Publications related to Geospatial-Information Science and Remote Sensing | Geographical Sciences Department

Xu, S., Wang, D., Liang, S., Jia, A., Li, R., Wang, Z., & Liu, Y. (2024). A novel approach to estimate land surface temperature from landsat top-of-atmosphere reflective and emissive data using transfer-learning neural network. Science of The Total Environment, 176783.
Jia, A., Liang, S., Wang, D., Mallick, K., Zhou, S., Hu, T., & Xu, S. (2024). Advances in Methodology and Generation of All-Weather Land Surface Temperature Products From Polar-Orbiting and Geostationary Satellites: A comprehensive review. IEEE Geoscience and Remote Sensing Magazine.
Hall, J. V., Argueta, F., & Giglio, L. (2024). GloCAB Cropland Field Boundary Dataset. Data in Brief, 110739
Xu, H., E. Ragno, S. N. Jonkman, J. Wang, J. D. Bricker, Z. Tian, L. Sun. 2024. “Combining statistical and hydrodynamic models to assess compound flood hazards from rainfall and storm surge: a case study of Shanghai.” Hydrology and Earth System Sciences(2022 IF: 6.3). Vol. 28, issue 16, pp. 3919–3930. https://doi.org/10.5194/hess-28-3919-2024. Combining statistical and hydrodynamic models to assess compound flood hazards from rainfall and storm surge A case study of Shanghai_Hess-28-3919-2024.pdf5.49 MB
Zubkova, M.; Lotter, M.; Bronkhorst, F.; Giglio, L. 2024. Assessment of the Effectiveness of Coarse Resolution Fire Products in Monitoring Long-term Changes in Fire Regime in Protected Areas in South Africa. International Journal of Applied EarthObservation and Geoinformation, 132. https://doi.org/10.1016/j.jag.2024.104064 Assessment of the effectiveness of coarse resolution fire products in monitoring long-term changes in fire regime within protected areas in South Africa.pdf4.4 MB
Sandler, Austin and Laixiang Sun. 2024. “The Socio-Environmental Determinants of Childhood Malnutrition: A Spatial and Hierarchical Analysis.” Nutrients (2022 IF: 5.719) 16, article no. 2014. https://doi.org/10.3390/nu16132014. The Socio-Environmental Determinants of Childhood Malnutrition A Spatial and Hierarchical Analysis__Nutrients-16-02014.pdf2.82 MB
Wang, Y, K Feng, L Sun, Y Xie, X-P Song. 2024. Satellite-based soybean yield prediction in Argentina: a comparison between panel regression and deep learning methods. Computers and Electronics in Agriculture (2022 IF = 8.3). 221, article no. 108978.https://doi.org/10.1016/j.compag.2024.108978.
Vadrevu, K. and Eaturu, A., 2024. Trends in Nighttime Fires in South/Southeast Asian Countries. Atmosphere, 15(1), p.85.
Hall, J. V., Argueta, F., Zubkova, M., Chen, Y., Randerson, J. T., & Giglio, L. (2024). GloCAB: global cropland burned area from mid-2002 to 2020. Earth System Science Data, 16(2), 867-885. essd-16-867-2024.pdf6.58 MB
Vadrevu, K., Gutman, G., Tsuneo, M. and Justice, C., 2024. Land use changes, degradation, and impact on ecosystem services in Asia and Southeast Asia. Land Degradation & Development. 2024;35:919–922. https://doi.org/10.1002/ldr.4971
Qadir, A., Skakun, S., Eun, J., Prashnani, M., Shumilo, L. (2023). Sentinel-1 time series data for sunflower (Helianthus annuus) phenology monitoring. Remote Sensing of Environment, 295, art. num. 113689.
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 (2022 IF: 7.9). Vol. 4, article no. 334. https://doi.org/10.1038/s43247-023-00992-2 Satellite forecasting of crop harvest can trigger a cross-hemispheric production response_CommEarth&Env2023.pdf494.66 KB
Xu, S., Wang, D., Liang, S., Liu, Y., & Jia, A. (2023). Assessing the reliability of the MODIS LST product to detect temporal variability. IEEE Geoscience and Remote Sensing Letters.
Duncan, E. C., Skakun, S., Kariryaa, A., & Prishchepov, A. V. (2023). Detection and mapping of artillery craters with very high spatial resolution satellite imagery and deep learning. Science of Remote Sensing, 7, art. num. 100092.
Hall, J.V., Schroeder, W., Rishmawi, K., Wooster, M., Schmidt, C.C., Huang, C., Csiszar, I. and Giglio, L., 2023. Geostationary active fire products validation: GOES-17 ABI, GOES-16 ABI, and Himawari AHI. International Journal of Remote Sensing, 44(10), pp.3174-3193. Geostationary active fire products validation GOES 17 ABI GOES 16 ABI and Himawari AHI.pdf8.17 MB
Xu, S., Wang, D., Liang, S., Liu, Y., & Jia, A. (2023). Assessment of gridded datasets of various near surface temperature variables over Heihe River Basin: Uncertainties, spatial heterogeneity and clear-sky bias. International Journal of Applied Earth Observation and Geoinformation, 120, 103347.
Vadrevu, K.P., Ohara, T. and Justice, C. eds., 2023. Vegetation Fires and Pollution in Asia. Book Publication. Springer Nature.
Xin, Yu, Laixiang Sun*, Matthew Hansen. 2023. Land-cover and land-use change trajectory hopping facilitates estate-crop expansion into protected forests in Indonesia. Conservation Letters (2022 IF: 8.5). 16 (4), article no. e12957.https://doi.org/10.1111/conl.12957 Land‐cover and land‐use change trajectory hopping facilitates estate‐crop expansion_ConservationLetters2023.pdf1.57 MB
Zhang, P., Stewart, K., & Li, Y. (2023). Estimating traffic speed and speeding using passively collected big mobility data and a distributed computing framework. Transactions in GIS, 00, 1– 21. https://doi.org/10.1111/tgis.13061
Mullen, A. L., Watts, J. D., Rogers, B. M., Carroll, M. L., Elder, C. D., Noomah, J., ... & Kyzivat, E. D. (2023). Using High‐Resolution Satellite Imagery and Deep Learning to Track Dynamic Seasonality in Small Water Bodies.Geophysical Research Letters, 50(7), e2022GL102327.
Dai Y. et al. Coastal phytoplankton blooms expand and intensify in the 21st century. Nature 615, 280–284 (2023). https://doi.org/10.1038/s41586-023-05760-y Dai-etal-nature-2023.pdf11.65 MB
Meng, Z. et al. Post-2020 biodiversity framework challenged by cropland expansion in protected areas. Nat Sustain (2023). https://doi.org/10.1038/s41893-023-01093-w
Meredith L. Gore, Rowan Hilend, Jonathan O. Prell, Emily Griffin, John R. Macdonald, Burcu B. Keskin, Aaron Ferber & Bistra Dilkina (2023) A data directory to facilitate investigations on worldwide wildlife trafficking, Big Earth Data, DOI: 10.1080/209644 A data directory to facilitate investigations on worldwide wildlife trafficking.pdf2.43 MB
Nakalembe, Catherine, and Hannah R. Kerner. "Considerations for AI-EO for agriculture in Sub-Saharan Africa." Environmental Research Letters (2023). Nakalembe_2023_Environ._Res._Lett._18_041002.pdf1.73 MB
Tucker, C., Brandt, M., Hiernaux, P. et al. Sub-continental-scale carbon stocks of individual trees in African drylands. Nature 615, 80–86 (2023). https://doi.org/10.1038/s41586-022-05653-6