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

Skakun, S., Vermote, E. F., Artigas, A. E. S., Rountree, W. H., & Roger, J. C. (2021). An experimental sky-image-derived cloud validation dataset for Sentinel-2 and Landsat 8 satellites over NASA GSFC.International Journal of Applied Earth Observation and Geoinformation, 95, 102253.
Hosseini M., Kerner H., Sahajpal R., Estefania I. P., Lu Y.H., Lawal A., Humber M., Mitkish M., Meyer S., Becker-Reshef I., 2020, Evaluating the Impact of the 2020 Iowa Derecho on Corn and Soybean Fields Using Synthetic Aperture Radar, Remote Sensing, 12,
Thieme, A., Glennie, E., Oddo, P., McCartney, S., Ruid, M., & Anand, A. (2020). Application of Remote Sensing for Ex ante Decision Support and Evaluating Impact. American Journal of Evaluation, 109821402096257. https://doi.org/10.1177/1098214020962579
Vadrevu, K.P. and Ohara, T., 2020. Focus on land use cover changes and environmental impacts in South/Southeast Asia. Environmental Research Letters, 15(10), p.100201.
Vadrevu, K.P., Eaturu, A., Biswas, S., Lasko, K., Sahu, S., Garg, J.K. and Justice, C., 2020. Spatial and temporal variations of air pollution over 41 cities of India during the COVID-19 lockdown period. Scientific reports.10(1)1-15.
Vadrevu, K.P., Garg, J., and Wynne, R. 2020. Summary of the 2019 SARI sustainable forestry in South Asia meeting. 32(5)21-26
Brandt, M., Tucker, C.J., Kariryaa, A. et al. An unexpectedly large count of trees in the West African Sahara and Sahel. Nature (2020). https://doi.org/10.1038/s41586-020-2824-5 An unexpectedly large count of trees in the West African Sahara and Sahel_0.pdf12.54 MB
Nakalembe, C. (2020). Urgent and critical need for Sub-Saharan African countries to invest in Earth observation-based agricultural early warning and monitoring systems. Environmental Research Letters. https://doi.org/10.1088/1748-9326/abc0bb
Nakalembe, C. (2020). Urgent and critical need for Sub-Saharan African countries to invest in Earth observation-based agricultural early warning and monitoring systems. Environmental Research Letters. https://doi.org/10.1088/1748-9326/abc0bb Nakalembe_2020_Environ._Res._Lett._10.1088_1748-9326_abc0bb.pdf807.49 KB
Skakun S., Vermote E. F., Santamaria Artigas A. E., Rountree W. H., Roger J.C., 2020 An experimental sky-image-derived cloud validation dataset for Sentinel-2 and Landsat 8 satellites over NASA GSFC, International Journal of Applied Earth Observations and Geoinformation, 95 (2021) 102253, doi.org/10.1016/j.jag.2020.102253
Skakun S., Vermote E. F., Santamaria Artigas A. E., Rountree W. H., Roger J.C., 2020 An experimental sky-image-derived cloud validation dataset for Sentinel-2 and Landsat 8 satellites over NASA GSFC, International Journal of Applied Earth Observations and Geoinformation, 95 (2021) 102253, doi.org/10.1016/j.jag.2020.102253
Thieme, A., Yadav, S., Oddo, P. C., Fitz, J. M., McCartney, S., King, L., ... & Hively, W. D. (2020). Using NASA Earth observations and Google Earth Engine to map winter cover crop conservation performance in the Chesapeake Bay watershed. Remote Sensing of Environment, 248, 111943. 1-s2.0-S0034425720303138-main.pdf2.55 MB
Rich et al., (2020). arcos and arcospy: R and Python packages for accessing the DEA ARCOS database from 2006 - 2014. Journal of Open Source Software, 5(53), 2450, https://doi.org/10.21105/joss.02450
Vermote, E.F.; Skakun, S.; Becker-Reshef, I.; Saito, K. Remote Sensing of Coconut Trees in Tonga Using Very High Spatial Resolution WorldView-3 Data. Remote Sens. 2020, 12, 3113.
Dong, G., Z. Jiang, Z. Tian, E. Buonomo, L. Sun, D. Fan. 2020. “Projecting Changes in Mean and Extreme Precipitation over Eastern China during 2041-2060.” Earth and Space Science (2018 IF = 2.15), Vol. 7, article no. e2019EA001024.https://doi.org/10.1029/2019EA001024. Projecting Changes in Mean and Extreme Precipitation over Eastern China during 2041-2060_Earth&SpaceScience2020.pdf16.93 MB
Giglio, L., and Roy, D. P., 2020, On the outstanding need for a long-term, multi-decadal, validated and quality assessed record of global burned area: Caution in the use of Advanced Very High Resolution Radiometer data. Science of Remote Sensing, 2, 100007. Giglio2020_SRS.pdf2.7 MB
Jiang, Z., Z. Tian, G. Dong, L. Sun, P. Zhang, E. Buonomo, D. Fan. 2020. “High-Resolution Projections of Mean and Extreme Precipitation over China by Two Regional Climate Models.” Journal of Meteorological Research (IF = 2.302; 5-yr IF = 2.225), 34 (5), 1–22. http://jmr.cmsjournal.net/article/doi/10.1007/s13351-020-9208-5. High-ResolutionProjectionsOfMeanAndExtremePrecipitationOverChina_J Meteo Res2020.pdf48.25 MB
Breau, S., Burkhart., N., Shin, M., Marchand, Y., Sauer, J. (2020). Is it time to start worrying more about growing regional inequalities in Canada? The Canadian Geographer. https://doi.org/10.1111/cag.12634
Forkuor, G., Zoungrana, J.B.B., Dimobe, K., Ouattara, B., Vadrevu, K.P. and Tondoh, J.E., 2020. Above-ground biomass mapping in West African dryland forest using Sentinel-1 and 2 datasets-A case study. Remote Sensing of Environment, 236, p.111496.
He, J., & Eastman, J. R. (2020). A Sequential Autoencoder for Teleconnection Analysis. Remote Sensing, 12(5), 851. doi:10.3390/rs12050851 remotesensing-12-00851_0.pdf8.01 MB
Li, Y., Zhang, N., Li, R.K., Liu, C.Y., Shen, J. and Jing, Y.C., 2020. Soil mapping based on assessment of environmental similarity and selection of calculating samples. CATENA, 188, p.104379.
Buckley, E. M., Farrell, S. L., Duncan, K., Connor, L. N., Kuhn, J. M., & Dominguez, R. T. ( 2020). Classification of Sea Ice Summer Melt Features in High‐resolution IceBridge Imagery. JGR, 125, e2019JC015738. https://doi.org/10.1029/2019JC015738 2019JC015738.pdf2.3 MB
Li, Y., Shetty, A.C., Lon, C., Spring, M., Saunders, D.L., Fukuda, M.M., Hien, T.T., Pukrittayakamee, S., Fairhurst, R.M., Dondorp, A.M. and Plowe, C.V., 2020. Detecting geospatial patterns of Plasmodium falciparum parasite migration in Cambodia using optimized estimated effective migration surfaces. International Journal of Health Geographics, 19(1), pp.1-11.
Pickens, A.H., Hansen, M.C., Hancher, M., Stehman, S.V., Tyukavina, A., Potapov, P., Marroquin, B., Sherani, Z., 2020. Mapping and sampling to characterize global inland water dynamics from 1999 to 2018 with full Landsat time-series. Remote Sensing of Environment 243, 111792. https://doi.org/10.1016/j.rse.2020.111792 globalWaterPickens.pdf3.84 MB
Liang, M.; Pause, M.; Prechtel, N.; Schramm, M. Regionalization of Coarse Scale Soil Moisture Products Using Fine-Scale Vegetation Indices—Prospects and Case Study. Remote Sens. 2020, 12, 551. remotesensing-12-00551.pdf1.99 MB