processing procedures and methodologies commonly used in this field into a single treatment. It is the intention of this book to provide such a function, at a level meaningful to the non-specialist digital image analyst, but in sufficient detail that algorithm limitations, alternative procedures and current trends can be appreciated. Often the applications specialist in remote sensing wishing to make use of digital processing procedures has had to depend upon either the mathematically detailed treatments of image processing found in the electrical engineering and computer science literature, or the sometimes necessarily superficial treatments given in general texts on remote sensing. This book seeks to redress that situation. Both image enhancement and classification techniques are covered making the material relevant in those applications in which photointerpretation is used for information extraction and in those wherein information is obtained by classification.

Advanced Remote Sensing is an application-based reference that provides a single source of mathematical concepts necessary for remote sensing data gathering and assimilation. It presents state-of-the-art techniques for estimating land surface variables from a variety of data types, including optical sensors such as RADAR and LIDAR. Scientists in a number of different fields including geography, geology, atmospheric science, environmental science, planetary science and ecology will have access to critically-important data extraction techniques and their virtually unlimited applications. While rigorous enough for the most experienced of scientists, the techniques are well designed and integrated, making the book's content intuitive, clearly presented, and practical in its implementation. - Comprehensive overview of various practical methods and algorithms - Detailed description of the principles and procedures of the state-of-the-art algorithms - Real-world case studies open several chapters - More than 500 full-color figures and tables - Edited by top remote sensing experts with contributions from authors across the geosciences

"High spatial remote sensing data have been often used as valuable sources of information throughout emergency management cycle. Information extracted in high spatial remote sensing data right after a devastating earthquake can help assess the earthquake's damage of roads and buildings and make emergency plans for contact and evacuation. The book will discuss emerging high spatial resolution data sources, and detail novel techniques and applications for handling, retrieving, and making best use of high spatial resolution remote sensing data."--Provided by publisher.

Over the past decade renewed interest in practical applications of Earth observations from space has coincided with and been fueled by significant improvements in the availability of remote sensing data and in their spectral and spatial resolution. In addition, advances in complementary spatial data technologies such as geographic information systems and the Global Positioning System have permitted more varied uses of the data. During the same period, the institutions that produce remote sensing data have also become more diversified. In the United States, satellite remote sensing was until recently dominated largely by federal agencies and their private sector contractors. However, private firms are increasingly playing a more prominent role, even a leadership role, in providing satellite remote sensing data, through either public-private partnerships or the establishment of commercial entities that serve both government and private sector Earth observation needs. In addition, a large number of private sector value-adding firms have been established to work with end users of the data. These changes, some technological, some institutional, and some financial, have implications for new and continuing uses of remote sensing data. To gather data for exploring the importance of these changes and their significance for a variety of issues related to the use of remote sensing data, the Space Studies Board initiated a series of three workshops. The first, "Moving Remote Sensing from Research to Applications: Case Studies of the Knowledge Transfer Process," was held in May 2000. This report draws on data and information obtained in the workshop planning meeting with agency sponsors, information presented by workshop speakers and in splinter group discussions, and the expertise and viewpoints of the authoring Steering Committee on Space Applications and Commercialization. The recommendations are the consensus of the steering committee and not necessarily of the workshop participants.

Advances in spatial, spectral, and temporal resolution over the past several years have greatly expanded opportunities for practical applications of remote sensing data. To explore the implications of these possibilities, the NRC held a series of three workshops on different facets of remote sensing applications. This report is on the third of those workshops: the development and use of remote sensing data and information by state, local, and regional governments. The steering committee was asked to examine the opportunities, potential challenges, and policy issues associated with the application of remote sensing data in the public sector including approaches and procedures for government agencies to use such data and barriers to development and use of the applications. The resulting report is addressed primarily to non-technical managers and decisions makers at all levels of government below the federal level.

This book is a completely updated, greatly expanded version of the previously successful volume by the author. The Second Edition includes new results and data, and discusses a unified framework and rationale for designing and evaluating image processing algorithms.Written from the viewpoint that image processing supports remote sensing science, this book describes physical models for remote sensing phenomenology and sensors and how they contribute to models for remote-sensing data. The text then presents image processing techniques and interprets them in terms of these models. Spectral, spatial, and geometric models are used to introduce advanced image processing techniques such as hyperspectral image analysis, fusion of multisensor images, and digital elevationmodel extraction from stereo imagery.The material is suited for graduate level engineering, physical and natural science courses, or practicing remote sensing scientists. Each chapter is enhanced by student exercises designed to stimulate an understanding of the material. Over 300 figuresare produced specifically for this book, and numerous tables provide a rich bibliography of the research literature.

This book shows how artificial intelligence, including neural networks and deep learning, can be applied to the processing of satellite data for Earth observation. The authors explain how to develop a set of libraries for the implementation of artificial intelligence that encompass different aspects of research.