Spectral library of crops and discrimination of major vegetables grown in the eastern Himalayan ecosystem: A proximal hyperspectral remote sensing approach

BU Choudhury, R Narzari, M Zafar, N Singh… - Ecological …, 2023 - Elsevier
Identifying, characterising and map**, unique vegetable crops grown on small mixed
lands in the eastern Himalayan mountain ecosystem (EHME) using traditional methods is a …

New generation hyperspectral sensors DESIS and PRISMA provide improved agricultural crop classifications

I Aneece, PS Thenkabail - Photogrammetric Engineering & …, 2022 - ingentaconnect.com
Using new remote sensing technology to study agricultural crops will support advances in
food and water security. The recently launched, new generation spaceborne hyperspectral …

Classifying crop types using two generations of hyperspectral sensors (Hyperion and DESIS) with machine learning on the cloud

I Aneece, PS Thenkabail - Remote Sensing, 2021 - mdpi.com
Advances in spaceborne hyperspectral (HS) remote sensing, cloud-computing, and
machine learning can help measure, model, map and monitor agricultural crops to address …

New generation hyperspectral data from DESIS compared to high spatial resolution PlanetScope data for crop type classification

I Aneece, D Foley, P Thenkabail… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Thoroughly investigating the characteristics of new generation hyperspectral and high
spatial resolution spaceborne sensors will advance the study of agricultural crops …

Remote Sensing Handbook, Volume III: Agriculture, Food Security, Rangelands, Vegetation, Phenology, and Soils

PS Thenkabail - Remote Sensing Handbook, Volume III, 2024 - taylorfrancis.com
This chapter provides a summary of each of the 16 chapters in Volume III of the six-volume
Remote Sensing Handbook (Second Edition). The topics covered in the chapters of Volume …

Machine Learning and New-Generation Spaceborne Hyperspectral Data Advance Crop Type Map**

I Aneece, PS Thenkabail, R McCormick… - … & Remote Sensing, 2024 - ingentaconnect.com
Hyperspectral sensors provide near-continuous spectral data that can facilitate
advancements in agricultural crop classification and characterization, which are important …

Hyperspectral remote sensing for terrestrial applications

PS Thenkabail, I Aneece, P Teluguntla… - Remote Sensing …, 2016 - api.taylorfrancis.com
Remote Sensing Handbook, Volume III; Agriculture, Food Security, Rangelands, Vegetation,
Phenology, and Soils; Second Edition Page 1 285 10 DOI: 10.1201/9781003541165-12 …

Artificial Neural Network Multi-layer Perceptron Models to Classify California's Crops using Harmonized Landsat Sentinel (HLS) Data

R McCormick, PS Thenkabail, I Aneece… - … & Remote Sensing, 2025 - ingentaconnect.com
Advances in remote sensing and machine learning are enhancing cropland classification,
vital for global food and water security. We used multispectral Harmonized Landsat 8 …

New generation and old generation hyperspectral remote sensing data and their comparisons with multispectral data in the study of global agriculture and vegetation

PS Thenkabail, I Aneece, P Teluguntla… - IGARSS 2022-2022 …, 2022 - ieeexplore.ieee.org
Great advances in remote sensing are taking place with new generation of spaceborne
hyperspectral sensors such as the DESIS and PRISMA which are already acquiring data for …

Summary Chapter, Volume II, Remote Sensing Handbook: Image Processing, Change Detection, GIS, and Spatial Data Analysis

PS Thenkabail - Remote Sensing Handbook, Volume II, 2024 - taylorfrancis.com
This chapter provides a summary of each of the 16 chapters in Volume II of the six-volume
Remote Sensing Handbook (Second Edition). The topics covered in the chapters of Volume …