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Spatial Statistics for Remote Sensing

Sofort lieferbar | Lieferzeit: Sofort lieferbar I
ISBN-13:
9780306476471
Veröffentl:
2005
Seiten:
284
Autor:
A. Stein
Serie:
1, Remote Sensing and Digital Image Processing
eBook Typ:
PDF
eBook Format:
EPUB
Kopierschutz:
1 - PDF Watermark
Sprache:
Englisch
Beschreibung:

This book is a collection of papers on spatial statistics for remote sensing. The book emerges from a study day that was organized in 1996 at the International Institute for Aerospace Survey and Earth Sciences, ITC, in Enschede, The Netherlands. It was by several means a memorable event. The beautiful new building, according to a design by the famous modern Dutch architect Max van Huet was just opened, and this workshop was the first to take place there. Of course, much went wrong during the workshop, in particular as the newest electronic equipment regularly failed. But the workshop attrackted more than hundred attendants, and was generally well received. The results of the workshop have been published in Stein et al. (1998). The aim of the workshop was to address issues of spatial statistics for remote sensing. The ITC has a long history on collecting and analyzing satellite and other remote sensing data, but its involvement into spatial statistics is of a more recent date. Uncertainties in remote sensing images and the large amounts of data in many spectral bands are now considered to be of such an impact that it requires a separate approach from a statistical point of view. To quote from the justification of the study day, we read: Modern communication means such as remote sensing require an advanced use of collected data. Satellites collect data with different resolution on different spectral bands.
Description of the data used in this book.- Some basic elements of statistics.- Physical principles of optical remote sensing.- Remote sensing and geographical information systems.- Spatial Statistics.- Spatial prediction by linear kriging.- Issues of scale and optimal pixel size.- Conditional Simulation: An alternative to estimation for achieving mapping objectives.- Supervised image classification.- Unsupervised class detection by adaptive sampling and density estimation.- Image classification through spectral unmixing.- Accuracy assessment of spatial information.- Spatial sampling schemes for remote sensing.- Remote sensing and decision support systems.

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