Deep Inamdar

McGill University
Candidat Ph.D.
superviseur(e): Margaret Kalacska
George Leblanc, McGill University
Début: 2019-01-01
Fin: 2022-05-01

Projet

Novel tools for the acquisition, processing, analysis and quality assessment of hyperspectral imaging data

Mots-clés

Hyperspectral imaging, Data Processing, Peatlands

Publications

1- Estimating Peatland Water Table Depth and Net Ecosystem Exchange: A Comparison between Satellite and Airborne Imagery
Kalacska, Margaret, J. Arroyo-Mora, Raymond Soffer, Nigel Roulet, Tim Moore, Elyn Humphreys, George Leblanc, Oliver Lucanus, Deep Inamdar
2018 Remote Sensing

2- Implementation of a UAV–Hyperspectral Pushbroom Imager for Ecological Monitoring
Arroyo-Mora, J., Margaret Kalacska, Deep Inamdar, Raymond Soffer, Oliver Lucanus, Janine Gorman, Tomas Naprstek, Erica Schaaf, Gabriela Ifimov, Kathryn Elmer, George Leblanc
2019 Drones

3- Characterizing and Mitigating Sensor Generated Spatial Correlations in Airborne Hyperspectral Imaging Data
Inamdar, Deep, Margaret Kalacska, George Leblanc, J. Pablo Arroyo-Mora
2020 Remote Sensing

4- The Directly-Georeferenced Hyperspectral Point Cloud: Preserving the Integrity of Hyperspectral Imaging Data
Inamdar, Deep, Margaret Kalacska, J. Pablo Arroyo-Mora, George Leblanc
2021 Frontiers in Remote Sensing

5- Implementation of the directly-georeferenced hyperspectral point cloud
Inamdar, Deep, Margaret Kalacska, George Leblanc, J. Pablo Arroyo-Mora
2021 MethodsX