Book ChapterDOI
Revisiting hyperspectral remote sensing: origin, processing, applications and way forward
Prashant K. Srivastava,Ramandeep Kaur M. Malhi,Prem Chandra Pandey,Akash Anand,Prachi Singh,Manish Kumar Pandey,Ayushi Gupta +6 more
- pp 3-21
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TLDR
This chapter discusses the origin of hyperspectral remote sensing, its importance, preprocessing, inversion models suitable for hyperspectrals, as well as several possible applications, including but not limited to, vegetation analysis, agriculture, urban, water quality, and mineral identification.Abstract:
After several years of research and development in hyperspectral imaging systems that enriched our knowledge and enhanced our capacity to explore the Earth, these systems have been widely accepted by the remote sensing community. They have evolved as major techniques and have now entered the mainstream of the earth observation data users. This chapter discusses the origin of hyperspectral remote sensing, its importance, preprocessing, inversion models suitable for hyperspectral datasets, as well as several possible applications, including but not limited to, vegetation analysis, agriculture, urban, water quality, and mineral identification. The chapter concludes by looking at the way forward for hyperspectral remote sensing.read more
Citations
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Journal ArticleDOI
Synergistic evaluation of Sentinel 1 and 2 for biomass estimation in a tropical forest of India
Ramandeep Kaur M. Malhi,Sultanova Umida Rustamovna,Akash Anand,Prashant K. Srivastava,Sumit Kumar Chaudhary,Manish Kumar Pandey,Mukund Dev Behera,Amit Kumar,Prachi Singh,G. Sandhya Kiran +9 more
TL;DR: In this paper, two nonparametric machine learning algorithms viz Support Vector Machines (SVMs) with different kernel functions were employed for the prediction of above ground biomass using different combinations of VV, VH, Normalized Difference Vegetation Index (NDVI) and Incidence Angle (IA).
Journal ArticleDOI
An Integrated Spatiotemporal Pattern Analysis Model to Assess and Predict the Degradation of Protected Forest Areas
Ramandeep Kaur M. Malhi,Akash Anand,Prashant Srivastava,G. Sandhya Kiran,George P. Petropoulos,Christos Chalkias +5 more
TL;DR: This study is one of the few focusing on exploring and demonstrating the added value of the synergistic use of the Cellular Automata Markov Chain Model Coupled with Fragmentation Statistics in forest degradation analysis and prediction.
Journal ArticleDOI
Enhanced classification of hyperspectral images using improvised oversampling and undersampling techniques
TL;DR: The current work explored the solution to handle class imbalance by resampling the datasets before the application of classification algorithms by proposing a new computationally efficient class wise resampled technique which is based on SMOTE and centroid-based clustering.
Journal ArticleDOI
Band selection algorithms for foliar trait retrieval using AVIRIS-NG: a comparison of feature based attribute evaluators
Ramandeep Kaur M. Malhi,Manish Kumar Pandey,Akash Anand,Prashant K. Srivastava,George P. Petropoulos,Prachi Singh,G. Sandhya Kiran,B. K. Bhattarcharya +7 more
TL;DR: Interband information overlapping enhances redundancy in hyperspectral data, which makes identification of application-specific optimal bands essential for obtaining accurate information about folia...
Journal ArticleDOI
Optimal band characterization in reformation of hyperspectral indices for species diversity estimation
Akash Anand,Sultanova Umida Rustamovna,Ramandeep Kaur M. Malhi,Prashant K. Srivastava,Prachi Singh,Ashwini N. Mudaliar,George P. Petropoulos,G. Sandhya Kiran +7 more
TL;DR: In this article, the authors provided modified hyperspectral indices through detection of optimum bands for estimating species diversity within Shoolpaneshwar Wildlife Sanctuary (SWS) in India.
References
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Journal ArticleDOI
Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods
Jochem Verrelst,Z. Malenovsky,Z. Malenovsky,Christiaan van der Tol,Gustau Camps-Valls,Jean-Philippe Gastellu-Etchegorry,Philip Lewis,Philip Lewis,Peter North,Jose Moreno +9 more
TL;DR: In this article, a review of state-of-the-art retrieval methods that have been applied in experimental imaging spectroscopy studies inferring all kinds of vegetation biophysical variables is presented.
Journal ArticleDOI
Classification of hyperspectral data by decision trees and artificial neural networks to identify weed stress and nitrogen status of corn
Pradeep K. Goel,Shiv O. Prasher,Ramanbhai M. Patel,Jacques-André Landry,R. B. Bonnell,Alain A. Viau +5 more
TL;DR: In this paper, the authors evaluated the potential of decision tree classification algorithms for the classification of hyperspectral data, with the goal of discriminating between different growth scenarios in a cornfield.
Journal ArticleDOI
Airborne hyperspectral remote sensing to assess spatial distribution of water quality characteristics in large rivers: the Mississippi River and its tributaries in Minnesota.
TL;DR: In this paper, the spectral characteristics that distinguish waters dominated by several inherent optical properties (IOPs) were used to develop models to map water quality characteristics in optically complex waters.
Journal ArticleDOI
Hyperspectral versus multispectral crop-productivity modeling and type discrimination for the HyspIRI mission
Isabella Mariotto,Isabella Mariotto,Prasad S. Thenkabail,Alfredo Huete,E. Terrence Slonecker,Alexander Platonov +5 more
TL;DR: In this paper, the authors compared hyperspectral narrowband (HNB) versus multispectral broadband (MBB) reflectance data in studying irrigated cropland characteristics of five leading world crops (cotton, wheat, maize, rice, and alfalfa) with the objectives of: 1) modeling crop productivity, and 2) discriminating crop types.
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