Remotely sensed images are an indispensable tool to researchers in disciplines such as cartography, forestry and geology in which mapping by satellite or aircraft is often a far more acurate, efficient and cost-effective method than conventional survey. Most users of remote sensing data are now familiar with using photographic images prepared to standard prescriptions by others to relate colours or grey tones to what actually exists on the ground. This book is aimed at the discipline-oriented user who wishes to move away from these traditional photographic interpretation methods towards interactive analysis systems. Such systems permit the classification of the digital data in ways that enable locations and quantitative information on specific themes to be extracted and portrayed. The empasis is upon the integration of these new techniques into existing discipline skills: the user is not expected to become a 'computer operator'. The book covers the fundamental theory of image classification, and illustrates it with practical examples in the form of a structured outline of a total research project. It is therefore an essential reference manual to 'sit at the elbow' of the user working with an image processing system for remotely sensed data.
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Für höhere Schule und Studium
Für Beruf und Forschung
Maße
Höhe: 235 mm
Breite: 156 mm
ISBN-13
978-0-85274-496-3 (9780852744963)
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Schweitzer Klassifikation
Autor*in
Department of Lands and Survey, Wellington, New Zealand
Department of Lands and Survey, Wellington, New Zealand
Photointerpretation to digital classification. Spectral signatures and the sensed pixel. Levels of refinement in a classification. An introduction to the Landsat multispectral scanner. An introduction to an aircraft multiband scanner system. Introduction to image enhancement and analysis. The classification of ground cover classes and measures of their separability. Image registration. An analysis pathway to classification products. The presentation of classification data. Determining the confidence level for a classification. Forest inventory from Landsat imagery. Land cover mapping from Landsat. Classification of agricultural land cover from Landsat. Classification of agricultural land cover from aircraft scanner data. Bibliography. Appendix. Glossary. Index.
blurb
Remotely sensed images are an indispensable tool to researchers in disciplines such as cartography, forestry and geology in which mapping by satellite or aircraft is often a far more acurate, efficient and cost-effective method than conventional survey. Most users of remote sensing data are now familiar with using photographic images prepared to standard prescriptions by others to relate colours or grey tones to what actually exists on the ground. This book is aimed at the discipline-oriented user who wishes to move away from these traditional photographic interpretation methods towards interactive analysis systems. Such systems permit the classification of the digital data in ways that enable locations and quantitative information on specific themes to be extracted and portrayed. The empasis is upon the integration of these new techniques into existing discipline skills: the user is not expected to become a 'computer operator'. The book covers the fundamental theory of image classification, and illustrates it with practical examples in the form of a structured outline of a total research project. It is therefore an essential reference manual to 'sit at the elbow' of the user working with an image processing system for remotely sensed data.
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