Recent Publications

Shumilo, L., & Skakun, S. (2024). Optical Flow of Temperature Reveals Climate Change Patterns for Agriculture and Forestry. Remote Sensing Applications: Society and Environment, 101198. https://doi.org/10.1016/j.rsase.2024.101198.
Qadir, A., Skakun, S., Kussul, N., Shelestov, A., & Becker-Reshef, I. (2024). A generalized model for mapping sunflower areas using Sentinel-1 SAR data. Remote Sensing of Environment, 306, 114132. https://doi.org/10.1016/j.rse.2024.114132.
He, E., Xie, Y., Chen, W., Skakun, S., Bao, H., Ghosh, R., ... & Jia, X. (2024). Learning With Location-Based Fairness: A Statistically-Robust Framework and Acceleration. IEEE Transactions on Knowledge and Data Engineering, https://doi.org/10.1109/TKDE.2024.3371460.
Burton, K., Becker, D., Hovardas, T., Wardropper, C.B. and Maas, A., 2024. Assessing policy preferences for preventing and managing wildfire in Greece. Forest Policy and Economics, 163, p.103209. https://doi.org/10.1016/j.forpol.2024.103209
Cortner, O., Chen, S., Olofsson, P., Gollnow, F., Torchinava, P., & Garrett, R. D. (2024). Exploring natural and social drivers of forest degradation in post-Soviet Georgia. Global Environmental Change, 84, 102775.
Liao, C., Nolte, K., Sullivan, J., Brown, D.G., Lay, J., Althoff, C., and Agrawal, A. Carbon emissions from the global land rush and potential mitigation. Nature Food, Volume 2 https://www.nature.com/articles/s43016-020-00215-3
Williams, T.G., Trush, S.A., Sullivan, J., Liao, C., Chesterman, N., Agrawal, A. Geuikema, S.D., Brown, D.G. Land-use changes associated with large-scale land transactions in Ethiopia. Ecology and Society, Volume 26, Number 4 https://repository.arizona.edu/bitstream/handle/10150/663461/ES-2021-12825.pdf?sequence=1&isAllowed=y
Williams, T.G., Guikema, S.D., Brown, D.G., Agrawal, A. Let the farmer decide: Examining smallholder autonomy in large-scale land acquisitions with an agent-based model. Environmental Research Letters, Volume 16, Number 10 https://iopscience.iop.org/article/10.1088/1748-9326/ac2933/meta
Williams, T.G., Guikema, S.D., Brown, D.G., and Agrawal, A. Resilience and equity: Quantifying the distributional effects of resilience-enhancing strategies in a smallholder agricultural system. Agricultural Systems, Volume 182 https://www.sciencedirect.com/science/article/pii/S0308521X19313587?casa_token=CQuPPbW3yWkAAAAA:mJOOhRk2-o5kFVIyFX8knwwIa3VWEm0Vb2twIeugnoT-cKNSSMrnydr0cx-Y2ITLskRU53-tCsg
Liao, C., Jung, S., Brown, D.G., and Agrawal, A. Spatial patterns of large-scale land transactions and their potential socio-environmental outcomes in Cambodia, Ethiopia, Liberia, and Peru. Land Degradation and Development, Volume 87, Article 10 https://onlinelibrary.wiley.com/doi/epdf/10.1002/ldr.3544
Jung, S., Liao, C., Agrawal, A, Brown, D.G. Evidence on wealth-improving effects of forest concessions in Liberia. Journal of the Association of Environmental and Resource Economists, Volume 6, Article 5 https://www.journals.uchicago.edu/doi/epdf/10.1086/704614
Agrawal, A., Brown, D.G., and Sullivan, J. Are global land grabs ticking socio-environmental bombs or just inefficient investments? One Earth, Volume 1 https://www.cell.com/one-earth/pdf/S2590-3322(19)30085-5.pdf
Dang, K. B., H. H. Pham, T. N. Nguyen, T. L. Giang, T. P. N. Pham, S. V. Nghiem, D. H. Nguyen, K. C. Vu, Q. D. Bui , H. N. Pham, T. T. Nguyen, and H. H. Ngo, Monitoring the effects of urbanization and flood hazards on sandy ecosystem services. Science of the Total Environment, 880, 163271, doi:10.1016/j.scitotenv.2023.163271, 2023
Shumilo, L., Skakun, S., Gore, M. L., Shelestov, A., Kussul, N., Hurtt, G., & Yarotskiy, V. (2023). Conservation policies and management in the Ukrainian Emerald Network have maintained reforestation rate despite the war. Communications Earth & Environment, 4(1), 443.
Nguyen, D.-M T., T.-N. Do, S. V. Nghiem, J. Ghimire, K.-B. Dang, V.-T. Giang, K.-C. Vu, and V.-M. Pham, Flood inundation assessment of UNESCO World Heritage Sites using remote sensing and spatial metrics in Hoi An City, Vietnam. Ecological Informatics, 79, 102427, doi:10.1016/j.ecoinf.2023.102427, 2023.
Dixon, D., C. Brown, Y. Zhu, and Y. Jin (2023). Satellite detection of canopy scale tree mortality from California wildfires with spatio-temporal deep learning, Remote Sensing of Environment, 298(113842), https://doi.org/10.1016/j.rse.2023.113842.
Radeloff V., Mockrin M., Helmers D., Carlson A., Hawbaker T., Martinuzzi S., Schug F., Alexandre P., Kramer H., Pidgeon A. Rising wildfire risk to houses in the United States, especially in grasslands and shrublands. Science, Volume 382, Number 6671 https://www.science.org/doi/10.1126/science.ade9223
Pnvr, K., Bandaru, V. Mapping sugarcane residue burnt areas in smallholder farming systems using machine learning approaches. International Journal of Applied Earth Observation and Geoinformation, Volume 6 https://doi.org/10.1016/j.atech.2023.100347.
Liu B., Roopsind A. and Sohngen B. Overlapping extractive land use rights increases deforestation and forest degradation in managed natural production forests. World Development, Volume 174 https://www.sciencedirect.com/science/article/pii/S0305750X23002590?via%3Dihu.
Robert Gilmore Pontius Jr, Thomas Bilintoh, Gustavo de L. T. Oliveira, and Julia Z. Shimbo “Trajectories of losses and gains of soybean cultivation during multiple time intervals in western Bahia, Brazil, Space Week Nordeste 2023 in Fortaleza, Brazil.
Tanaka, T., L. Sun, I. Becker-Reshef, X.-P. Song, E. Puricelli. 2023. Satellite forecasting of crop harvest can trigger a cross-hemispheric production response and improve global food security. Communications Earth & Environment, 4, 334 : https://www.nature.com/articles/s43247-023-00992-2
Xi X., Steinfeld D., Cavallo S M., Wang J., Chen J., Zulpykharov K. and Henebry G. M . What caused the unseasonal extreme dust storm in Uzbekistan during November 2021? Environmental Research Letters, Volume 18, Number 11 https://iopscience.iop.org/article/10.1088/1748-9326/ad02af/meta
Abys, C., Skakun, S., & Becker-Reshef, I. (2024). Two decades of winter wheat expansion and intensification in Russia. Remote Sensing Applications: Society and Environment, 33, 101097.
F. Schug, A. Bar-Massada, A. R. Carlson, H. Cox, T. J. Hawbaker, D. Helmers, P. Hostert, D. Kaim, N. K. Kasraee, S. Martinuzzi, M. H. Mockrin, K. A. Pfoch, and V. C. Radeloff. 2023. The global wildland-urban interface. Nature, DOI: 10.1038/s41586-023-06320-0.
2023. Sullivan, J.A., Samii, C., Brown, D.G., Moyo, F., and Agrawal, A. Large-scale land acquisitions exacerbate land inequality in Tanzania. 2023 Proceedings of the National Academy of Sciences, 120(32): e2207398120. doi: 10.1073/pnas.2207398120
A. Qadir, S. Skakun, J. Eun, M. Prashnani, L. Shumilo, Sentinel-1 time series data for sunflower (Helianthus annuus) phenology monitoring, Remote Sensing of Environment, Volume 295, 2023, 113689, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2023.113689.
R. Traldi, J. A. Silva, P. Potapov, A. Tyukavina, M. Epprecht, M. L. Gore, C. Phompila, Cultivating inequality? Regional rubber dynamics and implications for voluntary sustainability programs in Lao PDR, World Development, Volume 170, 2023, 106312, ISSN 0305-750X, https://doi.org/10.1016/j.worlddev.2023.106312
Tzu-Hsin Karen Chen, Bhartendu Pandey, Karen C. Seto, Detecting subpixel human settlements in mountains using deep learning: A case of the Hindu Kush Himalaya 1990–2020, Remote Sensing of Environment, Volume 294, 2023, 113625, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2023.113625.
Li, Z., Xie, Y., Jia, X., Stuart, K., Delaire, C., & Skakun, S. (2023, June). Point-to-region co-learning for poverty mapping at high resolution using satellite imagery. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 37, No. 12, pp. 14321-14328).
Xie, Y., Li, Z., Bao, H., Jia, X., Xu, D., Zhou, X., & Skakun, S. (2023, June). Auto-CM: Unsupervised deep learning for satellite imagery composition and cloud masking using spatio-temporal dynamics. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 37, No. 12, pp. 14575-14583).