£161.11

CRC Press Remote Sensing of Natural Resources - Volume 9

148 black & white illustrations, 45 colo

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Description

Remote Sensing of Natural Resources: Volume 9 from the Remote Sensing Applications Series explores advanced remote sensing systems and algorithms for comprehensive natural resource evaluation. This authoritative guide covers image processing, enhancement, feature extraction, data fusion, image classification, and image-based modelling techniques. The book addresses practical applications including sampling design, land use and land cover classification, natural landscape and ecosystem assessment, forestry, agriculture, biomass and carbon-cycle modelling, and wetland classification with dynamics monitoring. Designed for higher education students and professionals, it bridges cutting-edge remote sensing technology with real-world resource management challenges, providing essential knowledge for environmental scientists, geographers, and land management specialists seeking to master modern remote sensing methodologies.

Key Features

Remote Sensing of Natural Resources covers advanced image processing, enhancement and feature extraction algorithms for professional resource analysis.

Includes comprehensive data fusion and image classification techniques for accurate land use and land cover mapping applications.

Addresses image-based modelling and sampling design methods for efficient natural resource evaluation and assessment.

Features applications in forestry, agriculture and ecosystem monitoring with biomass and carbon-cycle modelling frameworks.

Provides wetland classification and dynamics monitoring protocols essential for environmental management and conservation planning.

Part of the Remote Sensing Applications Series, offering expert-level content for higher education and professional development.

Covers map accuracy assessment and quality control procedures to ensure reliability of remote sensing data and interpretations.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
12 July 2013
Listed Since
29 February 2012

Barcode

No barcode data available

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