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Remote sensing
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Books about remote sensing

Remote Sensing and Image Interpretation
Remote Sensing and Image Interpretation presents the principles on which remote sensing is used, and explores the interplay between remote sensing and GIS. It describes the tools of photography, airphoto interpretation processes, and principles of acquiring and interpreting data collected by non-photographic sensors. Extensively illustrated, this invaluable reference provides a balance between classical visual image interpretation and digital image processing techniques.

An Introduction to Satellite Image Interpretation
Prepared in association with the National Oceanic and Atmospheric Administration (NOAA), this extensively illustrated text and accompanying CD-ROM offer a thorough overview of the use of satellite technology in Earth and planetary science, weather forecasting, and environmental research. The book covers the foundations of remote sensing, the types of satellites, and the basics of satellite image interpretation. Other topics include geographical, oceanographical applications, and atmospheric science applications of satellite imagery. With a fully indexed glossary, this well-written and thoughtfully presented text is ideal for science teachers, undergraduate and graduate students, professionals working in the field of operational meteorology, and others interested in knowing more about interpreting satellite imagery. The accompanying CD-ROM of satellite images enables the user to zoom in on many images (some of which appear in color), use overlays to identify important elements in the satellite image, and keep a notes file.

Computer Processing of Remotely Sensed Images : An Introduction
"...Like its first edition, Computer Processing of Remotely-Sensed Images: An Introduction will serve as a well-structures introductory textbook for geography students studying remote sensing at an advanced undergraduate and Masters levels. The book can be used as a sequence of remote sensing tutorials, with questions at the end of each chapter..." GI News, March 2000
Remote Sensing in Hydrology and Water Management
Uncertainty in Remote Sensing and GIS
The growth in the use of remote sensing systems and GIS has been accompanied by an awareness of the limitations imposed by uncertainty. The contributors to this volume focus on uncertainty in these two systems in a clear and comprehensive way.
Geoinformation: Remote Sensing, Photogrammetry and Geographical Information Systems
This book presents the required basic background for remote sensing, digital photogrammetry and GIS in the new geoinformatics concept in which the different methodologies must be combined. For remote sensing, the basic fundamentals are the properties of electromagnetic radiation and their interaction with matter. This radiation is received by sensors and platforms in analogue or digital form, and is subject to image processing. In photogrammetry, the stereo-concept is used for the location of information in 3D. With the advent of high-resolution satellite systems in stereo, the theory of analytical photogrammetry restituting 2-D image information into 3D is of increasing importance, merging the remote sensing approach with that of photogrammetry. The result of the restitution is a direct input into geographical information systems in vector or in raster form. The fundamentals of these are described in detail, with an emphasis on global, regional and local applications.
Introductory Digital Image Processing: A Remote Sensing Perspective
This text focuses exclusively on the art and science of digital image processing of satellite and aircraft-derived remotely-sensed data for resource management. Extensively illustrated, it explains how to extract biophysical information from remote sensor data for almost all multidisciplinary land-based environmental projects.
Classification Methods for Remote Sensed Data
The extraction of thematic information from remotely sensed images is a key area of research into applications of remote sensing data. Standard methods of classification based on similarity ond probability measures, such as the maximum likelihood procedure, are now being superseded neural/connectionist and artificial intelligence algorithms. Concepts such as fuzzy decision rules and soft classification are extending the traditional boundaries of pattern recognition.
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