Hyperspectral Remote Sensing
Theory and Applications

Integrates hyperspectral analysis techniques for a variety of research applications, including the latest advances and methods

Prem Chandra Pandey (Edited by), Prashant K. Srivastava (Edited by), Heiko Balzter (Edited by), Bimal Bhattacharya (Edited by), George P. Petropoulos (Edited by)

9780081028940, Elsevier Science

Paperback / softback, published 7 August 2020

506 pages, 140 illustrations (40 in full color)
23.4 x 19 x 3.1 cm, 1.05 kg

"The editors have produced a detailed and state-of-the-art research monograph on hyperspectral remote sensing (HRS) and imaging modalities. This monograph should be of interest to image scientists and graduate students involved in HRS and imaging technologies. Beyond a review on HRS, the authors address airborne imaging spectrometers, anomalies in HRS images, atmosphere parameter retrieval and corrections. Readers interested in HRS applications for vegetation, urban research including water and wetland ecosystems resources or agricultural research will find a wealth of information, including case studies from India, South Africa, Ecuador and Nigeria. These case studies are enhanced by HRS images and advanced statistical analysis. Furthermore, a chapter on HRS multi-sensor and fusion capabilities can be found in connection with pollution detection and noninvasive detection of plant parasitic nematodes. HRS applications in soil and mineral explorations, which includes heavy metal pollution and future requirements for advanced sensor systems for satellite and airborne systems, should attract a wide readership." --OSA

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.

Section 1 Introduction to Hyperspectral Remote Sensing and Principles of Theory and Data Processing
1. Revisiting hyperspectral remote sensing: origin, processing, applications and way forward
2. Spectral smile correction for airborne imaging spectrometers
3. Anomaly detection in hyperspectral remote sensing images
4. Atmospheric parameter retrieval and correction using hyperspectral data
5. Hyperspectral image classifications and feature selection
Section 2 Hyperspectral Remote Sensing Application in Vegetation
6. Identification of functionally distinct plants using linear spectral mixture analysis
7. Estimation of chengal trees relative abundance using coarse spatial resolution hyperspectral systems
8. Hyperspectral remote sensing in precision agriculture: present status, challenges, and future trends
9. Discriminating tropical grasses grown under different nitrogen fertilizer regimes in KwaZulu-Natal, South Africa
Section 3 Hyperspectral Remote Sensing Application in Water, Snow, Urban Research
10. Effect of contamination and adjacency factors on snow using spectroradiometer and hyperspectral images
11. Remote sensing of inland water quality: a hyperspectral perspective
12. Efficacy of hyperspectral data for monitoring and assessment of wetland ecosystem
Section 4 Hyperspectral Remote Sensing Application in Soil and Mineral Exploration
13. Spectroradiometry as a tool for monitoring soil contamination by heavy metals in a floodplain site
14. Hyperspectral remote sensing applications in soil: a review
15. Mineral exploration using hyperspectral data
16. Metrological hyperspectral image analysis through spectral differences
Section 5 Hyperspectral Remote Sensing: Multi-sensor, Fusion and Indices applications for Pollution
Detection and Other Applications
17. Improving the detection of cocoa bean fermentation-related changes using image fusion
18. Noninvasive detection of plant parasitic nematodes using hyperspectral and other remote sensing systems
19. 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 Delta
20. Hyperspectral vegetation indices to detect hydrocarbon pollution
Section 6 Hyperspectral Remote Sensing: Challenges, Future Pathway for Research & Emerging Applications
21. Future perspectives and challenges in hyperspectral remote sensing

Subject Areas: Geophysics [PHVG]