Publications | GEOG | Geographical Sciences Department | University of Maryland

Note: Dr. Krishna Prasad Vadrevu's research was previously published as "V.K.Prasad" and "V.Krishna Prasad". Asterisk indicates student researcher.
Kerner, H. R., Sahajpal, R., Pai, D. B., Skakun, S., Puricelli, E., Hosseini, M., ... & Becker-Reshef, I. (2022). Phenological normalization can improve in-season classification of maize and soybean: A case study in the central US Corn Belt.Science of Remote Sensing, 6, art. num. 100059.
Qi, Xinxian, Kuishuang Feng, Laixiang Sun, Dandan Zhao, Xianjin Huang. 2022. Drivers of rising agriculture water scarcity in China. One Earth (2021 IF: 14.944), forthcoming.
Prudente, V.H.R., Skakun, S., Oldoni, L.V., Xaud, H.A., Xaud, M.R., Adami, M., & Sanches, I.D.A. (2022). Multisensor approach to land use and land cover mapping in Brazilian Amazon. ISPRS Journal of Photogrammetry and Remote Sensing, 189, 95–109.
Yao Li, Kathleen Stewart, Kay Thwe Han, Zay Yar Han, Poe P Aung, Zaw W Thein, Thura Htay, Dong Chen, Myaing M Nyunt, Christopher V Plowe, Understanding spatio-temporal human mobility patterns for malaria control using a multi-agent mobility simulation model, Clinical Infectious Diseases, 2022;, ciac568, https://doi.org/10.1093/cid/ciac568
Zubkova, M.; Boschetti, L.; Abatzoglou, J.; Giglio, L. 2022. Fire regions as environmental niches: a new paradigm to define potential fire regimes in Africa and Australia. JGR Biogeosciences. JGR Biogeosciences - 2022 - Zubkova - Fire Regions as Environmental Niches A New Paradigm to Define Potential Fire Regimes.pdf3.97 MB
Franch, B., Cintas, J., Becker-Reshef, I., Sanchez-Torres, M. J., Roger, J., Skakun, S., Sobrino, J. A., Van Tricht, K., Degerickx, J., Gilliams, S., Koetz, B., Szantoi, Z., & Whitcraft, A. (2022).Global crop calendars of maize and wheat in the framework of the WorldCereal project. GIScience & Remote Sensing, 59(1), 885–913.
Funes, J., L. Sun, T. Benson, F. Sedano, G. Baiocchi. 2022. Social Interaction and Geographic Diffusion of Iron Biofortified Beans in Rwanda. Agricultural Economics (2020 IF: 2.585). Published online 14 June 2022. https://doi.org/10.1111/agec.12722. Agricultural Economics-2022-Social interaction and geographic diffusion of iron‐biofortified beans in Rwanda.pdf1.12 MB
Gong, W., Huang, C., Houghton, R.A., Nassikas, A., Zhao, F., Tao, X., Lu, J., & Schleeweis, K. (2022). Carbon fluxes from contemporary forest disturbances in North Carolina evaluated using a grid-based carbon accounting model and fine resolution remote sensing products. Science of Remote Sensing, Vol. 5. DOI: 10.1016/j.srs.2022.100042
Jia, A., Liang, S., & Wang, D. (2022). Generating a 2-km, all-sky, hourly land surface temperature product from Advanced Baseline Imager data. Remote Sensing of Environment. 278. 113105. https://doi.org/10.1016/j.rse.2022.113105
Khan. I.M.P., K. Hubacek, K. L. Brubaker, L. Sun, G. Moglen. 2022. Stormwater management adaptation pathways under climate change and urbanization. Journal of Sustainable Water in the Built Environment (2020 IF: 1.78). 8(4): 04022009. DOI: 10.1061/JSWBAY.0000992 Khan et al-Stormwater Management Adaptation Pathways-2022.pdf2.26 MB
Kumar, I., K. Feng, L. Sun, V. Bandaru. 2022. Adoption of biomass for electricity generation in Thailand: Implications for energy security, employment, environment, and land use change. Renewable Energy (2020 IF: 8.001). Available online 5 June 2022. https://doi.org/10.1016/j.renene.2022.05.162.
Lu, J., Huang, C., Tao, X., Gong, W., & Schleeweis, K. (2022). Annual forest disturbance intensity mapped using Landsat time series and field inventory data for the conterminous United States (1986–2015). Remote Sensing of Environment, 275, 113003.
Skakun, S., Wevers, J., Brockmann, C., Doxani, G., Aleksandrov, M., Batič, M., Frantz, D., Gascon, F., Gómez-Chova, L., Hagolle, O., López-Puigdollers, D., Louis, J., Lubej, M., Mateo-García, G., Osman, J., Peressutti, D., Pflug, B., Puc, J., Richter, Roger, J.-C., Scaramuzza, P., Vermote, E., Vesel, N., Zupanc, A., Žust, L. (2022). Cloud Mask Intercomparison eXercise (CMIX): An evaluation of cloud masking algorithms for Landsat 8 and Sentinel-2. Remote Sensing of Environment, 274, art. num. 112990.
Tian, Z., X. Lyu, H. Zou, H. Yang, L. Sun3, M. S. Pinya, Q. Chao, A. Feng, B. Smith. 2022. Advancing index-based climate risk assessment to facilitate adaptation planning: Application in Shanghai and Shenzhen, China. Advances in Climate Change Research (2020 IF: 4.13). Vol. 13, Issue 3, pp. 432-442. https://doi.org/10.1016/j.accre.2022.02.003. Advancing index-based climate risk assessment to facilitate adaptation planning_AdvanceClimateChangeResearch2022.pdf1.29 MB
Zhang, Y., Skakun, S., Adegbenro, M.O., & Ying, Q. (2022). Leveraging the use of labeled benchmark datasets for urban area change mapping and area estimation: a case study of the Washington DC–Baltimore region. International Journal of Digital Earth.https://doi.org/10.1080/17538947.2022.2094001
Nakalembe, C., Zubkova, M., Hall, J. V., Argueta, F., & Giglio, L. (2022). Impacts of large-scale refugee resettlement on LCLUC: Bidi Bidi refugee settlement, Uganda case study. Environmental Research Letters, 17(6), 064019. Nakalembe_2022_Environ._Res._Lett._17_064019.pdf9.23 MB
Vadrevu, K.P., Le Toan, T., Ray, S.S., and Justice, C. 2022. Remote Sensing of Agriculture and Land Cover/Land Use Changes in South and Southeast Asian Countries. Springer Book. https://doi.org/10.1007/978-3-030-92365-5
Xu, H, Z Tian, L Sun, Q Ye, et al. 2022. Compound flood impact of water level and rainfall during tropical cyclone period in a coastal city: The case of Shanghai. Natural Hazards and Earth System Sciences (2022 IF: 4.345). In press. https://doi.org/10.5194/nhess-2022-26.
Comment on Otón et al. Analysis of Trends in the FireCCI Global Long Term Burned Area Product (1982–2018)
Huang, X., Fu, Y., Wang, J., Dong, J., Zheng, Y., Pan, B., Skakun, S., & Yuan, W. (2022). High-Resolution Mapping of Winter Cereals in Europe by Time Series Landsat and Sentinel Images for 2016–2020. Remote Sensing, 14(9), art. num. 2120.
Zhao, D., K. Feng, L. Sun, G. Baiocchi, H. Liu. 2022. Environmental implications of economic transformation in China’s Pearl River Delta region: Dynamics at four nested geographical scales over 1987-2017.” Science of the Total Environment (2020 IF: 7.963)Vol. 816, article no. 151631. https://doi.org/10.1016/j.scitotenv.2021.151631.
Li, R., Wang, D., Liang, S., Jia, A., & Wang, Z. (2022). Estimating global downward shortwave radiation from VIIRS data using a transfer-learning neural network. Remote Sensing of Environment, 274, 112999.
Dubayah, et al. (2021) GEDI L4A Footprint Level Aboveground Biomass Density, V2. ORNL DAAC, Oak Ridge, TNhttps://doi.org/10.3334/ORNLDAAC/1986
Duncanson et al. (2022). Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission. Remote Sensing of Environment, 270, 112845. 1-s2.0-S0034425721005654-main (1).pdf3.63 MB