| Implementation of a UAV–hyperspectral pushbroom imager for ecological monitoring JP Arroyo-Mora, M Kalacska, D Inamdar, R Soffer, O Lucanus, J Gorman, ... Drones 3 (1), 12, 2019 | 99 | 2019 |
| Estimating peatland water table depth and net ecosystem exchange: A comparison between satellite and airborne imagery M Kalacska, JP Arroyo-Mora, RJ Soffer, NT Roulet, TR Moore, ... Remote Sensing 10 (5), 687, 2018 | 60 | 2018 |
| Characterizing and mitigating sensor generated spatial correlations in airborne hyperspectral imaging data D Inamdar, M Kalacska, G Leblanc, JP Arroyo-Mora Remote Sensing 12 (4), 641, 2020 | 32 | 2020 |
| Airborne Hyperspectral Evaluation of Maximum Gross Photosynthesis, Gravimetric Water Content, and CO2 Uptake Efficiency of the Mer Bleue Ombrotrophic … JP Arroyo-Mora, M Kalacska, RJ Soffer, TR Moore, NT Roulet, S Juutinen, ... Remote Sensing 10 (4), 565, 2018 | 31 | 2018 |
| Remotely sensed carbon content: The role of tree composition and tree diversity CIB Wallis, AL Crofts, D Inamdar, JP Arroyo-Mora, M Kalacska, É Laliberté, ... Remote Sensing of Environment 284, 113333, 2023 | 21 | 2023 |
| The directly-georeferenced hyperspectral point cloud: preserving the integrity of hyperspectral imaging data D Inamdar, M Kalacska, JP Arroyo-Mora, G Leblanc Frontiers in Remote Sensing 2, 675323, 2021 | 16 | 2021 |
| The correlation coefficient as a simple tool for the localization of errors in spectroscopic imaging data D Inamdar, G Leblanc, RJ Soffer, M Kalacska Remote sensing 10 (2), 231, 2018 | 12 | 2018 |
| Spatial response resampling (SR2): Accounting for the spatial point spread function in hyperspectral image resampling D Inamdar, M Kalacska, PO Darko, JP Arroyo-Mora, G Leblanc MethodsX 10, 101998, 2023 | 8 | 2023 |
| Implementation of the directly-georeferenced hyperspectral point cloud D Inamdar, M Kalacska, G Leblanc, JP Arroyo-Mora MethodsX 8, 101429, 2021 | 7 | 2021 |
| Implementation of a UAV–Hyperspectral Pushbroom Imager for Ecological Monitoring. Drones 3, 12 JP Arroyo-Mora, M Kalacska, D Inamdar, R Soffer, O Lucanus, J Gorman, ... | 6 | 2019 |
| Limitations of a Multispectral UAV Sensor for Satellite Validation and Mapping Complex Vegetation B Cottrell, M Kalacska, JP Arroyo-Mora, O Lucanus, D Inamdar, T Løke, ... Remote Sensing 16 (13), 2463, 2024 | 5 | 2024 |
| Water column compensation workflow for hyperspectral imaging data D Inamdar, GSL Rowan, M Kalacska, JP Arroyo-Mora MethodsX 9, 101601, 2022 | 4 | 2022 |
| Multi-scale spectral separability of submerged aquatic vegetation species in a freshwater ecosystem GSL Rowan, M Kalacska, D Inamdar, JP Arroyo-Mora, R Soffer Frontiers in Environmental Science 9, 760372, 2021 | 4 | 2021 |
| Exploring the spectral variation hypothesis for α-and β-diversity: a comparison of open vegetation and forests CIB Wallis, S Kothari, JR Jantzen, AL Crofts, S St-Jean, D Inamdar, ... Environmental Research Letters 19 (6), 064005, 2024 | 3 | 2024 |
| Linking aerial hyperspectral data to canopy tree biodiversity: An examination of the spectral variation hypothesis AL Crofts, CIB Wallis, S St‐Jean, S Demers‐Thibeault, D Inamdar, ... Ecological Monographs, e1605, 2024 | 3 | 2024 |
| Towards the Improvement of Hyperspectral Imaging Data: Limitations of the Raster Model and the Development of a Novel Point Cloud Data Format D Inamdar McGill University (Canada), 2022 | | 2022 |
