| Assessing very high resolution UAV imagery for monitoring forest health during a simulated disease outbreak JP Dash, MS Watt, GD Pearse, M Heaphy, HS Dungey ISPRS Journal of Photogrammetry and Remote Sensing 131, 1-14, 2017 | 400 | 2017 |
| Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission L Duncanson, JR Kellner, J Armston, R Dubayah, DM Minor, S Hancock, ... Remote Sensing of Environment 270, 112845, 2022 | 180 | 2022 |
| UAV multispectral imagery can complement satellite data for monitoring forest health JP Dash, GD Pearse, MS Watt Remote Sensing 10 (8), 1216, 2018 | 147 | 2018 |
| Comparison of high-density LiDAR and satellite photogrammetry for forest inventory GD Pearse, JP Dash, HJ Persson, MS Watt ISPRS journal of photogrammetry and remote sensing 142, 257-267, 2018 | 86 | 2018 |
| Early detection of invasive exotic trees using UAV and manned aircraft multispectral and LiDAR Data JP Dash, MS Watt, TSH Paul, J Morgenroth, GD Pearse Remote Sensing 11 (15), 1812, 2019 | 77 | 2019 |
| A comparison of UAV laser scanning, photogrammetry and airborne laser scanning for precision inventory of small-forest properties S Puliti, JP Dash, MS Watt, J Breidenbach, GD Pearse Forestry: An International Journal of Forest Research 93 (1), 150-162, 2020 | 68 | 2020 |
| Phenotyping whole forests will help to track genetic performance HS Dungey, JP Dash, D Pont, PW Clinton, MS Watt, EJ Telfer Trends in Plant Science 23 (10), 854-864, 2018 | 65 | 2018 |
| Optimising prediction of forest leaf area index from discrete airborne lidar GD Pearse, J Morgenroth, MS Watt, JP Dash Remote Sensing of Environment 200, 220-239, 2017 | 63 | 2017 |
| Comparing parametric and non-parametric methods of predicting Site Index for radiata pine using combinations of data derived from environmental surfaces, satellite imagery and … MS Watt, JP Dash, S Bhandari, P Watt Forest Ecology and Management 357, 1-9, 2015 | 54 | 2015 |
| Detecting and mapping tree seedlings in UAV imagery using convolutional neural networks and field-verified data GD Pearse, AYS Tan, MS Watt, MO Franz, JP Dash ISPRS Journal of Photogrammetry and Remote Sensing 168, 156-169, 2020 | 53 | 2020 |
| Comparison of models describing forest inventory attributes using standard and voxel-based lidar predictors across a range of pulse densities GD Pearse, MS Watt, JP Dash, C Stone, G Caccamo International Journal of Applied Earth Observation and Geoinformation 78 …, 2019 | 45 | 2019 |
| Methods for estimating multivariate stand yields and errors using k-NN and aerial laser scanning JP Dash, HM Marshall, B Rawley Forestry: An International Journal of Forest Research 88 (2), 237-247, 2015 | 36 | 2015 |
| Characterising forest structure using combinations of airborne laser scanning data, RapidEye satellite imagery and environmental variables JP Dash, MS Watt, S Bhandari, P Watt Forestry 89 (2), 159-169, 2016 | 35 | 2016 |
| Remote sensing for precision forestry J Dash, D Pont, R Brownlie, A Dunningham, M Watt, G Pearse New Zealand Journal of Forestry 60 (4), 12-24, 2016 | 32 | 2016 |
| Application of remote sensing technologies to identify impacts of nutritional deficiencies on forests MS Watt, GD Pearse, JP Dash, N Melia, EMC Leonardo ISPRS Journal of Photogrammetry and Remote Sensing 149, 226-241, 2019 | 30 | 2019 |
| Taking a closer look at invasive alien plant research. A review of the current state, opportunities, and future directions for UAVs JP Dash, MS Watt, TSH Paul, J Morgenroth, R Hartley Methods in Ecology and Evolution, 2019 | 29 | 2019 |
| Forest-scale phenotyping: Productivity characterisation through machine learning M Bombrun, JP Dash, D Pont, MS Watt, GD Pearse, HS Dungey Frontiers in Plant Science 11, 99, 2020 | 26 | 2020 |
| Spatial prediction of optimal final stand density for even-aged plantation forests using productivity indices MS Watt, MO Kimberley, JP Dash, D Harrison Canadian Journal of Forest Research 47 (4), 527-535, 2017 | 24 | 2017 |
| Multi-sensor modelling of a forest productivity index for radiata pine plantations MS Watt, JP Dash, P Watt, S Bhandari New Zealand Journal of Forestry Science 46, 1-14, 2016 | 23 | 2016 |
| UAVs for data collection-plugging the gap M Heaphy, MS Watt, JP Dash, GD Pearse NZJ For 62, 23-30, 2017 | 20 | 2017 |
Michael WattScion在 scionresearch.com 的电子邮件经过验证
