Description
Hyperspectral Remote Sensing: Theory and Applications offers the latest information on the techniques, advances and wide-ranging applications of hyperspectral remote sensing, such as forestry, agriculture, water resources, soil and geology, among others. The book also presents hyperspectral data integration with other sources, such as LiDAR, Multi-spectral data, and other remote sensing techniques. Researchers who use this resource will be able to understand and implement the technology and data in their respective fields. As such, it is a valuable reference for researchers and data analysts in remote sensing and Earth Observation fields and those in ecology, agriculture, hydrology and geology.- Includes the theory of hyperspectral remote sensing, along with techniques and applications across a variety of disciplines- Presents the processing, methods and techniques utilized for hyperspectral remote sensing and in-situ data collection- Provides an overview of the state-of-the-art, including algorithms, techniques and case studies
Table of Contents
Section 1 Introduction to Hyperspectral Remote Sensing and Principles of Theory and Data Processing1. Revisiting hyperspectral remote sensing: origin, processing, applications and way forward2. Spectral smile correction for airborne imaging spectrometers3. Anomaly detection in hyperspectral remote sensing images4. Atmospheric parameter retrieval and correction using hyperspectral data5. Hyperspectral image classifications and feature selectionSection 2 Hyperspectral Remote Sensing Application in Vegetation6. Identification of functionally distinct plants using linear spectral mixture analysis7. Estimation of chengal trees relative abundance using coarse spatial resolution hyperspectral systems8. Hyperspectral remote sensing in precision agriculture: present status, challenges, and future trends9. Discriminating tropical grasses grown under different nitrogen fertilizer regimes in KwaZulu-Natal, South AfricaSection 3 Hyperspectral Remote Sensing Application in Water, Snow, Urban Research10. Effect of contamination and adjacency factors on snow using spectroradiometer and hyperspectral images11. Remote sensing of inland water quality: a hyperspectral perspective12. Efficacy of hyperspectral data for monitoring and assessment of wetland ecosystemSection 4 Hyperspectral Remote Sensing Application in Soil and Mineral Exploration13. Spectroradiometry as a tool for monitoring soil contamination by heavy metals in a floodplain site14. Hyperspectral remote sensing applications in soil: a review15. Mineral exploration using hyperspectral data16. Metrological hyperspectral image analysis through spectral differencesSection 5 Hyperspectral Remote Sensing: Multi-sensor, Fusion and Indices applications for PollutionDetection and Other Applications17. Improving the detection of cocoa bean fermentation-related changes using image fusion18. Noninvasive detection of plant parasitic nematodes using hyperspectral and other remote sensing systems19. Evaluating the performance of vegetation indices for detecting oil pollution effects on vegetation using hyperspectral (Hyperion EO-1) and multispectral (Sentinel-2A) data in the Niger Delta20. Hyperspectral vegetation indices to detect hydrocarbon pollutionSection 6 Hyperspectral Remote Sensing: Challenges, Future Pathway for Research & Emerging Applications21. Future perspectives and challenges in hyperspectral remote sensing
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