RESEARCH THEMES
Research overview
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Our research focuses on the application of application of integrated socio-environmental approaches, along with spatially explicit modelling and remote sensing. The current research areas include sustainable urban planning, natural resource management, extractive industries and biodiversity conservation. We have undertaken research across the world from Oceania to Southeast Asia and Europe and has a successful track record of applying landscape ecology methods to a broad range of cross-cutting areas with ongoing projects in the following areas: 1) modelling threats to the environment from infrastructure development and resource extraction using big environmental data and machine learning, 2) applications of Nature-based Solutions; and 3) supporting socio-environmental change with interdisciplinary approaches to modelling and collaborating across environmental domains and disciplines.
Current Research - Mining Environmental and Social Challenges
Mining is one of the most consequential and least measured land-use pressures on Earth. The minerals underpinning decarbonisation, technological development, and global supply chains come at environmental and social costs that remain poorly quantified. Existing global mining inventories are structurally incomplete and spatially inaccurate. Standard approaches to characterising mine disturbance conflate process-distinct features into undifferentiated land cover classes, erasing the information needed to assess impact severity, model risk pathways, and estimate rehabilitation liability. Regulators, investors, and the communities who bear the burden of mine closure operate without the foundational data needed to hold the industry to account.
Our research addresses these deficiencies by integrating remote sensing, deep learning, AI, geographic information science, spatial ecology, and environmental risk assessment into a globally scalable framework for measuring mining's environmental footprint and its consequences. We work across the full chain from inventory to impact to liability.
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Our work in this area includes the following:
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Global mining inventory and area estimation.
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Mining environmental metrics and land cover classification.
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Deep learning remote sensing for mining footprint mapping.
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Spatially explicit environmental and social risk and impact assessment modelling off-site exposure pathways
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Cumulative impact modelling.
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Rehabilitation liability assessment.
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This work sits at the intersection of environmental monitoring, land system science, and the political economy of extractive industries. It has direct relevance to critical minerals governance, corporate environmental accountability, and the conditions for just transitions in mining-dependent economies.
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See Google Scholar for academic papers
Example research outputs:
Overviews
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​Lechner, A.M., Foody, G., Boyd, D. (2020) 'Applications in remote sensing to forest ecology and management', One Earth, 2(5), pp. 405–412.
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Lechner, A.M., McIntyre, N., Raymond, C.M., Witt, K., Scott, M. & Rifkin, W. (2017) 'Challenges of integrated modelling in mining regions to address social, environmental and economic impacts', Environmental Modelling and Software, 93, pp. 268–281.​
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Global Mining Challenges
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Kemp, D., Loginova, J., Lechner, A. M., Ang, M. L. E., Kuswati, R. A., Saputra, M. R. U., Unger, C., Bebbington, A., & Owen, J. R. (2026, January 16). The rise of brownfield mining is reshaping global mineral supply and intensifying social and environmental risk. One Earth.​
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​Owen, J. R., Lèbre, E., Lechner, A. M., Harris, J., Zhang, R. & Kemp, D. (2023) 'Energy transition minerals and their intersection with land connected peoples', Nature Sustainability, 6(2), pp. 203-211.
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Remote sensing methods
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Saputra, M. R. U., Bhaswara, I. D., Nasution, B. I., Ern, M. A. L., Husna, N. L. R., Witra, T., Feliren, V., Owen, J. R., Kemp, D., & Lechner, A. M. (2025). ‘Multi-modal deep learning approaches to semantic segmentation of mining footprints with multispectral satellite imagery’. Remote Sensing of Environment, 318, 114584
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GIS and RS approaches
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Ang, M. L. E., Owen, J. R., Gibbins, C. N., Lèbre, É., Kemp, D., Saputra, M. R. U., Everingham, J.-A. & Lechner, A. M. (2023) 'Systematic review of GIS and remote sensing applications for assessing the socioeconomic impacts of mining', The Journal of Environment & Development, 10704965231190126.
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Ecosystem Services Modelling
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Lourdes, K. T., Hamel, P., Gibbins, C. N., Sanusi, R., Azhar, B. & Lechner, A. M. (2022) 'Planning for green infrastructure using multiple urban ecosystem service models and multicriteria analysis', Landscape and Urban Planning, 226(June), p. 104500.
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High impact papers
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Macklin, M.G., Thomas, C.J., Mudbhatkal, A., Brewer, P.A., Hudson-Edwards, K.A., Lewin, J., Scussolini, P., Eilander, D., Lechner, A. M., Owen, J.R., Bird, G., Kemp, D. & Mangalaa, K. R. (2023) 'Impacts of metal mining on river systems: the first global assessment', Science, 381(6664), pp. 1345-1350.
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Lechner, A.M., Chan, F.K.S. & Campos-Arceiz, A. (2018) 'Biodiversity conservation should be a core value of China’s Belt and Road Initiative', Nature Ecology & Evolution, 23, pp. 23-24.
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Previous Project websites