Graduate Student Publications
Adebayo, A. D., & Nakalembe, C. (2025). Forecasting agricultural drought impacts through satellite soil moisture products and deep learning in water-limited African regions [Abstract B31L-1876]. AGU Fall Meeting Abstracts 2025, 2025, B31L-1876.
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.
Adebayo, A. D., Nakalembe, C., Kerner, H. R., Zvonkov, I., Frimpong, D. B., & Skakun, S. (2024). Reconciling remote sensing and survey-based cropland area estimates in Africa [Abstract GC53F-0424]. AGU Fall Meeting Abstracts 2024, 2024, GC53F-0424.
Adebayo, A. D., Nakalembe, C., Skakun, S., Frimpong, D. B., Ginsburg, A., & Kerner, H. R. (2026). Optimizing satellite-based cropland area estimation through integrated map accuracy assessment and stratified sampling design across six African countries. International Journal of Applied Earth Observation and Geoinformation, 148, Article 104112.
Ghosh, A., Rambaud, P., Finegold, Y., Jonckheere, I., Martin-Ortega, P., Jalal, R., Adebayo, A. D., Alvarez, A., Borretti, M., Caela, J., Ghosh, T., Lindquist, E., & Henry, M. (2024). Monitoring Sustainable Development Goal indicator 15.3.1 on land degradation using SEPAL: Examples, challenges and prospects. Land, 13(7), Article 1027.
Nakalembe, C. L., Adebayo, A. D., Cosh, M., Mwangi, K., Mourice, S., & Okello, D. (2025, December 15–19). RootSense: Bridging in-situ and Earth observation data for agricultural drought resilience in Sub-Saharan Africa [Conference presentation]. AGU25 Annual Meeting, New Orleans, LA, United States.
Uponi, J., Alabi, W., Alabi, T., Khan, B., Ali, H. A., Adeluyi, O., & Olayide, O. (2026). Assessing maize and cassava extent and intercropping in southwest Nigeria. Environmental Research: Food Systems, 3(2), Article 025002.
Negash, E., de Perez, E. C., Peters, L. E. R., Asare-Ansah, A. B., Twongyirwe, R., & Van Den Hoek, J. (2026). Uneven hydroclimatic risk and land access constraints challenge refugee agricultural self-reliance in Uganda. Journal of Agriculture and Food Research, 21, Article 102942.
Twumasi, Y. A., Merem, E. C., Ning, Z. H., Yeboah, H. B., Loh, P. M., Osei, J. D., & Asare-Ansah, A. B. (2026). Coastal erosion and sea level rise in Louisiana: A critical analysis of the challenges, impacts, and mitigation strategies. International Journal of Geosciences, 17(5), 313–334.
Asare-Ansah, A. B., Nakalembe, C. L., Gadhiya, Y. H., & Van Den Hoek, J. (2025). Earth observation for humanitarian support: Mapping croplands in Northern Uganda's refugee-hosting communities [Abstract GC43L-0936]. AGU Fall Meeting Abstracts 2025, 2025, GC43L-0936.
Negash, E., Nakalembe, C. L., Asare-Ansah, A. B., & Van Den Hoek, J. (2025). Drought patterns and rainfall shifts undermine the resilience of Uganda's refugee integration model [Abstract GC31J-0798]. AGU Fall Meeting Abstracts 2025, 2025, GC31J-0798.
Oppong, J., Namwamba, J. B., Twumasi, Y. A., Ning, Z. H., & Asare-Ansah, A. B. (2025). Urbanization and urban forest loss: A spatial analysis of five metropolitan districts in Ghana. Geology, Ecology, and Landscapes, 9(1), 346–355.
Adebayo, A. D., Nakalembe, C. L., Kerner, H. R., Zvonkov, I., Frimpong, D. B., & Asare-Ansah, A. B. (2024). Reconciling remote sensing and survey-based cropland area estimates in Africa [Abstract GC53F-0424]. AGU Fall Meeting Abstracts 2024, 2024, GC53F-0424.
Mawusi, S. K., Nukpezah, D., Awudor, P., Oppong, J. C., Asare-Ansah, A. B., & Fosu-Mensah, B. Y. (2024). Reduced indoor air pollution but increased cooking time and fuelwood consumption of improved local cookstoves in Asuogyaman, Ghana: Implications for appropriate stove design. West African Journal of Applied Ecology, 32(2), 45–58.
Li, F., Baber, S., Sahajpal, R., Sadeh, Y., Becker-Reshef, I., & Nerry, F. (2026). Earth observation derived yield forecasting and estimation in low-and lower-middle-income countries dominated by smallholder agriculture: A review. International Journal of Applied Earth Observation and Geoinformation, 148, Article 104218.
Nair, S. S., Wagner, J., Skakun, S., Sadeh, Y., Gupta, M., Lampert, T., Hosseini, M., & Baber, S. (2026). In-season winter crop harvest status monitoring in Ukraine for 2022 using unsupervised change detection. Remote Sensing Applications: Society and Environment, 40, Article 101877.
Wagner, J., Skakun, S., Nair, S. S., Sadeh, Y., Baber, S., Oliinyk, O., Hosseini, M., Khan, M. A. Q., Sahajpal, R., & Becker-Reshef, I. (2026). Monitoring winter crop areas during wartime: Remote sensing support for Ukraine’s agricultural statistics. npj Sustainable Agriculture, 4(1), Article 1.
Baber, S., Sadeh, Y., Nair, S., Skakun, S., Blasch, G., Sahajpal, R., & Becker-Reshef, I. (2025, December 15–19). Mapping irrigation change in conflict zones and areas with little ground truth: Case studies in Ukraine and Ethiopia [Conference presentation]. AGU25 Annual Meeting, New Orleans, LA, United States.
Baber, S., Sadeh, Y., Skakun, S., Oliinyk, O., Hosseini, M., Khan, M. A. Q., & Becker-Reshef, I. (2025). Using Earth observation data to study the impacts of the Kakhovka Dam destruction on crop irrigation and agricultural management. SSRN.
Yailymov, B., Yailymova, H., Kolotii, A., Shelestov, A., Skakun, S., Baber, S., & Kussul, N. (2025). Flooded and irrigation area monitoring after the Kakhovka dam disaster based on machine learning and satellite data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 18, 4120–4132.
Yailymov, B., Yailymova, H., Kussul, N., Shelestov, A., Baber, S., & Skakun, S. (2025). Satellite-based assessment of agricultural transformation in war-affected Southern Ukraine. In IGARSS 2025 - 2025 IEEE International Geoscience and Remote Sensing Symposium (pp. 1102–1105). IEEE.
Baber, S., Sadeh, Y., Skakun, S., Oliinyk, O., Hosseini, M., Khan, M. A. Q., Nair, S., & Becker-Reshef, I. (2024). Destruction of the Kakhovka Reservoir in 2023 continues to desiccate agricultural lands in Southeastern Ukraine [Abstract GC33O-0341]. AGU Fall Meeting Abstracts 2024, 2024, GC33O-0341.
Becker-Reshef, I., Mitkish, M., Justice, C. O., Rhee, P., Skakun, S., Kerner, H. R., & Baber, S. (2024). Rapid agricultural assessments in support of agricultural policy and food security [Abstract GC22E-01]. AGU Fall Meeting Abstracts 2024, 2024, GC22E-01.
Gupta, M., Nair, S., Wagner, J., Skakun, S., Sadeh, Y., Khabbazan, S., & Baber, S. (2024). Multi-modal harvest monitoring at regional and field scales in the absence of ground truth data [Abstract GC13O-039]. AGU Fall Meeting Abstracts 2024, 2024, GC13O-039.
Ma, Y., Sadeh, Y., Baber, S., Oliinyk, O., Becker-Reshef, I., & Lobell, D. B. (2024). Using transfer learning to map winter wheat yields in Ukraine [Abstract GC23M-05]. AGU Fall Meeting Abstracts 2024, 2024, GC23M-05.
Oliinyk, O., Becker-Reshef, I., Wagner, J., Mitkish, M., Baber, S., Sadeh, Y., & Skakun, S. (2024). Case study: Public-private partnerships delivering efficient analytics in Ukraine during wartime [Abstract GC33O-0333]. AGU Fall Meeting Abstracts 2024, 2024, GC33O-0333.
Sadeh, Y., Baber, S., Ma, Y., Oliinyk, O., Leroux, L., Shiferaw, T., Blasch, G., & Becker-Reshef, I. (2024). Advancing field-scale yield prediction for data-limited agricultural regions [Abstract GC22E-02]. AGU Fall Meeting Abstracts 2024, 2024, GC22E-02.
Baber, S., Marcaida, M., & Becker-Reshef, I. (2023). Rice paddy transplanting detection in the Korean Peninsula using multiple Earth observation methods [Abstract GC41H-1196]. AGU Fall Meeting Abstracts 2023, 2023, GC41H-1196.
Becker-Reshef, I., Skakun, S., Wagner, J., Nair, S., Sadeh, Y., Khan, M. A. Q., & Baber, S. (2023). Bridging data gaps in war-torn Ukraine: NASA Harvest's partnership with Ukraine to assess the war's impact on agricultural production [Abstract SY43D-1068]. AGU Fall Meeting Abstracts 2023, 2023, SY43D-1068.
Hosseini, M., Becker-Reshef, I., Khabbazan, S., Wagner, J., Nair, S., Sadeh, Y., & Baber, S. (2023). Rapid response crop planting detection over Ukraine using synthetic aperture radar. In IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium (pp. 5123–5126). IEEE.
Nair, S. S., Becker-Reshef, I., Wagner, J., Sadeh, Y., Hosseini, M., Khabbazan, S., & Baber, S. (2023). A rapid assessment framework to monitor harvest progress in Ukraine [Abstract EGU-16834]. EGU General Assembly 2023, Vienna, Austria.
Sadeh, Y., Baber, S., Justice, C. J., Leroux, L., Blasch, G., Shiferaw, T., Wagner, J., & Becker-Reshef, I. (2023). Predicting agricultural output in challenging contexts: A study on crop yield estimation in conflict zones and smallholder farming systems [Abstract GC23A-07]. AGU Fall Meeting Abstracts 2023, 2023, GC23A-07.
Wagner, J., Becker-Reshef, I., Nair, S., Skakun, S., Sadeh, Y., Baber, S., & Hosseini, M. (2023). In-season progressive crop type mapping in war affected Ukraine [Abstract EGU-16685]. EGU General Assembly 2023, Vienna, Austria.
Baber, S., Wagner, J., Becker-Reshef, I., Li, F., Nair, S., Sadeh, Y., Skakun, S., & Hosseini, M. (2022). Rapid response in-season crop mapping for Ukraine using PlanetScope in light of the 2022 Russian invasion [Abstract GC32E-05]. AGU Fall Meeting Abstracts 2022, 2022, GC32E-05.
Tyukavina, A., Poulson, A. J., Pickering, J., Adusei, B., Hansen, M. C., Potapov, P., Song, Z., Pickens, A. H., Turubanova, S., Lima, A., & Hernandez-Serna, A. (2026). Global extent and drivers of tree cover loss quantified with high-resolution satellite data. Science, 392(6802), Article eadz9042.
Li, H., Song, X.-P., Adusei, B., Pickering, J., de Lima, A., Poulson, A., Baggett, A., Potapov, P., Khan, A., Zalles, V., Hernandez-Serna, A., Jantz, S. M., Pickens, A. H., Ortiz-Dominguez, C., Li, X., Kerr, T., Song, Z., Turubanova, S., Bongwele, E., … Hansen, M. C. (2025). 2019-2022 10-m maize and soybean maps over the United States (Version 2) [Data set]. figshare.
Li, H., Song, X.-P., Adusei, B., Pickering, J., Lima, A., Poulson, A., Baggett, A., Potapov, P., Khan, A., Zalles, V., Hernandez-Serna, A., Jantz, S. M., Pickens, A. H., Ortiz-Dominguez, C., Li, X., Kerr, T., Song, Z., Turubanova, S., Bongwele, E., … Hansen, M. C. (2025). An accurate 10 m annual crop map product of maize and soybean across the United States. Earth System Science Data Discussions, 1–33.
Pickens, A. H., Hansen, M. C., Song, Z., Poulson, A., Komarova, A., Baggett, A., Kerr, T., & Mikus, A. (2025). Rapid monitoring of global land change. Nature Communications, 16(1), Article 8948.
Li, H., Song, X.-P., Adusei, B., Pickering, J., Lima, A., Poulson, A. J., Baggett, A., Potapov, P., Khan, A., Zalles, V., Hernandez-Serna, A., Jantz, S. M., Pickens, A. H., Ortiz-Dominguez, C., Li, X., Kerr, T., Song, Z., Turubanova, S., Bongwele, E., … Hansen, M. C. (2024). Advancing 10-m crop mapping using all Sentinel-2 observations over the Contiguous United States [Abstract GC13O-0407]. AGU Fall Meeting Abstracts 2024, 2024, GC13O-0407.
Song, Z., Hansen, M., Pickens, A. H., Poulson, A. J., Baggett, A., Komarova, A., Kerr, T., Mikus, A., Adusei, B., Turubanova, S., & Potapov, P. (2024). DIST-ALERT: Near-real time monitoring system of land cover change [Abstract GC41B-02]. AGU Fall Meeting Abstracts 2024, 2024, GC41B-02.
Pickens, A. H., Hansen, M., Song, Z., Poulson, A. J., Lima, A., Baggett, A., Mikus, A., Kerr, T., Komarova, A., Adusei, B., Turubanova, S., & Potapov, P. (2023). DIST-ALERT: Global vegetation monitoring in near real-time [Abstract B23A-05]. AGU Fall Meeting Abstracts 2023, 2023, B23A-05.
Song, Z., Hansen, M., Pickens, A. H., Lima, A., Poulson, A. J., & Baggett, A. (2023). Mapping near real-time fractional vegetation cover based on Harmonized Landsat and Sentinel-2 data [Abstract IN42B-03]. AGU Fall Meeting Abstracts 2023, 2023, IN42B-03.
Potapov, P., Hansen, M. C., Pickens, A., Hernandez-Serna, A., Tyukavina, A., Turubanova, S., Zalles, V., Li, X., Khan, A., Stolle, F., Harris, N. L., Song, X.-P., Baggett, A., Komarova, A., & Karo, A. (2022). The global 2000–2020 land cover and land use change dataset derived from the Landsat archive: First results. Frontiers in Remote Sensing, 3, Article 856903.
Tyukavina, A., Hansen, M., Potapov, P., Pickering, J., Adusei, B., Poulson, A. J., & Song, Z. (2022). PlanetScope and Sentinel-2 data to quantify the extent and drivers of global forest loss: Sample-based analysis [Abstract IN42A-02]. AGU Fall Meeting Abstracts 2022, 2022, IN42A-02.
Vieira, D. C., Sanches, I. D. A., Montibeller, B., Prudente, V. H. R., Hansen, M. C., & Potapov, P. (2022). Cropland expansion, intensification, and reduction in Mato Grosso state, Brazil, between the crop years 2000/01 to 2017/18. Remote Sensing Applications: Society and Environment, 28, Article 100841.
Here are the formatted APA (7th edition) references for your list of papers, ordered from latest to oldest publication date (with duplicates removed and citations cleaned up):
References
Tyukavina, A., Poulson, A. J., Pickering, J., Adusei, B., Hansen, M. C., Potapov, P., Song, Z., Pickens, A. H., Turubanova, S., Lima, A., & Hernandez-Serna, A. (2026). Global extent and drivers of tree cover loss quantified with high-resolution satellite data. Science, 392(6802), Article eadz9042.
Li, H., Song, X.-P., Adusei, B., Pickering, J., de Lima, A., Poulson, A., Baggett, A., Potapov, P., Khan, A., Zalles, V., Hernandez-Serna, A., Jantz, S. M., Pickens, A. H., Ortiz-Dominguez, C., Li, X., Kerr, T., Song, Z., Turubanova, S., Bongwele, E., … Hansen, M. C. (2025). 2019-2022 10-m maize and soybean maps over the United States (Version 2) [Data set]. figshare.
Li, H., Song, X.-P., Adusei, B., Pickering, J., Lima, A., Poulson, A., Baggett, A., Potapov, P., Khan, A., Zalles, V., Hernandez-Serna, A., Jantz, S. M., Pickens, A. H., Ortiz-Dominguez, C., Li, X., Kerr, T., Song, Z., Turubanova, S., Bongwele, E., … Hansen, M. C. (2025). An accurate 10 m annual crop map product of maize and soybean across the United States. Earth System Science Data Discussions, 1–33.
Pickens, A. H., Hansen, M. C., Song, Z., Poulson, A., Komarova, A., Baggett, A., Kerr, T., & Mikus, A. (2025). Rapid monitoring of global land change. Nature Communications, 16(1), Article 8948.
Cited by: 33
Li, H., Song, X.-P., Adusei, B., Pickering, J., Lima, A., Poulson, A. J., Baggett, A., Potapov, P., Khan, A., Zalles, V., Hernandez-Serna, A., Jantz, S. M., Pickens, A. H., Ortiz-Dominguez, C., Li, X., Kerr, T., Song, Z., Turubanova, S., Bongwele, E., … Hansen, M. C. (2024). Advancing 10-m crop mapping using all Sentinel-2 observations over the Contiguous United States [Abstract GC13O-0407]. AGU Fall Meeting Abstracts 2024, 2024, GC13O-0407.
Song, Z., Hansen, M., Pickens, A. H., Poulson, A. J., Baggett, A., Komarova, A., Kerr, T., Mikus, A., Adusei, B., Turubanova, S., & Potapov, P. (2024). DIST-ALERT: Near-real time monitoring system of land cover change [Abstract GC41B-02]. AGU Fall Meeting Abstracts 2024, 2024, GC41B-02.
Pickens, A. H., Hansen, M., Song, Z., Poulson, A. J., Lima, A., Baggett, A., Mikus, A., Kerr, T., Komarova, A., Adusei, B., Turubanova, S., & Potapov, P. (2023). DIST-ALERT: Global vegetation monitoring in near real-time [Abstract B23A-05]. AGU Fall Meeting Abstracts 2023, 2023, B23A-05.
Song, Z., Hansen, M., Pickens, A. H., Lima, A., Poulson, A. J., & Baggett, A. (2023). Mapping near real-time fractional vegetation cover based on Harmonized Landsat and Sentinel-2 data [Abstract IN42B-03]. AGU Fall Meeting Abstracts 2023, 2023, IN42B-03.
Potapov, P., Hansen, M. C., Pickens, A., Hernandez-Serna, A., Tyukavina, A., Turubanova, S., Zalles, V., Li, X., Khan, A., Stolle, F., Harris, N. L., Song, X.-P., Baggett, A., Komarova, A., & Karo, A. (2022). The global 2000–2020 land cover and land use change dataset derived from the Landsat archive: First results. Frontiers in Remote Sensing, 3, Article 856903.
Cited by: 797
Tyukavina, A., Hansen, M., Potapov, P., Pickering, J., Adusei, B., Poulson, A. J., & Song, Z. (2022). PlanetScope and Sentinel-2 data to quantify the extent and drivers of global forest loss: Sample-based analysis [Abstract IN42A-02]. AGU Fall Meeting Abstracts 2022, 2022, IN42A-02.
Vieira, D. C., Sanches, I. D. A., Montibeller, B., Prudente, V. H. R., Hansen, M. C., & Potapov, P. (2022). Cropland expansion, intensification, and reduction in Mato Grosso state, Brazil, between the crop years 2000/01 to 2017/18. Remote Sensing Applications: Society and Environment, 28, Article 100841.
Here are the formatted APA (7th edition) references for your list of papers, ordered from latest to oldest publication date (with duplicates removed and citations cleaned up):
References
Tyukavina, A., Poulson, A. J., Pickering, J., Adusei, B., Hansen, M. C., Potapov, P., Song, Z., Pickens, A. H., Turubanova, S., Lima, A., & Hernandez-Serna, A. (2026). Global extent and drivers of tree cover loss quantified with high-resolution satellite data. Science, 392(6802), Article eadz9042.
Li, H., Song, X.-P., Adusei, B., Pickering, J., de Lima, A., Poulson, A., Baggett, A., Potapov, P., Khan, A., Zalles, V., Hernandez-Serna, A., Jantz, S. M., Pickens, A. H., Ortiz-Dominguez, C., Li, X., Kerr, T., Song, Z., Turubanova, S., Bongwele, E., … Hansen, M. C. (2025). 2019-2022 10-m maize and soybean maps over the United States (Version 2) [Data set]. figshare.
Li, H., Song, X.-P., Adusei, B., Pickering, J., Lima, A., Poulson, A., Baggett, A., Potapov, P., Khan, A., Zalles, V., Hernandez-Serna, A., Jantz, S. M., Pickens, A. H., Ortiz-Dominguez, C., Li, X., Kerr, T., Song, Z., Turubanova, S., Bongwele, E., … Hansen, M. C. (2025). An accurate 10 m annual crop map product of maize and soybean across the United States. Earth System Science Data Discussions, 1–33.
Pickens, A. H., Hansen, M. C., Song, Z., Poulson, A., Komarova, A., Baggett, A., Kerr, T., & Mikus, A. (2025). Rapid monitoring of global land change. Nature Communications, 16(1), Article 8948.
Cited by: 33
Li, H., Song, X.-P., Adusei, B., Pickering, J., Lima, A., Poulson, A. J., Baggett, A., Potapov, P., Khan, A., Zalles, V., Hernandez-Serna, A., Jantz, S. M., Pickens, A. H., Ortiz-Dominguez, C., Li, X., Kerr, T., Song, Z., Turubanova, S., Bongwele, E., … Hansen, M. C. (2024). Advancing 10-m crop mapping using all Sentinel-2 observations over the Contiguous United States [Abstract GC13O-0407]. AGU Fall Meeting Abstracts 2024, 2024, GC13O-0407.
Song, Z., Hansen, M., Pickens, A. H., Poulson, A. J., Baggett, A., Komarova, A., Kerr, T., Mikus, A., Adusei, B., Turubanova, S., & Potapov, P. (2024). DIST-ALERT: Near-real time monitoring system of land cover change [Abstract GC41B-02]. AGU Fall Meeting Abstracts 2024, 2024, GC41B-02.
Pickens, A. H., Hansen, M., Song, Z., Poulson, A. J., Lima, A., Baggett, A., Mikus, A., Kerr, T., Komarova, A., Adusei, B., Turubanova, S., & Potapov, P. (2023). DIST-ALERT: Global vegetation monitoring in near real-time [Abstract B23A-05]. AGU Fall Meeting Abstracts 2023, 2023, B23A-05.
Song, Z., Hansen, M., Pickens, A. H., Lima, A., Poulson, A. J., & Baggett, A. (2023). Mapping near real-time fractional vegetation cover based on Harmonized Landsat and Sentinel-2 data [Abstract IN42B-03]. AGU Fall Meeting Abstracts 2023, 2023, IN42B-03.
Potapov, P., Hansen, M. C., Pickens, A., Hernandez-Serna, A., Tyukavina, A., Turubanova, S., Zalles, V., Li, X., Khan, A., Stolle, F., Harris, N. L., Song, X.-P., Baggett, A., Komarova, A., & Karo, A. (2022). The global 2000–2020 land cover and land use change dataset derived from the Landsat archive: First results. Frontiers in Remote Sensing, 3, Article 856903.
Cited by: 797
Tyukavina, A., Hansen, M., Potapov, P., Pickering, J., Adusei, B., Poulson, A. J., & Song, Z. (2022). PlanetScope and Sentinel-2 data to quantify the extent and drivers of global forest loss: Sample-based analysis [Abstract IN42A-02]. AGU Fall Meeting Abstracts 2022, 2022, IN42A-02.
Vieira, D. C., Sanches, I. D. A., Montibeller, B., Prudente, V. H. R., Hansen, M. C., & Potapov, P. (2022). Cropland expansion, intensification, and reduction in Mato Grosso state, Brazil, between the crop years 2000/01 to 2017/18. Remote Sensing Applications: Society and Environment, 28, Article 100841.
Here are the formatted APA (7th edition) references for your list of papers, ordered from latest to oldest publication date (with duplicates removed and citations cleaned up):
References
Tyukavina, A., Poulson, A. J., Pickering, J., Adusei, B., Hansen, M. C., Potapov, P., Song, Z., Pickens, A. H., Turubanova, S., Lima, A., & Hernandez-Serna, A. (2026). Global extent and drivers of tree cover loss quantified with high-resolution satellite data. Science, 392(6802), Article eadz9042.
Li, H., Song, X.-P., Adusei, B., Pickering, J., de Lima, A., Poulson, A., Baggett, A., Potapov, P., Khan, A., Zalles, V., Hernandez-Serna, A., Jantz, S. M., Pickens, A. H., Ortiz-Dominguez, C., Li, X., Kerr, T., Song, Z., Turubanova, S., Bongwele, E., … Hansen, M. C. (2025). 2019-2022 10-m maize and soybean maps over the United States (Version 2) [Data set]. figshare.
Li, H., Song, X.-P., Adusei, B., Pickering, J., Lima, A., Poulson, A., Baggett, A., Potapov, P., Khan, A., Zalles, V., Hernandez-Serna, A., Jantz, S. M., Pickens, A. H., Ortiz-Dominguez, C., Li, X., Kerr, T., Song, Z., Turubanova, S., Bongwele, E., … Hansen, M. C. (2025). An accurate 10 m annual crop map product of maize and soybean across the United States. Earth System Science Data Discussions, 1–33.
Pickens, A. H., Hansen, M. C., Song, Z., Poulson, A., Komarova, A., Baggett, A., Kerr, T., & Mikus, A. (2025). Rapid monitoring of global land change. Nature Communications, 16(1), Article 8948.
Cited by: 33
Li, H., Song, X.-P., Adusei, B., Pickering, J., Lima, A., Poulson, A. J., Baggett, A., Potapov, P., Khan, A., Zalles, V., Hernandez-Serna, A., Jantz, S. M., Pickens, A. H., Ortiz-Dominguez, C., Li, X., Kerr, T., Song, Z., Turubanova, S., Bongwele, E., … Hansen, M. C. (2024). Advancing 10-m crop mapping using all Sentinel-2 observations over the Contiguous United States [Abstract GC13O-0407]. AGU Fall Meeting Abstracts 2024, 2024, GC13O-0407.
Song, Z., Hansen, M., Pickens, A. H., Poulson, A. J., Baggett, A., Komarova, A., Kerr, T., Mikus, A., Adusei, B., Turubanova, S., & Potapov, P. (2024). DIST-ALERT: Near-real time monitoring system of land cover change [Abstract GC41B-02]. AGU Fall Meeting Abstracts 2024, 2024, GC41B-02.
Pickens, A. H., Hansen, M., Song, Z., Poulson, A. J., Lima, A., Baggett, A., Mikus, A., Kerr, T., Komarova, A., Adusei, B., Turubanova, S., & Potapov, P. (2023). DIST-ALERT: Global vegetation monitoring in near real-time [Abstract B23A-05]. AGU Fall Meeting Abstracts 2023, 2023, B23A-05.
Song, Z., Hansen, M., Pickens, A. H., Lima, A., Poulson, A. J., & Baggett, A. (2023). Mapping near real-time fractional vegetation cover based on Harmonized Landsat and Sentinel-2 data [Abstract IN42B-03]. AGU Fall Meeting Abstracts 2023, 2023, IN42B-03.
Potapov, P., Hansen, M. C., Pickens, A., Hernandez-Serna, A., Tyukavina, A., Turubanova, S., Zalles, V., Li, X., Khan, A., Stolle, F., Harris, N. L., Song, X.-P., Baggett, A., Komarova, A., & Karo, A. (2022). The global 2000–2020 land cover and land use change dataset derived from the Landsat archive: First results. Frontiers in Remote Sensing, 3, Article 856903.
Cited by: 797
Tyukavina, A., Hansen, M., Potapov, P., Pickering, J., Adusei, B., Poulson, A. J., & Song, Z. (2022). PlanetScope and Sentinel-2 data to quantify the extent and drivers of global forest loss: Sample-based analysis [Abstract IN42A-02]. AGU Fall Meeting Abstracts 2022, 2022, IN42A-02.
Vieira, D. C., Sanches, I. D. A., Montibeller, B., Prudente, V. H. R., Hansen, M. C., & Potapov, P. (2022). Cropland expansion, intensification, and reduction in Mato Grosso state, Brazil, between the crop years 2000/01 to 2017/18. Remote Sensing Applications: Society and Environment, 28, Article 100841.
Here are the formatted APA (7th edition) references for your list of papers, ordered from latest to oldest publication date (with duplicates removed and citations cleaned up):
References
Tyukavina, A., Poulson, A. J., Pickering, J., Adusei, B., Hansen, M. C., Potapov, P., Song, Z., Pickens, A. H., Turubanova, S., Lima, A., & Hernandez-Serna, A. (2026). Global extent and drivers of tree cover loss quantified with high-resolution satellite data. Science, 392(6802), Article eadz9042.
Li, H., Song, X.-P., Adusei, B., Pickering, J., de Lima, A., Poulson, A., Baggett, A., Potapov, P., Khan, A., Zalles, V., Hernandez-Serna, A., Jantz, S. M., Pickens, A. H., Ortiz-Dominguez, C., Li, X., Kerr, T., Song, Z., Turubanova, S., Bongwele, E., … Hansen, M. C. (2025). 2019-2022 10-m maize and soybean maps over the United States (Version 2) [Data set]. figshare.
Li, H., Song, X.-P., Adusei, B., Pickering, J., Lima, A., Poulson, A., Baggett, A., Potapov, P., Khan, A., Zalles, V., Hernandez-Serna, A., Jantz, S. M., Pickens, A. H., Ortiz-Dominguez, C., Li, X., Kerr, T., Song, Z., Turubanova, S., Bongwele, E., … Hansen, M. C. (2025). An accurate 10 m annual crop map product of maize and soybean across the United States. Earth System Science Data Discussions, 1–33.
Pickens, A. H., Hansen, M. C., Song, Z., Poulson, A., Komarova, A., Baggett, A., Kerr, T., & Mikus, A. (2025). Rapid monitoring of global land change. Nature Communications, 16(1), Article 8948.
Cited by: 33
Li, H., Song, X.-P., Adusei, B., Pickering, J., Lima, A., Poulson, A. J., Baggett, A., Potapov, P., Khan, A., Zalles, V., Hernandez-Serna, A., Jantz, S. M., Pickens, A. H., Ortiz-Dominguez, C., Li, X., Kerr, T., Song, Z., Turubanova, S., Bongwele, E., … Hansen, M. C. (2024). Advancing 10-m crop mapping using all Sentinel-2 observations over the Contiguous United States [Abstract GC13O-0407]. AGU Fall Meeting Abstracts 2024, 2024, GC13O-0407.
Song, Z., Hansen, M., Pickens, A. H., Poulson, A. J., Baggett, A., Komarova, A., Kerr, T., Mikus, A., Adusei, B., Turubanova, S., & Potapov, P. (2024). DIST-ALERT: Near-real time monitoring system of land cover change [Abstract GC41B-02]. AGU Fall Meeting Abstracts 2024, 2024, GC41B-02.
Pickens, A. H., Hansen, M., Song, Z., Poulson, A. J., Lima, A., Baggett, A., Mikus, A., Kerr, T., Komarova, A., Adusei, B., Turubanova, S., & Potapov, P. (2023). DIST-ALERT: Global vegetation monitoring in near real-time [Abstract B23A-05]. AGU Fall Meeting Abstracts 2023, 2023, B23A-05.
Song, Z., Hansen, M., Pickens, A. H., Lima, A., Poulson, A. J., & Baggett, A. (2023). Mapping near real-time fractional vegetation cover based on Harmonized Landsat and Sentinel-2 data [Abstract IN42B-03]. AGU Fall Meeting Abstracts 2023, 2023, IN42B-03.
Potapov, P., Hansen, M. C., Pickens, A., Hernandez-Serna, A., Tyukavina, A., Turubanova, S., Zalles, V., Li, X., Khan, A., Stolle, F., Harris, N. L., Song, X.-P., Baggett, A., Komarova, A., & Karo, A. (2022). The global 2000–2020 land cover and land use change dataset derived from the Landsat archive: First results. Frontiers in Remote Sensing, 3, Article 856903.
Cited by: 797
Tyukavina, A., Hansen, M., Potapov, P., Pickering, J., Adusei, B., Poulson, A. J., & Song, Z. (2022). PlanetScope and Sentinel-2 data to quantify the extent and drivers of global forest loss: Sample-based analysis [Abstract IN42A-02]. AGU Fall Meeting Abstracts 2022, 2022, IN42A-02.
Vieira, D. C., Sanches, I. D. A., Montibeller, B., Prudente, V. H. R., Hansen, M. C., & Potapov, P. (2022). Cropland expansion, intensification, and reduction in Mato Grosso state, Brazil, between the crop years 2000/01 to 2017/18. Remote Sensing Applications: Society and Environment, 28, Article 100841.
Here are the formatted APA (7th edition) references for your list of papers, ordered from latest to oldest publication date (with duplicates removed and citations cleaned up):
References
Tyukavina, A., Poulson, A. J., Pickering, J., Adusei, B., Hansen, M. C., Potapov, P., Song, Z., Pickens, A. H., Turubanova, S., Lima, A., & Hernandez-Serna, A. (2026). Global extent and drivers of tree cover loss quantified with high-resolution satellite data. Science, 392(6802), Article eadz9042.
Li, H., Song, X.-P., Adusei, B., Pickering, J., de Lima, A., Poulson, A., Baggett, A., Potapov, P., Khan, A., Zalles, V., Hernandez-Serna, A., Jantz, S. M., Pickens, A. H., Ortiz-Dominguez, C., Li, X., Kerr, T., Song, Z., Turubanova, S., Bongwele, E., … Hansen, M. C. (2025). 2019-2022 10-m maize and soybean maps over the United States (Version 2) [Data set]. figshare.
Li, H., Song, X.-P., Adusei, B., Pickering, J., Lima, A., Poulson, A., Baggett, A., Potapov, P., Khan, A., Zalles, V., Hernandez-Serna, A., Jantz, S. M., Pickens, A. H., Ortiz-Dominguez, C., Li, X., Kerr, T., Song, Z., Turubanova, S., Bongwele, E., … Hansen, M. C. (2025). An accurate 10 m annual crop map product of maize and soybean across the United States. Earth System Science Data Discussions, 1–33.
Pickens, A. H., Hansen, M. C., Song, Z., Poulson, A., Komarova, A., Baggett, A., Kerr, T., & Mikus, A. (2025). Rapid monitoring of global land change. Nature Communications, 16(1), Article 8948.
Li, H., Song, X.-P., Adusei, B., Pickering, J., Lima, A., Poulson, A. J., Baggett, A., Potapov, P., Khan, A., Zalles, V., Hernandez-Serna, A., Jantz, S. M., Pickens, A. H., Ortiz-Dominguez, C., Li, X., Kerr, T., Song, Z., Turubanova, S., Bongwele, E., … Hansen, M. C. (2024). Advancing 10-m crop mapping using all Sentinel-2 observations over the Contiguous United States [Abstract GC13O-0407]. AGU Fall Meeting Abstracts 2024, 2024, GC13O-0407.
Song, Z., Hansen, M., Pickens, A. H., Poulson, A. J., Baggett, A., Komarova, A., Kerr, T., Mikus, A., Adusei, B., Turubanova, S., & Potapov, P. (2024). DIST-ALERT: Near-real time monitoring system of land cover change [Abstract GC41B-02]. AGU Fall Meeting Abstracts 2024, 2024, GC41B-02.
Pickens, A. H., Hansen, M., Song, Z., Poulson, A. J., Lima, A., Baggett, A., Mikus, A., Kerr, T., Komarova, A., Adusei, B., Turubanova, S., & Potapov, P. (2023). DIST-ALERT: Global vegetation monitoring in near real-time [Abstract B23A-05]. AGU Fall Meeting Abstracts 2023, 2023, B23A-05.
Song, Z., Hansen, M., Pickens, A. H., Lima, A., Poulson, A. J., & Baggett, A. (2023). Mapping near real-time fractional vegetation cover based on Harmonized Landsat and Sentinel-2 data [Abstract IN42B-03]. AGU Fall Meeting Abstracts 2023, 2023, IN42B-03.
Potapov, P., Hansen, M. C., Pickens, A., Hernandez-Serna, A., Tyukavina, A., Turubanova, S., Zalles, V., Li, X., Khan, A., Stolle, F., Harris, N. L., Song, X.-P., Baggett, A., Komarova, A., & Karo, A. (2022). The global 2000–2020 land cover and land use change dataset derived from the Landsat archive: First results. Frontiers in Remote Sensing, 3, Article 856903.
Tyukavina, A., Hansen, M., Potapov, P., Pickering, J., Adusei, B., Poulson, A. J., & Song, Z. (2022). PlanetScope and Sentinel-2 data to quantify the extent and drivers of global forest loss: Sample-based analysis [Abstract IN42A-02]. AGU Fall Meeting Abstracts 2022, 2022, IN42A-02.
Vieira, D. C., Sanches, I. D. A., Montibeller, B., Prudente, V. H. R., Hansen, M. C., & Potapov, P. (2022). Cropland expansion, intensification, and reduction in Mato Grosso state, Brazil, between the crop years 2000/01 to 2017/18. Remote Sensing Applications: Society and Environment, 28, Article 100841.
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Chakravarty, S., Mullally, C., Gars, J., & Saha, M. (2026). Workfare and forest cover: The case of NREGS in India. Journal of the Agricultural and Applied Economics Association, 5(1), 82–96.
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Xu, S., Wang, Z., Li, R., Wang, R., Ma, L., Hurtt, G. C., Jia, X., & Xie, Y. (2026). Knowledge-guided learning for global carbon flux prediction: Integrating high-level remote sensing with bottom-up physical modeling. In Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 3810–3821). Association for Computing Machinery.
Wang, Z., Li, C., Wang, R., Ma, L., Hurtt, G., Jia, X., Mai, G., Li, Z., & Xie, Y. (2026). TreeFinder [Model and dataset]. Hugging Face.
Wang, Z., Li, C., Wang, R., Ma, L., Hurtt, G., Jia, X., Mai, G., Li, Z., & Xie, Y. (2026). TreeFinder: A US-scale benchmark dataset for individual tree mortality monitoring using high-resolution aerial imagery. Advances in Neural Information Processing Systems, 38, 10245–10258.
Zhang, P., Yu, J., Wang, Z., Wang, R., & Xie, Y. (2026). Discover coincident data across satellites in dynamic Arctic environments: Exploring scalable strategies for spatio-temporal joins on Apache Sedona. International Journal of Geographical Information Science, 40(3), 1–37.
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Wang, R., Xie, Y., Du, L., Duncan, K., & Farrell, S. L. (2025). A coincident data discovery engine and web-portal for global-scale cross-platform data search [Abstract IN43B-0412]. AGU Fall Meeting Abstracts 2025, 2025, IN43B-0412.
Wang, R., Xie, Y., Du, L., Yu, J., Duncan, K., Farrell, S., Li, Z., & Chai, K. (2025). Coincident Data Discovery Engine: A portal for global-scale cross-platform satellite data search. In Proceedings of the 33rd ACM International Conference on Advances in Geographic Information Systems (pp. 410–414). Association for Computing Machinery.
Wang, Z., Xie, Y., Jia, X., Ma, L., Wang, R., Ott, L., & Hurtt, G. C. (2025). DeepED: A deep learning emulator for uncovering ecosystem tipping points under intermediate climate scenarios [Abstract B22D-07]. AGU Fall Meeting Abstracts 2025, 2025, B22D-07.
Xu, S., Wang, Z., Wang, R., Jia, X., Ma, L., Hurtt, G. C., & Xie, Y. (2025). Knowledge-guided assimilation to bridge the gap between sensing and modeling with indirect labels for global-scale carbon monitoring (arXiv:2509.12345). arXiv.
Xu, S., Xie, Y., Jia, X., Wang, Z., Ma, L., Hurtt, G. C., Wang, R., & Li, R. (2025). Knowledge-guided machine learning to enhance ecosystem carbon estimation with in-situ observations [Abstract B24B-04]. AGU Fall Meeting Abstracts 2025, 2025, B24B-04.
Xie, Y., Wang, Z., Chen, W., Li, Z., Jia, X., Li, Y., Wang, R., Chai, K., Li, R., & Skakun, S. (2024). When are foundation models effective? Understanding the suitability for pixel-level classification using multispectral imagery (arXiv:2404.11797). arXiv.
Here are the formatted APA (7th edition) references for your list of papers, cleaned up and ordered from latest to oldest publication date:
References
Wang, Z., Wang, R., Li, R., Ma, L., Hurtt, G., Jia, X., Mai, G., Wang, S., & Xie, Y. (2026). Earth system world model for what-if simulations: A case study for terrestrial ecosystems (arXiv:2609.08855). arXiv.
Xu, S., Wang, Z., Li, R., Wang, R., Ma, L., Hurtt, G. C., Jia, X., & Xie, Y. (2026). Knowledge-guided learning for global carbon flux prediction: Integrating high-level remote sensing with bottom-up physical modeling. In Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 3810–3821). Association for Computing Machinery.
Wang, Z., Li, C., Wang, R., Ma, L., Hurtt, G., Jia, X., Mai, G., Li, Z., & Xie, Y. (2026). TreeFinder [Model and dataset]. Hugging Face.
Wang, Z., Li, C., Wang, R., Ma, L., Hurtt, G., Jia, X., Mai, G., Li, Z., & Xie, Y. (2026). TreeFinder: A US-scale benchmark dataset for individual tree mortality monitoring using high-resolution aerial imagery. Advances in Neural Information Processing Systems, 38, 10245–10258.
Zhang, P., Yu, J., Wang, Z., Wang, R., & Xie, Y. (2026). Discover coincident data across satellites in dynamic Arctic environments: Exploring scalable strategies for spatio-temporal joins on Apache Sedona. International Journal of Geographical Information Science, 40(3), 1–37.
Wang, R., Li, C., Hou, S., Lu, A., Wang, Z., Jia, X., & Xie, Y. (2025). Characterizing the effectiveness of DINOv2 as an off-the-shelf foundation model for Earth monitoring tasks: Preliminary results. In Proceedings of the 4th ACM SIGSPATIAL International Workshop on Spatial Big Data and AI (pp. 12–21). Association for Computing Machinery.
Wang, R., Xie, Y., Du, L., Duncan, K., & Farrell, S. L. (2025). A coincident data discovery engine and web-portal for global-scale cross-platform data search [Abstract IN43B-0412]. AGU Fall Meeting Abstracts 2025, 2025, IN43B-0412.
Wang, R., Xie, Y., Du, L., Yu, J., Duncan, K., Farrell, S., Li, Z., & Chai, K. (2025). Coincident Data Discovery Engine: A portal for global-scale cross-platform satellite data search. In Proceedings of the 33rd ACM International Conference on Advances in Geographic Information Systems (pp. 410–414). Association for Computing Machinery.
Wang, Z., Xie, Y., Jia, X., Ma, L., Wang, R., Ott, L., & Hurtt, G. C. (2025). DeepED: A deep learning emulator for uncovering ecosystem tipping points under intermediate climate scenarios [Abstract B22D-07]. AGU Fall Meeting Abstracts 2025, 2025, B22D-07.
Xu, S., Wang, Z., Wang, R., Jia, X., Ma, L., Hurtt, G. C., & Xie, Y. (2025). Knowledge-guided assimilation to bridge the gap between sensing and modeling with indirect labels for global-scale carbon monitoring (arXiv:2509.12345). arXiv.
Xu, S., Xie, Y., Jia, X., Wang, Z., Ma, L., Hurtt, G. C., Wang, R., & Li, R. (2025). Knowledge-guided machine learning to enhance ecosystem carbon estimation with in-situ observations [Abstract B24B-04]. AGU Fall Meeting Abstracts 2025, 2025, B24B-04.
Xie, Y., Wang, Z., Chen, W., Li, Z., Jia, X., Li, Y., Wang, R., Chai, K., Li, R., & Skakun, S. (2024). When are foundation models effective? Understanding the suitability for pixel-level classification using multispectral imagery (arXiv:2404.11797). arXiv.
Here are the formatted APA (7th edition) references for your list of papers, cleaned up and ordered from latest to oldest publication date:
References
Wang, Z., Wang, R., Li, R., Ma, L., Hurtt, G., Jia, X., Mai, G., Wang, S., & Xie, Y. (2026). Earth system world model for what-if simulations: A case study for terrestrial ecosystems (arXiv:2609.08855). arXiv.
Xu, S., Wang, Z., Li, R., Wang, R., Ma, L., Hurtt, G. C., Jia, X., & Xie, Y. (2026). Knowledge-guided learning for global carbon flux prediction: Integrating high-level remote sensing with bottom-up physical modeling. In Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 3810–3821). Association for Computing Machinery.
Wang, Z., Li, C., Wang, R., Ma, L., Hurtt, G., Jia, X., Mai, G., Li, Z., & Xie, Y. (2026). TreeFinder [Model and dataset]. Hugging Face.
Wang, Z., Li, C., Wang, R., Ma, L., Hurtt, G., Jia, X., Mai, G., Li, Z., & Xie, Y. (2026). TreeFinder: A US-scale benchmark dataset for individual tree mortality monitoring using high-resolution aerial imagery. Advances in Neural Information Processing Systems, 38, 10245–10258.
Zhang, P., Yu, J., Wang, Z., Wang, R., & Xie, Y. (2026). Discover coincident data across satellites in dynamic Arctic environments: Exploring scalable strategies for spatio-temporal joins on Apache Sedona. International Journal of Geographical Information Science, 40(3), 1–37.
Wang, R., Li, C., Hou, S., Lu, A., Wang, Z., Jia, X., & Xie, Y. (2025). Characterizing the effectiveness of DINOv2 as an off-the-shelf foundation model for Earth monitoring tasks: Preliminary results. In Proceedings of the 4th ACM SIGSPATIAL International Workshop on Spatial Big Data and AI (pp. 12–21). Association for Computing Machinery.
Wang, R., Xie, Y., Du, L., Duncan, K., & Farrell, S. L. (2025). A coincident data discovery engine and web-portal for global-scale cross-platform data search [Abstract IN43B-0412]. AGU Fall Meeting Abstracts 2025, 2025, IN43B-0412.
Wang, R., Xie, Y., Du, L., Yu, J., Duncan, K., Farrell, S., Li, Z., & Chai, K. (2025). Coincident Data Discovery Engine: A portal for global-scale cross-platform satellite data search. In Proceedings of the 33rd ACM International Conference on Advances in Geographic Information Systems (pp. 410–414). Association for Computing Machinery.
Wang, Z., Xie, Y., Jia, X., Ma, L., Wang, R., Ott, L., & Hurtt, G. C. (2025). DeepED: A deep learning emulator for uncovering ecosystem tipping points under intermediate climate scenarios [Abstract B22D-07]. AGU Fall Meeting Abstracts 2025, 2025, B22D-07.
Xu, S., Wang, Z., Wang, R., Jia, X., Ma, L., Hurtt, G. C., & Xie, Y. (2025). Knowledge-guided assimilation to bridge the gap between sensing and modeling with indirect labels for global-scale carbon monitoring (arXiv:2509.12345). arXiv.
Xu, S., Xie, Y., Jia, X., Wang, Z., Ma, L., Hurtt, G. C., Wang, R., & Li, R. (2025). Knowledge-guided machine learning to enhance ecosystem carbon estimation with in-situ observations [Abstract B24B-04]. AGU Fall Meeting Abstracts 2025, 2025, B24B-04.
Xie, Y., Wang, Z., Chen, W., Li, Z., Jia, X., Li, Y., Wang, R., Chai, K., Li, R., & Skakun, S. (2024). When are foundation models effective? Understanding the suitability for pixel-level classification using multispectral imagery (arXiv:2404.11797). arXiv.
Here are the formatted APA (7th edition) references for your list of papers, cleaned up and ordered from latest to oldest publication date:
References
Wang, Z., Wang, R., Li, R., Ma, L., Hurtt, G., Jia, X., Mai, G., Wang, S., & Xie, Y. (2026). Earth system world model for what-if simulations: A case study for terrestrial ecosystems (arXiv:2609.08855). arXiv.
Xu, S., Wang, Z., Li, R., Wang, R., Ma, L., Hurtt, G. C., Jia, X., & Xie, Y. (2026). Knowledge-guided learning for global carbon flux prediction: Integrating high-level remote sensing with bottom-up physical modeling. In Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 3810–3821). Association for Computing Machinery.
Wang, Z., Li, C., Wang, R., Ma, L., Hurtt, G., Jia, X., Mai, G., Li, Z., & Xie, Y. (2026). TreeFinder [Model and dataset]. Hugging Face.
Wang, Z., Li, C., Wang, R., Ma, L., Hurtt, G., Jia, X., Mai, G., Li, Z., & Xie, Y. (2026). TreeFinder: A US-scale benchmark dataset for individual tree mortality monitoring using high-resolution aerial imagery. Advances in Neural Information Processing Systems, 38, 10245–10258.
Zhang, P., Yu, J., Wang, Z., Wang, R., & Xie, Y. (2026). Discover coincident data across satellites in dynamic Arctic environments: Exploring scalable strategies for spatio-temporal joins on Apache Sedona. International Journal of Geographical Information Science, 40(3), 1–37.
Wang, R., Li, C., Hou, S., Lu, A., Wang, Z., Jia, X., & Xie, Y. (2025). Characterizing the effectiveness of DINOv2 as an off-the-shelf foundation model for Earth monitoring tasks: Preliminary results. In Proceedings of the 4th ACM SIGSPATIAL International Workshop on Spatial Big Data and AI (pp. 12–21). Association for Computing Machinery.
Wang, R., Xie, Y., Du, L., Duncan, K., & Farrell, S. L. (2025). A coincident data discovery engine and web-portal for global-scale cross-platform data search [Abstract IN43B-0412]. AGU Fall Meeting Abstracts 2025, 2025, IN43B-0412.
Wang, R., Xie, Y., Du, L., Yu, J., Duncan, K., Farrell, S., Li, Z., & Chai, K. (2025). Coincident Data Discovery Engine: A portal for global-scale cross-platform satellite data search. In Proceedings of the 33rd ACM International Conference on Advances in Geographic Information Systems (pp. 410–414). Association for Computing Machinery.
Wang, Z., Xie, Y., Jia, X., Ma, L., Wang, R., Ott, L., & Hurtt, G. C. (2025). DeepED: A deep learning emulator for uncovering ecosystem tipping points under intermediate climate scenarios [Abstract B22D-07]. AGU Fall Meeting Abstracts 2025, 2025, B22D-07.
Xu, S., Wang, Z., Wang, R., Jia, X., Ma, L., Hurtt, G. C., & Xie, Y. (2025). Knowledge-guided assimilation to bridge the gap between sensing and modeling with indirect labels for global-scale carbon monitoring (arXiv:2509.12345). arXiv.
Xu, S., Xie, Y., Jia, X., Wang, Z., Ma, L., Hurtt, G. C., Wang, R., & Li, R. (2025). Knowledge-guided machine learning to enhance ecosystem carbon estimation with in-situ observations [Abstract B24B-04]. AGU Fall Meeting Abstracts 2025, 2025, B24B-04.
Xie, Y., Wang, Z., Chen, W., Li, Z., Jia, X., Li, Y., Wang, R., Chai, K., Li, R., & Skakun, S. (2024). When are foundation models effective? Understanding the suitability for pixel-level classification using multispectral imagery (arXiv:2404.11797). arXiv.
Tan, N. S., Gautam, R., Tan, F., Sarkawi, G. M., Majewski, J. M., Komori, J., Wee, S. J., & Meltzner, A. J. (2025). Three-dimensional models of coral microatolls using structure-from-motion photogrammetry and iPhone lidar scanning: A fast, reproducible method for collecting relative sea-level data in the field. Science of Remote Sensing, 11, Article 100288.
Tan, F., Horton, B. P., Lin, K., Li, T., Quye-Sawyer, J., Lim, J. T. Y., Peng, D., Aw, Z., & Meltzner, A. J. (2024). Late Holocene relative sea-level records from coral microatolls in Singapore. Scientific Reports, 14(1), Article 13458.
Tan, F., Horton, B., Lin, K., Li, T., Upton, M., Lin, Y., Walker, J., Ng, T., & Meltzner, A. (2024). Drivers of Late Holocene relative sea-level change in the Sunda Shelf: New insights from coral microatolls in Singapore [Paper presentation]. European Geosciences Union (EGU) General Assembly 2024, Vienna, Austria.
Wee, S. J., Park, E., Alcantara, E., & Lee, J. S. H. (2024). Exploring multi-driver influences on Indonesia's biomass fire patterns from 2002 to 2019 through geographically weighted regression. Journal of Geovisualization and Spatial Analysis, 8(1), Article 4.
Zhou, S., Yang, J., Shen, X., Yao, X., & Ma, X. (2025). Environmental footprint assessment of China's lithium iron phosphate battery production from energy-carbon-water-economic nexus insight. The International Journal of Life Cycle Assessment, 30(12), 3342–3355.
Zhang, C., Meng, M., Chen, Z., Du, W., Dong, W., Wang, J., Gao, B., Yi, F., Zhu, K., & Wang, Q. (2026). Wavelength-specific urban nighttime light modulates expressed sentiment across China. Nature Cities, 3(3), 261–272.
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