Yuri Shendryk

Evaluation of satellite remote sensing pathways for mapping and monitoring of gamba grass for the Savanna Fire Management Methodology

S. Levick, S. Setterfield, N. Rossiter-Rachor, 2019 .

A multidisciplinary approach to locating clandestine gravesites in cold cases: Combining geographic profiling, LiDAR, and near surface geophysics

Justin Ellis, X. Mallett, I. Moffat, 2022, Forensic science international. Synergy.

Fusing GEDI with earth observation data for large area aboveground biomass mapping

Yuri Shendryk, 2022, Int. J. Appl. Earth Obs. Geoinformation.

Deep learning for multi-modal classification of cloud, shadow and land cover scenes in PlanetScope and Sentinel-2 imagery

Yannik Rist, Catherine Ticehurst, Peter J. Thorburn, 2019, ISPRS Journal of Photogrammetry and Remote Sensing.

Estimating Pasture Biomass Using Sentinel-2 Imagery and Machine Learning

Dave Henry, Yuri Shendryk, Yun Chen, 2021, Remote. Sens..

Fine-scale prediction of biomass and leaf nitrogen content in sugarcane using UAV LiDAR and multispectral imaging

Yannik Rist, Peter J. Thorburn, Robert Garrard, 2020, Int. J. Appl. Earth Obs. Geoinformation.

Leveraging Airborne LiDAR Data and Gradient Boosting for Mapping the Density of Different Sized Trees

Yuri Shendryk, Emma Gorrod, E. Gorrod, 2021, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

Leveraging High-Resolution Satellite Imagery and Gradient Boosting for Invasive Weed Mapping

Shaun R. Levick, Samantha A. Setterfield, Yuri Shendryk, 2020, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

Identification of Suitable Sites Using GIS for Rainwater Harvesting Structures to Meet Irrigation Demand

Ataur Rahman, P. Preeti, Yuri Shendryk, 2022, Water.

Monitoring sugarcane growth response to varying nitrogen application rates: A comparison of UAV SLAM LiDAR and photogrammetry

Farid Kendoul, Chris Roelfsema, Stuart R. Phinn, 2019, Int. J. Appl. Earth Obs. Geoinformation.

Integrating satellite imagery and environmental data to predict field-level cane and sugar yields in Australia using machine learning

Yuri Shendryk, Robert Davy, Peter Thorburn, 2021 .