Hyperspectral remote sensing : theory and applications /: theory and applications. (2020)

• Record Type: Book
• Further Information: Note: Edited by Prem Chandra Pandey, Prashant K. Srivastava, Heiko Balzter, Bimal Bhattacharya, George P. Petropoulos.
• Editors: Pandey, Prem Chandra, 1985-; Srivastava, Prashant K; Balzter, Heiko; Bhattacharya, Bimal; Petropoulos, George P
• Contents: 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
• Publisher Details: Amsterdam : Elsevier
• Publication Date: 2020
• Extent: 1 online resource, illustrations (black and white, and colour)
• Subjects: 621.3678; Remote sensing; Hyperspectral imaging
• Languages: English
• ISBNs: 9780081028957
• Related ISBNs: 9780081028940
• Notes: Note: Description based on CIP data; resource not viewed.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.