Publications | GEOG | Geographical Sciences Department | University of Maryland

Luan, Y., G. Fischer, Y. Wada, L. Sun, and P. Shi. 2018. “Quantifying the impact of diet quality on hunger and undernutrition.” Journal of Cleaner Production (2018 IF: 6.395, 5-yr IF: 7.051), Vol. 205, pp. 432-466. https://doi.org/10.1016/j.jclepro.2018.09.064.
Qin, Y., Höglund-Isaksson, L., Byers, E., Feng, K., Wagner, F., Peng, W., Mauzerall, D.L., (2018), Air, Carbon, and Water Synergies and Trade-offs in China’s Natural Gas Industry, Nature Sustainability.
A Multi-stage Image Segmentation Framework for Human Detection in Mid Wave Infra-Red (MWIR) Imagery. In: Chmielewski L.J., Kozera R., Shin BS., Wojciechowski K. (eds) Computer Vision and Graphics. ICCVG 2014. Lecture Notes in Computer Science, vol 8671.
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.
Giglio, L.; Boschetti, L.; Roy, D.P.; Humber, M.L.; Justice, C.O., “The Collection 6 MODIS burned area mapping algorithm and product,” Remote Sensing of Environment, vol. 217, Aug. 2018
Investigation on noise sensitivity of Neural Networks in hyper spectral imagery classification, ERCICA-2013 , Elsevier conference journal
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.
Polarimetric Decomposition and Statistical Analysis of Chandrayan-I Mini-SAR Data for Study of Lunar Craters, 2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI), New Delhi, 2014, pp. 2655-2658. doi: 10.1109/ICACCI.2014.6968410
Understanding crop growing pattern in Bardhaman district of West Bengal using multi-date RISAT 1 MRS data , ISPRS Technical Commission VIII Symposium -2014
Marselis, S.M.; Tang, H.; Armston, J.D.; Calders, K.; Labriere, N.; Dubayah, R. (2018) Distinguishing vegetation types with airborne waveform lidar data in a tropical forest-savanna mosaic: A case study in Lopé National Park, Gabon. Rem. Sen. Env. 216https://doi.org/10.1016/j.rse.2018.07.023
Rappaport, D.I., Morton, D.C., Longo, M., Keller, M., Dubayah, R., dos-Santos, M.N., 2018. Quantifying long-term changes in carbon stocks and forest structure from Amazon forest degradation. Environ. Res. Lett. 13, 065013. https://doi.org/10.1088/1748-932
Song, Z., Liang, S., Wang, D., Zhou, Y., & Jia, A. (2018). Long-term record of top-of-atmosphere albedo over land generated from AVHRR data. Remote Sensing of Environment, 211, 71-88.
Abiotic Stress Detection in in-field Maize Crop Using UAV Remote SensingSeminar on Advances in Remote Sensing & GIS application, Conference Paper
Discrimination of minor crops (maize and cauliflower) using Sentinel-1 SAR data Seminar on Advances in Remote Sensing & GIS application, Conference Paper
Huang, R., Hubacek, K., Feng, K., Li, X., Zhang, C., (2018), Re-Examining Embodied SO2 and CO2 emissions in China, Sustainability 10, 1505
Qian, Y., Song, K., Hu, T., & Ying, T. (2018). Environmental status of livestock and poultry sectors in China under current transformation stage. Science of The Total Environment, 622, 702-709.
Baraldi, A.; Humber, M.L.; Tiede, D.; Lang, S., “GEO-CEOS stage 4 validation of the Satellite Image Automatic Mapper lightweight computer program for ESA Earth observation Level 2 product generation – Part 1: Theory,” Cogent Geoscience, Apr. 2018
Baraldi, A.; Humber, M.L.; Tiede, D.; Lang, S., “GEO-CEOS stage 4 validation of the Satellite Image Automatic Mapper lightweight computer program for ESA Earth observation Level 2 product generation – Part 2: Validation,” Cogent Geoscience, Apr. 2018
Silva, Julie A., Tatiana Loboda, and Michael Strong. 2018. Examining Aspiration’s Imprint on the Landscape: Lessons from Mozambique’s Limpopo National Park. Global Environmental Change 51: 43-53. DOI: 10.1016/j.gloenvcha.2018.04.013
Bruening, J. M., Bunn, A. G., & Salzer, M. W. (2018). A climate‐driven tree line position model in the White Mountains of California over the past six millennia. Journal of Biogeography, 45(5), 1067-1076.
Bruening, J. M., Bunn, A. G., & Salzer, M. W. (2018). A climate‐driven tree line position model in the White Mountains of California over the past six millennia. Journal of Biogeography, 45(5), 1067-1076. Bruening_et_al-2018-Journal_of_Biogeography.pdf1.97 MB
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
Wayland, J. (2018). Constraints on foreign aid effectiveness in the water, sanitation, and hygiene (WaSH) sector. Journal of Water, Sanitation and Hygiene for Development, 8(1), 44-52.
Zhang, W., Liu, Y., Feng, K., Hubacek, K., Wang, J., Liu, M., Jiang, L., Jiang, H., Zhou, Y., Bi, J., (2018), Revealing Environmental Inequality Hidden in China’s Inter-regional Trade, Environmental Science & Technology 52 (13), pp 7171–7181.
Flood Damage Assessment of Kharif Rice Crop Using Geospatial Technology International Geographical Union Commission , Guwahati , 08 – 10 February, 2018