Monitoring vegetation and fauna through GIS and remote sensing

Dr Lorna Hernandez-Santin is an ecologist and spatial scientist who focuses on minimising human impacts on the environment and its species at different scales, mostly through GIS and remote sensing tools (e.g. data obtained from camera-trapping, telemetry, maps, drones, and/or satellites – among others). 


Lorna’s research focuses on restoration ecology and mine-rehabilitation with aim to obtain positive outcomes for biodiversity. For example:

  • In 2022, Lorna developed a tool to monitor changes in landscape connectivity for flora and fauna from varying levels of mine-rehabilitation goals, comparing rehabilitating for agricultural purposes with restoring to native ecosystems. 
  • Between 2017 and 2022, Lorna was involved in a project dealing with the restoration of the high-profile Ranger Uranium Mine, which was conducted in collaboration with the Australian government’s Supervising Scientist (ERISS). Ranger is a high-profile mine, surrounded by the world heritage Kakadu National Park. As part of this project, Lorna helped to establish sites in reference areas and previously restored areas, monitored vegetation and soils, analysed data, conducted literature reviews with the goal of setting closure criteria, provided benchmark information and aided the provision of guidance to restore and monitor the restoration’s progression of Ranger.

Lorna is also interested in measuring mine-rehabilitation success through remote sensing and fieldwork (including understanding the relationship between them) and improving current practices to achieve positive outcomes. For example:

  • In 2023, Lorna is working on different projects that aim to monitor mine-rehabilitation projects and develop best practice guidelines for monitoring and recognising success. 
  • From late 2023, Lorna will collaborate in a project aiming to assess the potential impacts of a range of rehabilitation options and develop a monitoring program to conduct field assessments during the project. Then, a rehabilitation option will be chosen, and the monitoring program will be used as a framework to provide guidance for future monitoring of the rehabilitation trajectory the mines involved. 

•    In 2021, she conducted research to understand current use, limitations, and future needs of remote sensing in monitoring different aspects in mining and its rehabilitation. This research involved literature reviews and interviews to stakeholders in different sectors of mining. 

Lorna is also interested in broader ecological and conservation aspects, often aiming to minimise anthropogenic impacts on the environment. This work has had a strong fauna focus, with an expertise in carnivores. Through this research, Lorna has explored habitat suitability, species distributions, habitat quality, resource availability, habitat use, population dynamics, movement rates, activity patters, communities, and species interactions of native and introduced species in varied ecosystem types (including urban areas) across the world. For example:

  • In 2018, she led a project to identify the best locations for wildlife crossings in a new Expressway that was planned between Nairobi and Mombasa (Kenya). Unfortunately, the Expressway did not go ahead at that time and this project was suspended by the contractors. 
  • Since 2013, Lorna has been exploring different aspects of the ecology of the northern quoll in the Pilbara. More recently, Lorna collaborated on research, aiming to understand the space use and habitat preferences of this Endangered species. 


Lorna obtained a BSc in Biology (UDLAP in Puebla, Mexico; 2004), where she conducted a thesis (honours equivalent) looking at the spatial and temporal distribution of avifauna in urban areas. Then, while conducting her MSc in Range and Wildlife Management (SRSU in Texas, USA; 2008), Lorna explored the home range and movement rates of jaguars (Panthera onca) in agricultural and protected areas of northern Paraguay and monitored mesocarnivores in Big Bend National Park (Texas). She also worked on projects monitoring avifauna as indicators of restoration success, monitoring home ranges of grey foxes (Urocyon cinereoargenteus), tutored “GIS and Remote Sensing”, and started a role as research assistant that continued after graduation. The latter was to develop habitat suitability models for mountain lions (Puma concolor) and black bears (Ursus americanus). 

During her PhD in ecology (UQ 2017), Lorna looked into the ecology of the northern quoll (Dasyurus hallucatus) to assess potential aspects driving the range contraction of this endangered species. These aspects included top-down (predators) and bottom-up (habitat quality and prey availability) pressures, population dynamics of northern quolls –through live-trapping–, and interactions with other dasyurid species. This research was funded by ARC, scholarships awarded (CONACYT and UQ), grants (Holsworth, NESP), and in-kind funding (DPaW). Before graduating, Lorna held a research assistant position with the Quantitative Applied Spatial Ecology Group at QUT, where she worked with drone derived data over the course of three months.  

Upon being awarded her PhD, Lorna joined the Sustainable Minerals Institutes Centre (SMI) for Mined Land Rehabilitation. At the beginning of her career at SMI, she focused mostly on the project regarding the restoration of Ranger Uranium Mine (described above). She has also continued to build on and expand the northern quoll research through collaborations and short projects. As her career has progressed and the demands of Ranger’s project have decreased, Lorna started to become involved in a wider range of projects mostly dealing with different aspects of environmental monitoring through remote sensing. Funding for projects at SMI has been provided by the government at state and federal levels, as well as research institutes, mining companies, and consortiums between industry and research organisations (e.g. SartSat-CRC, CRC-TiME).


  • Nominated by SMI: SPARK program. This is a professional development program (first of its kind at UQ), where one-two persons from each faculty and institute of the university were chosen to improve their industry engagement skills. The University of Queensland, Australia (awarded 2022, course in 2023).
  • School of Biological Sciences Travel Award Prize. The University of Queensland, Australia (awarded 2015).
  • Outstanding Graduate Student for the Department of Natural Resource Management, Wildlife division. Sul Ross State University, USA (awarded 2008).

Current Memberships

  • Society for Ecological Restoration (2020-present) 
  • The Australian Mammal Society (2015-present)
  • Society for Conservation Biology (2010-present)

Engagement and Collaboration 

Government agencies and programs
  • Office of the Queensland Mine Rehabilitation Commissioner, Department of Environment and Science, Brisbane, Queensland
  • Department of Industry, Science, Energy and Resources’ Cooperative Research Centres (CRC) initiatives:
    • Transformations in Mining Economies (CRC-TiME)
    • Smart Satellite Technologies and Analytics (SmartSat-CRC).
  • Environmental Research Institute of the Supervising Scientist, Department of Agriculture, Water and the Environment, Darwin, Northern Territory
  • Science and Conservation Division, Department of Biodiversity, Conservation and Attractions, Kensington, Western Australia
  • National Environmental Science Program (NESP), Threatened Species Recovery Hub 
  • School of Biological Sciences, University of Queensland, St. Lucia, Queensland 4072, Australia
  • School of Science, Edith Cowan University, 100 Joondalup Drive, Joondalup, WA 6027, Australia
  • School of Environmental Science, Institute for Land, Water and Society, Charles Sturt University, Albury, New South Wales, Australia
  • Departamento de Investigación en Biodiversidad, Alimentación y Cambio Climático, Benemérita Universidad Autónoma de Puebla, Puebla, Mexico
  • School of BioSciences, University of Melbourne, Victoria 
  • Glencore Australia Holdings Pty Limited
  • MMG Australia Limited
  • Environmental Resource Management East Africa Limited. On Behalf of BNT Construction & Engineering Kenya Limited (BECHTEL)

Research opportunities (short projects). If interested, send an email with your CV.

1. Is there a pattern on distribution of canopy and non-grassy understory species in savanna woodlands?

The spatial distribution of vegetation species in savannas is highly variable, resulting in a heterogeneous ecosystem where patterns are hard to predict. This is particularly true for the canopy, which is usually composed of an open overstorey with a patchy distribution of trees. In contrast, the understorey is often dominated by a few grass species that can lead to predictable vegetation cover, but nevertheless can obscure the presence and distribution of highly diverse biodiversity. Increases in canopy cover in savanna woodlands is thought to lead to a decrease in the diversity of the understorey community. If we get rid of “noise” from dominant grass species, can the distribution of trees help explain or predict the presence and distribution of understorey species? Is there a difference between species with open canopies vs. closed canopies?

Through this project, you can help further our understanding of species distribution in savannas, using existing data sets. Specifically, you will have access to point-intercept data taken within plots distributed in eucalypt-dominated savannas of the iconic Kakadu National Park.

2. Flower detection with drone-based imagery

Detecting features in the ecosystem through remote sensing imagery depends upon image quality and resolution. Certainly, as technology has improved, so has our ability to reliably detect different features of the environment. Considering that spatial resolution of imagery is dictated by sensor capabilities and by its distance to the feature, technological advances allowing the incorporation of specialized sensors to drones has made possible the detection of features that are much smaller than those obtained from traditional remote systems. For instance, drone-based imagery has been successfully used to individually identify a variety of overstorey species. However, detecting understorey species is more complicated, given that they are much smaller and are often hidden by the overstorey’s canopy. Despite limitations, it is possible to detect understorey species (in open environments), with documented stories of success that are mostly proof of concept at this stage (Hernandez-Santin et al., 2019). So, the question rises, what is the minimum resolution needed to detect and identify understorey species in savannas?

Through this project, you can help to determine what is the minimum resolution needed to detect selected understorey species with distinguishing characteristics (i.e. flowers), using existing data sets. Specifically, you will have access to done-based imagery collected for different flower species at different heights. The ecosystem is a eucalypt-dominated savanna in the iconic Kakadu National Park.


As chief investigator or team member, Lorna has helped secure funds through a range of tenders, grants, and contracts. She has also received in-kind funding.

ORCID: 0000-0001-8996-3310

Scopus ID:  37016289200

Google Scholar ID: PjjQks8AAAAJ