Hyperspectral Remote Sensing: Theory and Applications

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.

Author Biography: Dr. Prem Chandra Pandey received his PhD degree (2015) from Centre for Landscape and Climate Research (CLCR) Department of Geography, University of Leicester, United Kingdom, under the Commonwealth Scholarship and Fellowship Plan (CSFP). He received his BSc degree in Botany (Hons.) from Institute of Sciences, Banaras Hindu University (2005), M.Sc. degree in Environmental Sciences (2007) from Institute of Sciences, BHU and M.Tech in Remote Sensing (2009) from Birla Institute of Technology (BIT) Mesra Ranchi, India. Dr Pandey is currently working as Assistant Professor in Center for Environmental Sciences & Engineering, Shiv Nadar University, Greater Noida, India. He did his Post-Doctoral from Department of Geography and Human Environment, Faculty of Exact Sciences, Tel Aviv University Israel (2016-2017). Dr Pandey has worked as a National Post- Doctoral Fellow with Institute of Environment and Sustainable Development (IESD), Banaras Hindu University (BHU) Varanasi. He worked on remote sensing applications as Professional Research fellow in National Urban Information System (NUIS) funded by National Remote Sensing Centre (NRSC) Government of India at BIT Mesra Ranchi. Dr. Pandey has been a recipient of several prestigious International and National awards including Commonwealth Fellowship UK, INSPIRE fellowship, Ministry of Human Resource and Development (MHRD) Government of India, University Grant Commission (UGC) fellowships, Science and Engineering Research Board (SERB)-NPDF and IT Merit awards from Government of India. He has authored 30+ research articles published in international peer-reviewed journal articles, Edited 2 Books, 9 book chapters and presented his work in several conferences. Additionally, he is also a member of Indian Society of Geomatics (ISG), Indian Society of Remote Sensing (ISRS), SPIE, and Association of American Geographers (AAG). His research interests include forestry, environmental pollutant modeling, urban studies and agricultural studies. Dr. Srivastava is working in Hydrological Sciences, NASA Goddard Space Flight Center on SMAP satellite soil moisture retrieval algorithm development, instrumentation and simulation for various applications, and affiliated with IESD, Banaras Hindu University as a faculty. He received his PhD degree from Department of Civil Engineering, University of Bristol, Bristol, UK. He has published 100+ papers in peer-reviewed journals, published 4 books with reputed publishing houses and authored several book chapters and conference papers. Prof. Heiko Balzter received the Dipl.-Ing.Agr. (equivalent to M.Sc.) and the Dr.Agr. (Ph.D.) degrees from Justus-Liebig-University, Giessen, Germany, in 1994 and 1998, respectively. He is a Research Professor and the Director of the Centre for Landscape and Climate Research at the University of Leicester, Leicester, U.K and Official Development Assistance (ODA) Programme Leader in the NERC National Centre for Earth Observation. Before joining the University of Leicester, he was Head of the Section for Earth Observation at the Centre for Ecology and Hydrology, Monks Wood, U.K., where he worked from 1998 to 2006. His research interests include interactions of the water cycle with ecosystems across multiple spatial and temporal scales, pressures from climate change and land use change on ecosystem services, and the effects of spatial patterns and processes upon biological populations in evolving 3-D landscapes. Prof. Balzter holds the Royal Society Wolfson Research Merit Award (2011) and the Royal Geographical Society's Cuthbert Peek Award 'for advancing geographical knowledge of human impact through earth observation' (2015). He received the President's Cup for the Best Paper Annual Remote Sensing and Photogrammetry Society Conference (2009). Prof. Balzter chairs the BESS-EO working group on biodiversity, ecosystem services and Earth Observation, is a member of the NERC Future Landscapes Scoping Group, and UK representative on the Group on Earth Observations (GEO) Programme Board. He is leading the Copernicus Land Monitoring Service for the UK, which produces the CORINE land cover map. In the Forests 2020 project he is leading the Forest Cover Change Detection task. In GLOBBIOMASS, he is in charge of the regional case studies work package. He is Principal Investigator of the European Centre of Excellence in Earth Observation Research Training GIONET. Dr. Bimal Bhattacharya is associated with SAC ISRO Ahmedabad since 2000 as Scientist SG. He received his PhD degree (Agriculture Physics) in 1995 and MSc degree (Agriculture Physics) in 1991, from Indian Agricultural Research Institute, New Delhi. He served as a scientist in the Indian Council of Agricultural research (ICAR) from 1995 to 2000. He has been working in different scientific capacities at Space Applications Centre, ISRO, Ahmedabad, Gujarat since 2000. He is involved in developing satellite-based agro-met products and their utilization in National Agro-met Advisory Services in India. He led the development of satellite-based surface energy balance modeling over Indian terrestrial ecosystems especially with remote sensing data from a suite (INSAT VHRR, 3A CCD, 3D Imager) of Indian geostationary sensors. He led an ISRO-Geosphere-Biosphere Programme (GBP) national-scale science project on Energy and Mass Exchange in vegetative Systems. He is also the principal investigator on the land surface processes in the ISRO-CNES MEGHA-TROPIQUE mission and science member of MoES-NERC Indo-UK Monsoon project called INCOMPASS. He is the science leader of AVIRIS-NG airborne hyperspectral mission in Indian and also the science co-chair of ISRO-CNES (Indo-French) thermal infrared mission. He is currently ISRO representative in CEOS for land surface imaging. He is the recipient of the P. R. Pisharoty award from Indian Society of Remote Sensing and young scientist award from AsiaFlux, Japan sponsored by Japanese Space Agency, JAXA. He also received ISRO team member award. He is the teaching faculty in the UN-sponsored course on "Satellite Meteorology and Global Climate" under Centre for Space Science Technology and Education for Asia-Pacific (CSSTEAP). He has published more than 50 research papers in peer-reviewed international as well as national journals. Dr. George P. Petropoulos (PhD, King's College London UK) is an Associate Researcher in Remote Sensing & GIS at the Dept. of Soil & Water Resources of the Institute of Industrial & Forage Crops (IIFC) of the Hellenic Agricultural Organization "ELGO DEMETER", Greece. He also holds a Marie Curie Fellowships with the Dept. of Mineral Resources Engineering of the Technical University of Crete in Greece. Previously (until 02/2018) he was Associate Professor in Remote Sensing & GIS at the Dept. of Geography & Earth Sciences, Aberystwyth University, UK. His research is focusing on the exploitation of technologically advanced EO sensors and synergistic multi-sensor EO modelling & GIS geospatial techniques for obtaining spatiotemporal estimates of key state variables characterising land surface processes. He is author/co-author so far of +70 peer-reviewed journal articles, +22 book chapters, and editor/co-editor of 4 books published by Elsevier and Taylor & Francis.

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