Publications related to Land Cover - Land Use Change | Geographical Sciences Department

Skakun, S.; Vermote, E.; Franch, B.; Roger, J.-C.; Kussul, N.; Ju, J.; Masek, J. (2019) Winter Wheat Yield Assessment from Landsat 8 and Sentinel-2 Data: Incorporating Surface Reflectance, Through Phenological Fitting, into Regression Yield Models.Remote Sensing, 11(15), 1768
Note: Dr.Vadrevu's research was previously published as "V.K.Prasad" and "V.Krishna Prasad". Asterisk indicates student researcher.
Vadrevu,KP,Lasko,K, Giglio,L, Schroeder,W, Biswas,S., and Justice,C. 2019. Trends in Vegetation fires in South and Southeast Asian Countries.NatureScientificReports 9:7422
Franch, B., Vermote, E. F., Skakun, S., Roger, J. C., Becker-Reshef, I., Murphy, E., & Justice, C. (2019). Remote sensing based yield monitoring: Application to winter wheat in United States and Ukraine. International Journal of Applied Earth Observation and Geoinformation, 76, 112-127.
Notaro, M., Emmett, K., and O’Leary, D. (2019). Spatio-Temporal Variability in Remotely Sensed Vegetation Greenness Across Yellowstone National Park. Remote Sensing 11, 798. https://doi:10.3390/rs11070798
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Munoz Castillo, R., K. Feng, L. Sun, J. Guilhoto, S. Pfister, F. Miralles-Wilhelm, K. Hubacek. 2019. “The land-water nexus of biofuel production in Brazil: analysis of synergies and trade-offs using a multiregional input-output model.” Journal of Cleaner Production (2017 IF: 5.651, 5-yr IF: 6.352), vol. 214, pp. 52-61.
Zhao, D., K. Hubacek, K. Feng, L. Sun, J. Liu. 2019. “Explaining the virtual water trade: A spatial-temporal analysis of the comparative advantage of land, labor and water in China.” Water Research (2017 IF: 7.051; 5 yr IF: 7.621), Vol. 153, pp. 304-314. Explaining virtual water trade A spatial-temporal analysis of the comparative advantage of land, labor and water in China_WaterResearch2019.pdf2.65 MB
Zhong, H., L. Sun, G. Fischer, Z. Tian, Z. Liang. 2019. “Optimizing regional cropping systems with a dynamic adaptation strategy for water sustainable agriculture in the Hebei Plain.” Agricultural Systems (2017 IF: 3.004, 5-yr IF: 3.756), 173, 94-106.https://doi.org/10.1016/j.agsy.2019.02.005
Zalles, V., Hansen, M. C., Potapov, P. V., Stehman, S. V., Tyukavina, A., Pickens, A., ... & John, N. (2019). Near doubling of Brazil’s intensive row crop area since 2000. Proceedings of the National Academy of Sciences, 116(2), 428-435.https://doi.org/10.1073/pnas.1810301115
Claverie, M., Ju, J., Masek, J. G., Dungan, J. L., Vermote, E. F., Roger, J.-C., Skakun, S. V., & Justice, C. (2018). The Harmonized Landsat and Sentinel-2 surface reflectance data set. Remote Sensing of Environment, 219, 145-161.
Cooper, M., Zvoleff, A, Gonzalez-Roglich, M., Tusiime, F., Musumba, M., Noon, M., Alele, P., Nyiratuza, M., (2018) Geographic Factors Predict Wild Food and Nonfood NTFP Collection by Households Across Four African Countries. Forest Policy and Economics, 9 2018 Cooper - Geographic factors predict wild food and nonfood NTFP collection by households across four African countries.pdf775.68 KB
Liao, W., Liu, X., Li, D., Luo., M., Wang., D., Wang, S., Lin, L., Li, X., Feng, K., Hubacek, K., Yang, X., (2018), Stronger Contributions of Urbanization to Heat Wave Trends in Wet Climates, Geophysical Research Letters, 45.
Tian, Z., Y. Ji, L. Sun, X. Xu, D. Fan, H. Zhong, Z. Liang, G. Ficsher. 2018. Changes in production potentials of rapeseed in the Yangtze River Basin of China under climate change: A multi-model ensemble approach. Journal of Geographical Sciences.(2017 IF: 1.623), Vol. 28, No. 11, pp. 1700-1714.
Donal O’Leary III,Dorothy Hall,Michael Medler, et al. Quantifying the early snowmelt event of 2015 in the Cascade Mountains, USA by developing and validating MODIS-based snowmelt timing maps[J]. Front. Earth Sci., 03 August 2018. [Epub ahead of print] doi: 10.1007/s11707-018-0719-7.
Li, Y., Chen, J., & Rao, Y. (2018). A practical sampling method for assessing accuracy of detected land cover/land use change: Theoretical analysis and simulation experiments. ISPRS Journal of Photogrammetry and Remote Sensing, 144, 379-389.
Khan, A., Hansen, M.C., Potapov, P.V., Adusei, B., Pickens, A., Krylov, A., Stehman, S.V. Evaluating Landsat and RapidEye Data for Winter Wheat Mapping and Area Estimation in Punjab, Pakistan, Remote Sensing (2018)https://doi.org/10.3390/rs10040489
Nakalembe, C. (2018) Characterizing agricultural drought in the Karamoja subregion of Uganda with meteorological and satellite-based indices. Natural Hazards 91: 837. https://doi.org/10.1007/s11069-017-3106-x
Alabar,I., Jaya,I.,Saharjo,B.H.,Kuncahyo,B., and K.P.Vadrevu. 2018. Spatio-temporal Analysis of Land and Forest Fires in Indonesia using MODIS Active Fire Dataset. Chapter-6. In Land-Atmospheric Research Applications in South and Southeast Asia. Spr
Chen, D., & Loboda, T.V. (2018). Surface forcing of non-stand-replacing fires in Siberian larch forests. Environmental Research Letters, 13, 045008.
Chen, D., Loboda, T.V., He, T., Zhang, Y., & Liang, S. (2018). Strong cooling induced by stand-replacing fires through albedo in Siberian larch forests. Scientific Reports, 8, 4821. strong_cooling_induced_by_stand-replacing_fires_through_albedo_in_siberian_larch_forests.pdf1.86 MB
Krishna Prasad Vadrevu, 2018. South/Southeast Asia Research Initiative (SARI): A Response to Regional Needs in Land Cover/Land Use Change Science and Priorities. Chapter-1. In Land-Atmospheric Research Applications in South and Southeast Asia. Springer.
Krishna Prasad Vadrevu, Toshimasa Ohara and Chris Justice (Eds). 2018. Land Atmospheric Research Applications in Asia. 30-Chapters. Springer Verlag. (ISBN: 978-3-319-67473-5)
Krishna Vadrevu and Kristofer Lasko. 2018. Intercomparison of MODIS AQUA and VIIRS I-Band Fires and Emissions in an Agricultural Landscape—Implications for Air Pollution Research. Remote Sens. 10, 978; doi:10.3390/rs10070978
Kussul, N., Lavreniuk, M., Shelestov, A., & Skakun, S. (2018). Crop inventory at regional scale in Ukraine: developing in season and end of season crop maps with multi-temporal optical and SAR satellite imagery. European Journal of Remote Sensing, 51(1), 627–636. kussul_et_al_2018_eujrs_crop_inventory_ukraine.pdf428.5 KB