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QUT ePrints 
High-Fidelity Antarctic UAV Simulation with Thermal Terrain Modelling
J. Sandino, S. Boiteau, D. Brown, B. A. Bollard, and F. Gonzalez in Int. Conf. Unmanned Aircraft Systems , Corfu, Greece , pp. 1–8 , Apr. 2026. [Accepted]
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Publications
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1151
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16
h-index
23
i10-index
Source: Google Scholar · Last updated July 1, 2026
Research profiles
Showing 51 of 51 publications
Video
Drone hyperspectral imaging and artificial intelligence for monitoring moss and lichen in Antarctica
J. Sandino, J. Barthelemy, A. Doshi, K. Randall, S. A. Robinson, B. Bollard, and F. Gonzalez Sci. Rep. , vol. 15, no. 1 , pp. 27244 , Jul. 2025. doi: 10.1038/s41598-025-11535-4
Published in Scientific Reports, Nature Portfolio
View Article 
Revolutionising Antarctic Flora Monitoring with AI and Drones
J. Sandino, J. Barthelemy, A. Doshi, K. Randall, S. A. Robinson, B. Bollard, and F. Gonzalez in NVIDIA GTC 2025 , San Jose, CA, US , Mar. 2025.
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Reducing Object Detection Uncertainty from RGB and Thermal Data for UAV Outdoor Surveillance
J. Sandino, P. A. Caccetta, C. Sanderson, F. Maire, and F. Gonzalez in 2022 IEEE Aerospace Conference (AERO) , pp. 1–16 , Mar. 2022. doi: 10.1109/AERO53065.2022.9843611
Drone-Based Autonomous Motion Planning System for Outdoor Environments under Object Detection Uncertainty
J. Sandino, F. Maire, P. Caccetta, C. Sanderson, and F. Gonzalez Remote Sensing , vol. 13, no. 21 , pp. 4481 , Nov. 2021. doi: 10.3390/rs13214481
Vision Transformers and Drones for Antarctic Hyperspectral Vegetation Mapping
J. Sandino, J. Barthelemy, A. Doshi, K. Randall, S. A. Robinson, B. Bollard, and F. Gonzalez in NVIDIA GTC 2026 , San Jose, CA, US , Mar. 2026.
Advances in machine learning approaches for UAV-based remote sensing in data-deficient Antarctic environments
B. Gorry, J. Sandino, P. Moghadam, F. Gonzalez, and J. Roberts Remote Sens. (Basel) , vol. 18, no. 3 , pp. 459 , Feb. 2026. doi: 10.3390/rs18030459
Article
Advancing real-time aerial wildfire detection through plume recognition and knowledge distillation
P. Keerthinathan, J. Sandino, S. Mahendren, A. Uthayasooriyan, J. Galvez, G. Hamilton, and F. Gonzalez Drones , vol. 9, no. 12 , pp. 827 , Nov. 2025. doi: 10.3390/drones9120827
Article
Detection and mapping of Antarctic lichen using drones, multispectral cameras, and supervised deep learning
N. Amarasingam, J. Sandino, A. Doshi, D. King, E. Blackman, J. Barthelemy, B. Bollard, S. A. Robinson, and F. Gonzalez Int. J. Appl. Earth Obs. Geoinf. , vol. 141, no. 104577 , pp. 104577 , Jul. 2025. doi: 10.1016/j.jag.2025.104577
Conference
DECK-GA: A hybrid clustering and distance efficient genetic algorithm for scalable multi-UAV path planning
D. Debnath, F. Vanegas, J. Sandino, and F. Gonzalez in 2025 International Conference on Unmanned Aircraft Systems (ICUAS) , Charlotte, NC, USA , pp. 301–308 , May 2025. doi: 10.1109/icuas65942.2025.11007785
Article
Advancing sparse vegetation monitoring in the arctic and antarctic: A review of satellite and UAV remote sensing, machine learning, and sensor fusion
A. Platel, J. Sandino, J. Shaw, B. Bollard, and F. Gonzalez Remote Sens. (Basel) , vol. 17, no. 9 , pp. 1513 , Apr. 2025. doi: 10.3390/rs17091513
Article
Mapping of insect pest infestation for precision agriculture: A UAV-based multispectral imaging and deep learning techniques
N. Amarasingam, K. Powell, J. Sandino, D. Bratanov, A. S. Ashan Salgadoe, and F. Gonzalez Int. J. Appl. Earth Obs. Geoinf. , vol. 137, no. 104413 , pp. 104413 , Mar. 2025. doi: 10.1016/j.jag.2025.104413
Article
Unmanned Aerial Vehicles for real-time vegetation monitoring in Antarctica: A review
K. Lockhart, J. Sandino, N. Amarasingam, R. Hann, B. Bollard, and F. Gonzalez Remote Sens. (Basel) , vol. 17, no. 2 , pp. 304 , Jan. 2025. doi: 10.3390/rs17020304
QUT Vice Chancellor’s Awards, Research and Innovation Excellence Award: “High Tech for Low Temperatures Team – Drones and AI for Conservation in Antarctica”
J. Sandino, N. Amarasingam, D. Bratanov, G. Broadbent, D. Gilligan, F. Gonzalez, J. Shaw, J. Galvez, and M. Swan , Dec. 2024.
View Record Misc
Remote Sensing Science in Antarctica and Sub-Antarctic Islands using Drones, Satellite, and AI: From Data Acquisition to Management/Policy
J. Sandino, B. Bollard, J. Shaw, F. Gonzalez, and S. A. Robinson in Australian Antarctic Research Conference , Hobart, Australia , Nov. 2024.
Article
A review of UAV path-planning algorithms and obstacle avoidance methods for remote sensing applications
D. Debnath, F. Vanegas, J. Sandino, A. F. Hawary, and F. Gonzalez Remote Sens. (Basel) , vol. 16, no. 21 , pp. 4019 , Oct. 2024. doi: 10.3390/rs16214019
Misc
Heatwaves and rapid freezing: does micro-topography influence how often Antarctic mosses exceed temperature thresholds?
K. Randall, X. Zheng, J. Sandino, and S. A. Robinson in 11th SCAR Open Science Conference , Pucon, Chile , Aug. 2024.
View Record Misc
Optimising UAS protocols for Vegetation Monitoring in Antarctica: Key Insights and Case Studies from the Windmill Islands, and Bunger Hills
J. Sandino, M. Swan, J. Galvez-Serna, N. Amarasingam, A. Doshi, K. Randall, S. A. Robinson, B. Bollard, and F. Gonzalez in 11th SCAR Open Science Conference , Pucon, Chile , Aug. 2024.
Article
Bitou bush detection and mapping using UAV-based multispectral and hyperspectral imagery and artificial intelligence
N. Amarasingam, J. E Kelly, J. Sandino, M. Hamilton, F. Gonzalez, R. L Dehaan, L. Zheng, and H. Cherry Remote Sens. Appl. Soc. Environ. , vol. 34, no. 101151 , pp. 101151 , Apr. 2024. doi: 10.1016/j.rsase.2024.101151
Article
Monitoring of Antarctica's fragile vegetation using drone-based remote sensing, multispectral imagery and AI
D. Raniga, N. Amarasingam, J. Sandino, A. Doshi, J. Barthelemy, K. Randall, S. A. Robinson, F. Gonzalez, and B. Bollard Sensors (Basel) , vol. 24, no. 4 , pp. 1063 , Feb. 2024. doi: 10.3390/s24041063
A green fingerprint of Antarctica: Drones, hyperspectral imaging, and machine learning for moss and lichen classification
J. Sandino, B. Bollard, A. Doshi, K. Randall, J. Barthelemy, S. A. Robinson, and F. Gonzalez Remote Sens. (Basel) , vol. 15, no. 24 , pp. 5658 , Dec. 2023. doi: 10.3390/rs15245658
Misc
Enhancing antarctic conservation with advanced remote sensing and machine learning techniques for ASPA scale mapping and monitoring
J. Sandino, B. Bollard, A. Doshi, J. Barthelemy, and F. Gonzalez in XIII SCAR Biology Symposium 2023 , Pucon, Chile , Jul. 2023. [In Press]
Photos from the field: spying on Antarctic moss using drones, MossCam, smart sensors and AI
B. Bollard, J. Barthélemy, J. Sandino, and K. Randall The Conversation , May 2023.
View Record Article
Autonomous Detection of Mouse-Ear Hawkweed Using Drones, Multispectral Imagery and Supervised Machine Learning
N. Amarasingam, M. Hamilton, J. E. Kelly, L. Zheng, J. Sandino, F. Gonzalez, R. L. Dehaan, and H. Cherry Remote Sensing , vol. 15, no. 6 , pp. 1633 , Mar. 2023. doi: 10.3390/rs15061633
Detection of white leaf disease in sugarcane crops using UAV-derived RGB imagery with existing deep learning models
N. Amarasingam, F. Gonzalez, A. S. A. Salgadoe, J. Sandino, and K. Powell Remote Sens. (Basel) , vol. 14, no. 23 , pp. 6137 , Dec. 2022. doi: 10.3390/rs14236137
Article
UAV4PE: An Open-Source Framework to Plan UAV Autonomous Missions for Planetary Exploration
J. Galvez-Serna, F. Vanegas, S. Brar, J. Sandino, D. Flannery, and F. Gonzalez Drones , vol. 6, no. 12 , pp. 391 , Dec. 2022. doi: 10.3390/drones6120391
Article
Detection of Parthenium weed (Parthenium hysterophorus L.) and its growth stages using artificial intelligence
B. Costello, O. O. Osunkoya, J. Sandino, W. Marinic, P. Trotter, B. Shi, F. Gonzalez, and K. Dhileepan Collect. FAO Agric. , vol. 12, no. 11 , pp. 1838 , Nov. 2022. doi: 10.3390/agriculture12111838
Conference
Weed managers guide to remote detection: Understanding opportunities and limitations of technologies for remote detection of weeds
J. Kelly, M. Rahaman, J. Sandino, L. Zheng, H. Cherry, M. A. Hamilton, R. Dehaan, F. Gonzalez, W. Menz, and L. Grant in 22nd Australasian Weeds Conference , Adelaide, Australia , pp. 58–62 , Sep. 2022.
View Paper 
Autonomous decision-making for UAVs operating under environmental and object detection uncertainty
J. Sandino , Jun. 2022. doi: 10.5204/thesis.eprints.232513
Conference
Design and Flight Testing of a Two DOF Decoupled Pantograph Aerial Manipulator for Commercial UAVs
C. Luxton, J. Sandino, F. Vanegas, and F. Gonzalez in 2022 International Conference on Unmanned Aircraft Systems (ICUAS) , pp. 1–10 , Jun. 2022. doi: 10.1109/ICUAS54217.2022.9836224
Conference
Design and Flight Test of an Aerial Manipulator for Applications in GPS-Denied Environments
M. Ng, F. Vanegas, K. Morton, J. Sandino, and F. Gonzalez in 2022 International Conference on Unmanned Aircraft Systems (ICUAS) , pp. 20–29 , Jun. 2022. doi: 10.1109/ICUAS54217.2022.9836060
Conference
Real-time segmentation of desiccation cracks onboard UAVs for planetary exploration
J. Galvez-Serna, N. Mandel, J. Sandino, F. Vanegas, N. Ly, D. T. Flannery, and F. Gonzalez in 2022 IEEE Aerospace Conference (AERO) , Big Sky, MT, USA , pp. 1–12 , Mar. 2022. doi: 10.1109/aero53065.2022.9843515
Conference
Resolution-adaptive Quadtrees for Semantic Segmentation Mapping in UAV Applications
N. Mandel, J. Sandino, J. Galvez-Serna, F. Vanegas, M. Milford, and F. Gonzalez in 2022 IEEE Aerospace Conference (AERO) , Big Sky, MT, USA , pp. 1–17 , Mar. 2022. doi: 10.1109/AERO53065.2022.9843498
Autonomous Mapping of Desiccation Cracks via a Probabilistic-based Motion Planner Onboard UAVs
J. Sandino, J. Galvez–Serna, N. Mandel, F. Vanegas, and F. Gonzalez in 2022 IEEE Aerospace Conference (AERO) , Big Sky, MT, USA , pp. 1–14 , Mar. 2022. doi: 10.1109/AERO53065.2022.9843299
UAV framework for autonomous onboard navigation and people/object detection in cluttered indoor environments
J. Sandino, F. Vanegas, F. Maire, P. Caccetta, C. Sanderson, and F. Gonzalez Remote Sens. (Basel) , vol. 12, no. 20 , pp. 3386 , Oct. 2020. doi: 10.3390/rs12203386
Autonomous UAV navigation for active perception of targets in uncertain and cluttered environments
J. Sandino, F. Vanegas, F. Gonzalez, and F. Maire in IEEE Aerospace Conference , Big Sky, United States , pp. 1–12 , Mar. 2020. doi: 10.1109/AERO47225.2020.9172808
Article
Phylloxera: Improving pest surveillance in vineyards through drones, hyperspectral and spatial data
F. Vanegas, D. Bratanov, J. Sandino, K. Powell, J. Weiss, and F. Gonzalez Wine \& Viticulture Journal , vol. 33, no. 4 , pp. 42–52 , Sep. 2018.
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A novel approach for invasive weeds and vegetation surveys using UAS and artificial intelligence
J. Sandino, and F. Gonzalez in 2018 23rd International Conference on Methods \& Models in Automation \& Robotics (MMAR) , Miedzyzdroje , pp. 515–520 , Aug. 2018. doi: 10.1109/mmar.2018.8485874
Aerial mapping of forests affected by pathogens using UAVs, hyperspectral sensors, and artificial intelligence
J. Sandino, G. Pegg, F. Gonzalez, and G. Smith Sensors , vol. 18, no. 4 , pp. 944 , Mar. 2018. doi: 10.3390/s18040944
Over 150 citations.
UAVs and Machine Learning Revolutionising Invasive Grass and Vegetation Surveys in Remote Arid Lands
J. Sandino, F. Gonzalez, K. Mengersen, and K. J. Gaston Sensors , vol. 18, no. 2 , pp. 605 , Feb. 2018. doi: 10.3390/s18020605
Conference
Revolutionising the detection and mapping of exotic weeds using UASs and machine learning
J. Sandino, S. Harris, P. Trotter, A. Shukla, and F. Gonzalez in International Master Class in Plant Biosecurity , Jan. 2018.
Report
Optimising surveillance protocols using unmanned aerial systems
B. McCornack, G. P. Bhattarai, T. Witt, F. Gonzalez, G. Hamilton, F. Vanegas, J. Froese, J. Sandino, J. Weiss, and G. Pegg , pp. 25 , 2018.
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Prediction of reproductive system affectation in Sprague Dawley rats by food intake exposed with Fenthion, using Naïve Bayes classifier and genetic algorithms
J. Sandino, D. Amaya Hurtado, and O. Lucia Ramos Biosci. Biotechnol. Res. Asia , vol. 14, no. 4 , pp. 1291–1297 , Dec. 2017. doi: 10.13005/bbra/2572
Conference
UAS remote sensing efforts for Myrtle rust management
F. Vanegas, G. Pegg, J. Kok, J. Sandino, and F. Gonzalez in Science Protecting Plant Health 2017 , Sep. 2017.
Towards the Automatic Detection of Pre-Existing Termite Mounds through UAS and Hyperspectral Imagery
J. Sandino, A. Wooler, and F. Gonzalez Sensors , vol. 17, no. 10 , pp. 2196 , Sep. 2017. doi: 10.3390/s17102196
Conference
Bitou bush surveillance UAV trial
S. Harris, P. Trotter, F. Gonzalez, and J. Sandino in 14th Queensland Weed Symposium , 2017.
Prediction of Endocrine System Affectation in Fisher 344 Rats by Food Intake Exposed with Malathion, Applying Naïve Bayes Classifier and Genetic Algorithms
J. Sandino, D. A. Hurtado, and O. L. R. Sandoval Int. J. Prev. Med. , vol. 7, no. 1 , pp. 111 , Sep. 2016. doi: 10.4103/2008-7802.190611
Method for estimating leaf coverage in strawberry plants using digital image processing
J. Sandino, O. L. Ramos-Sandoval, and D. Amaya-Hurtado Rev. Bras. Eng. Agric. Ambient./Braz. J. Agric. Environ. Eng. , vol. 20, no. 8 , pp. 716–721 , Aug. 2016. doi: 10.1590/1807-1929/agriambi.v20n8p716-721
Monitoreo Preliminar de Incidencia de Fisiopatías en Cultivos de Fresa usando Procesamiento Digital de Imágenes
J. Sandino, D. Amaya Hurtado, and O. L. Ramos Sandoval Biotecnología en el Sector Agropecuario y Agroindustrial , vol. 14, no. 1 , pp. 45–52 , 2016. doi: 10.18684/BSAA(14)45-52
Método preliminar de detección de patógenos biológicos en cultivos de fresa por medio del procesamiento digital de imágenes
D. Amaya-Hurtado, and J. Sandino Rev. Investig. Agrar. Ambient. , vol. 6, no. 1 , pp. 111 , Mar. 2015. doi: 10.22490/21456453.1267
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Last updated: 1 July 2026