Michael S. Watt

According to our database, Michael S. Watt authored at least 13 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

Early Detection of Myrtle Rust on Pōhutukawa Using Indices Derived from Hyperspectral and Thermal Imagery.

Michael S. Watt, Honey Jane Estarija, Michael Bartlett, Russell Main, Dalila Pasquini, Warren Yorston, Emily McLay, Maria Zhulanov, Kiryn Dobbie, Katherine Wardhaugh, Zulfikar Hossain, Stuart Fraser, Henning Buddenbaum

Remote. Sens., March, 2024

Automatic Detection of Phytophthora pluvialis Outbreaks in Radiata Pine Plantations Using Multi-Scene, Multi-Temporal Satellite Imagery.

Nicolò Camarretta, Grant D. Pearse, Benjamin S. C. Steer, Emily McLay, Stuart Fraser, Michael S. Watt

Remote. Sens., January, 2024

2023

Unsupervised Methodology for Large-Scale Tree Seedling Mapping in Diverse Forestry Settings Using UAV-Based RGB Imagery.

Sadeepa Jayathunga, Grant D. Pearse, Michael S. Watt

Remote. Sens., November, 2023

Climate-Change-Driven Droughts and Tree Mortality: Assessing the Potential of UAV-Derived Early Warning Metrics.

Ewane Basil Ewane, Midhun Mohan, Shaurya Bajaj, G. A. Pabodha Galgamuwa, Michael S. Watt, Pavithra S. Pitumpe Arachchige, Andrew T. Hudak, Gabriella Richardson, Nivedhitha Ajithkumar, Shruthi Srinivasan, Ana Paula Dalla Corte, Daniel J. Johnson, Eben North Broadbent, Sergio de-Miguel, Margherita Bruscolini, Derek J. N. Young, Shahid Shafai, Meshal M. Abdullah, Wan Shafrina Wan Mohd Jaafar, Willie Doaemo, Carlos Alberto Silva, Adrián Cardil

Remote. Sens., 2023

2022

A Mixed Methods Approach for Fuel Characterisation in Gorse (Ulex europaeus L.) Scrub from High-Density UAV Laser Scanning Point Clouds and Semantic Segmentation of UAV Imagery.

Robin J. L. Hartley, Sam J. Davidson, Michael S. Watt, Peter D. Massam, Samuel Aguilar-Arguello, Katharine O. Melnik, H. Grant Pearce, Veronica R. Clifford

Remote. Sens., 2022

2021

Deep Learning and Phenology Enhance Large-Scale Tree Species Classification in Aerial Imagery during a Biosecurity Response.

Grant D. Pearse, Michael S. Watt, Julia Soewarto, Alan Yu Shyang Tan

Remote. Sens., 2021

A New Drone Laser Scanning Benchmark Dataset for Characterization of Single-Tree and Forest Biophysical Properties.

Stefano Puliti, Grant D. Pearse, Michael S. Watt, Edward T. A. Mitchard, Iain McNicol, Magnus Bremer, Martin Rutzinger, Peter Surový, Luke Wallace, Markus Hollaus, Rasmus Astrup

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.

Robin J. L. Hartley, Ellen Mae Leonardo, Peter D. Massam, Michael S. Watt, Honey Jane Estarija, Liam Wright, Nathanael Melia, Grant D. Pearse

Remote. Sens., 2020

2019

Preprocessing Ground-Based Visible/Near Infrared Imaging Spectroscopy Data Affected by Smile Effects.

Henning Buddenbaum, Michael S. Watt, Rebecca C. Scholten, Joachim Hill

Sensors, 2019

Early Detection of Invasive Exotic Trees Using UAV and Manned Aircraft Multispectral and LiDAR Data.

Jonathan P. Dash, Michael S. Watt, Thomas S. H. Paul, Justin Morgenroth, Grant D. Pearse

Remote. Sens., 2019

Comparison of models describing forest inventory attributes using standard and voxel-based lidar predictors across a range of pulse densities.

Grant D. Pearse, Michael S. Watt, Jonathan P. Dash, Christine Stone, Gabriele Caccamo

Int. J. Appl. Earth Obs. Geoinformation, 2019

2018

UAV Multispectral Imagery Can Complement Satellite Data for Monitoring Forest Health.

Jonathan P. Dash, Grant D. Pearse, Michael S. Watt

Remote. Sens., 2018

2017

Combining Airborne Laser Scanning and Aerial Imagery Enhances Echo Classification for Invasive Conifer Detection.

Jonathan P. Dash, Grant D. Pearse, Michael S. Watt, Thomas S. H. Paul

Remote. Sens., 2017