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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.
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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. |
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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 |
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Remote Sensing in Hydrology and Water Management |
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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. |
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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. |
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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. |
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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. |