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Miss Laura Sotomayor
Miss

Laura Sotomayor

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Overview

Background

Laura Natali Sotomayor is a Research Platform Fellow (Geospatial Data Scientist) with the UQ Drone Collaborative Research Platform, based within the W.H. Bryan Mining Geology Research Centre at the Sustainable Minerals Institute. She develops tools and workflows to process, analyse and interpret drone-acquired multi-sensor imagery and lidar data, supporting research and industry applications.

She completed her PhD in Geomatic Engineering at the University of Tasmania, where her research developed deep learning workflows for multi-sensor Unoccupied Aerial Systems (UAS) monitoring of vegetation in semi-arid rangelands, combining remote sensing techniques with automated image analysis to translate high-resolution imagery into spatially explicit information on vegetation cover, structure, and condition.

Availability

Miss Laura Sotomayor is:
Available for supervision

Qualifications

  • Masters (Research) of Computer Science (Information Technology), University of Tasmania
  • Masters (Research) of Information Technology (Systems Analysis and Design), University of Tasmania

Works

Search Professor Laura Sotomayor’s works on UQ eSpace

2 works between 2023 and 2025

1 - 2 of 2 works

2025

Journal Article

Mapping fractional vegetation cover in UAS RGB and multispectral imagery in semi-arid Australian ecosystems using CNN-based semantic segmentation

Sotomayor, Laura N., Lucieer, Arko, Turner, Darren, Lewis, Megan and Kattenborn, Teja (2025). Mapping fractional vegetation cover in UAS RGB and multispectral imagery in semi-arid Australian ecosystems using CNN-based semantic segmentation. Landscape Ecology, 40 (8) 169, 1-34. doi: 10.1007/s10980-025-02193-y

Mapping fractional vegetation cover in UAS RGB and multispectral imagery in semi-arid Australian ecosystems using CNN-based semantic segmentation

2023

Journal Article

Supervised machine learning for predicting and interpreting dynamic drivers of plantation forest productivity in northern Tasmania, Australia

Sotomayor, Laura N., Cracknell, Matthew J. and Musk, Robert (2023). Supervised machine learning for predicting and interpreting dynamic drivers of plantation forest productivity in northern Tasmania, Australia. Computers and Electronics in Agriculture, 209 107804, 209. doi: 10.1016/j.compag.2023.107804

Supervised machine learning for predicting and interpreting dynamic drivers of plantation forest productivity in northern Tasmania, Australia

Supervision

Availability

Miss Laura Sotomayor is:
Available for supervision

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Media

Enquiries

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