All Publications

Desai, M., Camobreco, V., Hedger, T., Irving, W., Rewcastle, K., Steller, J., Barbieri, L., Weitz, M., Murumkar, T., Patel, A., Averyt, M., Bronstein, K., Butler, J., Chinery, L., Edquist, K., Ferenchiak, R., Garfinkel, J., Hakos, M., Icenhour, M., Kaelin, J., Kerr, E., Long, B., Manne, G., Moore, T., Rabemiarisoa, A., Randall, D., Robinson, L., Schaffner, K., Scully, P., … Hultman, N. (2026). Methodology report for greenhouse gas inventory and analysis by U.S. state: 1990–2024. Center for Global Sustainability, University of Maryland, College Park. https://doi.org/10.13016/5wlk-9ksj

Gore, M. L., Kobla, A. S., Mbi, B. T., Murray, H., Tene, R., Dilkina, B., Price, A. N., & Shirley, M. H. (2025). Participatory mapping of trade in pangolin scales and other wildlife in Cameroon dataset (PMTPSOWC) [Data descriptor]. IEEE. https://doi.org/10.5281/zenodo.19486884

Xu, L., Feng, K., Fan, M., Shao, S., & Sun, L. (2026). Clean-air regulation reduces childhood wasting and overweight in China. Communications Earth & Environment. Advance online publication. https://doi.org/10.1038/s43247-026-04061-2

Chen, X., Feng, K., Sun, L., Malerba, D., Tian, P., & Hultman, N. (2026). Reallocating fossil subsidies via social assistance reduces poverty and preserves emissions cuts. Proceedings of the National Academy of Sciences, 123(38), Article e2606441123. https://doi.org/10.1073/pnas.2606441123

Adeyemi, A. B., Adesuji Komolafe, A., Nakalembe, C. L., & Adebayo, A. D. (2026). Predictive flood susceptibility mapping of the lower Niger River Basin using GIS-based machine learning models under climate and environmental changes. International Journal of River Basin Management, 1–22. https://doi.org/10.1080/15715124.2026.2727417

Adebayo, A. D., & Nakalembe, C. (2026). Sub-seasonal forecasting of cropland productivity anomalies using satellite soil moisture in water-limited environments. Remote Sensing of Environment, 347, Article 115645. https://doi.org/10.1016/j.rse.2026.115645

Loboda, T., Chen, D., Caraballo-Vega, J., Bredder, A., & Orland, E. (2027). Wildfires in Alaska: Insights into fire occurrence, postfire impacts, and air quality implications. In C. Quintano, A. Fernández-Manso, J. M. Fernández-Guisuraga, & L. Calvo (Eds.), Advances in remote sensing for forest fire management (pp. 287–309). Elsevier. https://doi.org/10.1016/B978-0-443-41692-7.00015-9

Zhang, P., Yu, J., Wang, Z., Wang, R., & Xie, Y. (2026). Discovering coincident data across satellites in dynamic Arctic environments: Exploring scalable strategies for spatio-temporal joins on Apache Sedona. International Journal of Geographical Information Science, 1–37. https://doi.org/10.1080/13658816.2026.2718485

Tian, Y., Gong, W., Li, S., Li, M., & Zhao, F. (2026). High-resolution monthly estimation of disturbance-induced tropical forest carbon flux in the state of Rondônia, Brazilian Amazon. Forest Ecosystems, 13, Article 100534. https://doi.org/10.1016/j.fecs.2026.100534

He, C., Zhang, L. N., Leung, L. R., Richter, J. H., Bassett, C., Ferguson, C. R., Kumar, S., Olsen, M. A., Orr, M., Wang, H., Xue, Y., Attada, R., Berner, J., Draper, C., El Afandi, G., Fowler, M. D., Gerken, T., El Gharamti, M., Hu, A., Huang, M., … Zhang, Y. (2026). Harnessing land–atmosphere interactions to enhance subseasonal-to-seasonal predictability. Bulletin of the American Meteorological Society. Advance online publication. https://doi.org/10.1175/BAMS-D-25-0255.1

Lal, P., Armston, J., Bhogapurapu, N., Urbazaev, M., Siqueira, P., Wessels, K. J., Dubayah, R., & Duncanson, L. (2026). Multifrequency InSAR canopy height improves generalization of savanna biomass models. IEEE Geoscience and Remote Sensing Letters, 23, Article 2505705. https://doi.org/10.1109/LGRS.2026.3718772

Drozd, S., Kussul, N., Shelestov, A., & Skakun, S. (2026). Multi-agent explainable AI framework for forest disturbance analysis and biomass recovery modeling. In Explainable AI in Space (pp. 61–81). Communications in Computer and Information Science (Vol. 3107). Springer.