Remote Sensing Image Analysis: Including The Spatial Domain [electronic resource] /

Remote Sensing image analysis is mostly done using only spectral information on a pixel by pixel basis. Information captured in neighbouring cells, or information about patterns surrounding the pixel of interest often provides useful supplementary information. This book presents a wide range of innovative and advanced image processing methods for including spatial information, captured by neighbouring pixels in remotely sensed images, to improve image interpretation or image classification. Presented methods include different types of variogram analysis, various methods for texture quantification, smart kernel operators, pattern recognition techniques, image segmentation methods, sub-pixel methods, wavelets and advanced spectral mixture analysis techniques. Apart from explaining the working methods in detail a wide range of applications is presented covering land cover and land use mapping, environmental applications such as heavy metal pollution, urban mapping and geological applications to detect hydrocarbon seeps. The book is meant for professionals, PhD students and graduates who use remote sensing image analysis, image interpretation and image classification in their work related to disciplines such as geography, geology, botany, ecology, forestry, cartography, soil science, engineering and urban and regional planning.

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Bibliographic Details
Main Authors: Jong, Steven M. De. editor., Meer, Freek D. Van der. editor., SpringerLink (Online service)
Format: Texto biblioteca
Language:eng
Published: Dordrecht : Springer Netherlands : Imprint: Springer, 2004
Subjects:Physics., Science., Geology., Geotechnical engineering., Remote sensing., Optics., Optoelectronics., Plasmons (Physics)., Nature., Environment., Optics, Optoelectronics, Plasmonics and Optical Devices., Science, general., Popular Science in Nature and Environment., Remote Sensing/Photogrammetry., Geotechnical Engineering & Applied Earth Sciences.,
Online Access:http://dx.doi.org/10.1007/978-1-4020-2560-0
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