Grant D. Pearse
Orcid: 0000-0001-5277-2449
According to our database1,
Grant D. Pearse
authored at least 12 papers
between 2017 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
Early Prediction of Regional Red Needle Cast Outbreaks Using Climatic Data Trends and Satellite-Derived Observations.
Remote. Sens., April, 2024
Automatic Detection of Phytophthora pluvialis Outbreaks in Radiata Pine Plantations Using Multi-Scene, Multi-Temporal Satellite Imagery.
Remote. Sens., January, 2024
2023
Unsupervised Methodology for Large-Scale Tree Seedling Mapping in Diverse Forestry Settings Using UAV-Based RGB Imagery.
Remote. Sens., November, 2023
FOR-instance: a UAV laser scanning benchmark dataset for semantic and instance segmentation of individual trees.
CoRR, 2023
2022
Assessing the Potential of Backpack-Mounted Mobile Laser Scanning Systems for Tree Phenotyping.
Remote. Sens., 2022
2021
Deep Learning and Phenology Enhance Large-Scale Tree Species Classification in Aerial Imagery during a Biosecurity Response.
Remote. Sens., 2021
A New Drone Laser Scanning Benchmark Dataset for Characterization of Single-Tree and Forest Biophysical Properties.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021
2020
An Assessment of High-Density UAV Point Clouds for the Measurement of Young Forestry Trials.
Remote. Sens., 2020
2019
Early Detection of Invasive Exotic Trees Using UAV and Manned Aircraft Multispectral and LiDAR Data.
Remote. Sens., 2019
Comparison of models describing forest inventory attributes using standard and voxel-based lidar predictors across a range of pulse densities.
Int. J. Appl. Earth Obs. Geoinformation, 2019
2018
UAV Multispectral Imagery Can Complement Satellite Data for Monitoring Forest Health.
Remote. Sens., 2018
2017
Combining Airborne Laser Scanning and Aerial Imagery Enhances Echo Classification for Invasive Conifer Detection.
Remote. Sens., 2017