Rau, E-P., Swinfield, T., Williams, A., Keshav, S. and Coomes, D., 2025 (No publication date). Research data supporting “Forecasting carbon credits of prospective REDD+ projects using regional carbon loss patterns” Doi: http://doi.org/10.17863/CAM.116193
2025
Capol, L., Keshav, S. and Nagy, Z., 2025. Activity hours: Assessing liveability during heatwaves Building and Environment, v. 269 Doi: http://doi.org/10.1016/j.buildenv.2024.112339
Feng, Z., She, Y. and Keshav, S., 2025. SPREAD: A large-scale, high-fidelity synthetic dataset for multiple forest vision tasks Ecological Informatics, v. 87 Doi: http://doi.org/10.1016/j.ecoinf.2025.103085
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Virdee, M., Kazlauskaite, I., Boland, EJD., Shuckburgh, E. and Ming, A., 2025. Spatial and temporal dependence in distribution-based evaluation of CMIP6 daily maximum temperatures Atmospheric Science Letters, v. 26 Doi: http://doi.org/10.1002/asl.1290
Wang, J., Chang, L., Aggarwal, S., Abari, O. and Keshav, S., 2025. Sustainable and Low-Cost Greenhouse Soil Moisture Monitoring Using Battery-Free RFID Sensors ACM Transactions on Sensor Networks, v. 21 Doi: 10.1145/3715128
Rouse, RE., Khamis, D., Hosking, S., McRobie, A. and Shuckburgh, E., 2025. Streamflow prediction using artificial neural networks and soil moisture proxies Environmental Data Science, v. 4 Doi: http://doi.org/10.1017/eds.2024.48
Domiter, A. and Keshav, S., 2025. Machine Learning for Building-Level Heat Risk Mapping Proceedings of the 16th ACM International Conference on Future and Sustainable Energy Systems, Doi: http://doi.org/10.1145/3679240.3734628
Gschwind, JO. and Keshav, S., 2025. Fast Optimal Sizing of Domestic PV Energy Systems Proceedings of the 16th ACM International Conference on Future and Sustainable Energy Systems, Doi: http://doi.org/10.1145/3679240.3734690
Domiter, A. and Keshav, S., 2025. Fine-Grained Mapping of Urban Energy Demand During Heatwaves Proceedings of the 16th ACM International Conference on Future and Sustainable Energy Systems, Doi: http://doi.org/10.1145/3679240.3734688
Reynolds, S., Beery, S., Burgess, ND., Burgman, M., Butchart, S., Cooke, S., Coomes, D., Danielsen, F., Di Minin, E., Paz Durán, A., Gassert, F., Hinsley, A., Jaffer, S., Jones, JPG., Li, BV., Mac Aodha, O., Madhavapeddy, A., O'Donnel, SAL., Oxbury, WM., Peck, L., Pettorelli, N., Rodriguez, JP., Shuckburgh, E., Strassburg, B., Yamashita, H., Zhongqi, M. and Sutherland, WJ., 2025. The potential for AI to revolutionise conservation: a horizon scan Trends in Ecology and Evolution, Doi: 10.1016/j.tree.2024.11.013
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Furner, R., Haynes, P., Jones, DC., Munday, D., Paige, B. and Shuckburgh, E., 2025. The challenge of land in a neural network ocean model Environmental Data Science, v. 3 Doi: 10.1017/eds.2024.49
Zuñiga-Gonzalez, A., Madhavapeddy, A. and Bardhan, R., 2025. Green Urban Equity: Analyzing the 3-30-300 Rule in UK Cities and Its Socioeconomic Implications Doi: 10.5194/egusphere-egu24-20833
Eyres, A., Ball, TS., Dales, M., Swinfield, T., Arnell, A., Baisero, D., Durán, AP., Green, JMH., Green, RE., Madhavapeddy, A. and Balmford, A., 2025. LIFE: A metric for mapping the impact of land-cover change on global extinctions Philosophical Transactions of the Royal Society B: Biological Sciences, v. 380 Doi: http://doi.org/10.1098/rstb.2023.0327
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2024 (Published online)
Collins, M., Beverley, JD., Bracegirdle, TJ., Catto, J., McCrystall, M., Dittus, A., Freychet, N., Grist, J., Hegerl, GC., Holland, PR., Holmes, C., Josey, SA., Joshi, M., Hawkins, E., Lo, E., Lord, N., Mitchell, D., Monerie, P-A., Priestley, MDK., Scaife, A., Screen, J., Senior, N., Sexton, D., Shuckburgh, E., Siegert, S., Simpson, C., Stephenson, DB., Sutton, R., Thompson, V., Wilcox, LJ. and Woollings, T., 2024 (Published online). Emerging signals of climate change from the equator to the poles: new insights into a warming world Frontiers in Science, v. 2 Doi: http://doi.org/10.3389/fsci.2024.1340323
