Michelle Ang Li Ern is a PhD candidate at the Centre for Social Responsibility in Mining (CSRM) within the Sustainable Minerals Institute (SMI) at The University of Queensland. Her research focuses on leveraging GIS and remote sensing applications to measure, manage, and monitor the socio-environmental impacts of global resource development, particularly in the context of the renewable energy transition.
Possessing a background in environmental science and a keen interest in geospatial sciences, Michelle is driven by an overarching curiosity about the various geospatial software and methodologies available. Her expertise lies in utilising these tools to map and monitor the spatio-temporal dynamics of land use and land cover (LULC).
Over the past six years, Michelle has served as a research associate at the Landscape, Ecology, and Conservation (LEC) lab at the University of Nottingham Malaysia. Her primary research endeavours during this time involved LULC mapping and change detection analysis, specifically in characterising socio-environmental impacts within mining landscapes.
In her most recent role, Michelle actively contributed to the data collection and validation efforts for the Mining Spatial Data Intelligence for Ecological and Social Risk Assessment project, a collaborative effort between CSRM, Monash University Indonesia, supported by the Ford Foundation, The University of Queensland, and Google. One of the outcomes of this collaboration includes a Repository of Global Datasets for Characterising Resource Frontiers.
Michelle's diverse research portfolio extends beyond her current PhD focus. Noteworthy projects include assessing developmental conflict and place-based preferences through Public Participatory GIS (PPGIS), conducting mapping of oil palm plantations and contributing to Land Use Change Analysis (LUCA) projects with Wild Asia. Additionally, she engaged in wildlife connectivity modelling for prominent infrastructure projects such as WSP Australia's Nairobi-Nakuru-Mau Summit Highway and Australia’s Inland Rail projects.
Key Publications
- Owen, J. R., Kemp, D., Lechner, A. M., Ang, M. L. E., Mudd, G. M., Macklin, M. G., Saputra, M. R. U., Witra, T., & Bebbington, A. (2024). Increasing mine waste will induce land cover change that results in ecological degradation and human displacement. 351 (December 2023). https://doi.org/10.1016/j.jenvman.2023.119691
- Ang, M. L. E., Owen, J. R., Gibbins, C. N., Kemp, D., Saputra, M. R. U., Everingham, J., & Lechner, A. M. (2023). Systematic Review of GIS and Remote Sensing Applications for Assessing the Socioeconomic Impacts of Mining. https://doi.org/10.1177/10704965231190126
- Ang, M. L. E., Arts, D., Crawford, D., Labatos, B. V., Ngo, K. D., Owen, J. R., Gibbins, C., & Lechner, A. M. (2020). Socio-environmental land cover time series analysis of mining landscapes using Google Earth Engine and web-based mapping. Remote Sensing Applications: Society and Environment, 21 (7), 100458. https://doi.org/10.1016/j.rsase.2020.100458
- Lechner, A. M., Owen, J., Ang, M. L. E., Edraki, M., Che Awang, N. A., & Kemp, D. (2019). Historical socio-environmental assessment of resource development footprints using remote sensing. Remote Sensing Applications: Society and Environment, 15. https://doi.org/10.1016/j.rsase.2019.100236
- Lechner, A. M., Owen, J., Ang, M. L. E., & Kemp, D. (2019). Spatially integrated social sciences with qualitative GIS to support impact assessment in mining communities. Resources 2019, 8, 47. https://doi.org/10.3390/resources8010047