Jonathan Dash
Jonathan Dash
Remote Sensing and Forestry Scientist
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Cited by
Cited by
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
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
UAV multispectral imagery can complement satellite data for monitoring forest health
JP Dash, GD Pearse, MS Watt
Remote Sensing 10 (8), 1216, 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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
UAVs for data collection-plugging the gap
M Heaphy, MS Watt, JP Dash, GD Pearse
NZJ For 62, 23-30, 2017
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