Publications | GEOG | Geographical Sciences Department | University of Maryland

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.
Merz, J., V. Bandaru, Q. Hart, N. C. Parker, and B.M. Jenkins. 2018. Hybrid Poplar based Biorefinery Siting Web Application (HP-BiSWA): An online decision support application for siting hybrid poplar based biorefineries. Computers and Electronics in Agriculture. 155: 76-83
Berndtson, R. and L. Makanyama. 2018. "Online Learning for Geography Undergraduates: Student Perceptions and Motivations." The Geography Teacher 15:4, 145-155,
Bunn, A. G., Salzer, M. W., Anchukaitis, K. J., Bruening, J. M., & Hughes, M. K. (2018). Spatiotemporal variability in the climate growth response of high elevation bristlecone pine in the White Mountains of California. Geophysical Research Letters. https://doi.org/10.1029/2018GL080981 Bunn et al 2018 GRL.pdf1.52 MB
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
Gao, C., Zhang, S., Song, K., Na, H., Tian, F., Zhang, M., & Gao, W. (2018). Conjoint analysis of nitrogen, phosphorus and sulfur metabolism: A case study of Liaoning Province, China. Ecological Modelling, 390, 70-78.
Jiang, B., Liang, S., Jia, A., Xu, J., Zhang, X., Xiao, Z., ... & Yao, Y. (2018). Validation of the Surface Daytime Net Radiation Product From Version 4.0 GLASS Product Suite. IEEE Geoscience and Remote Sensing Letters. DOI: 10.1109/LGRS.2018.2877625Print ISSN: 1545-598X
Sauer, J., Berrang-Ford, L., Patterson, K., Donnelly, B., Lwasa, S., Namanya, D., . . . Harper, S. (2018). An Analysis of the Nutrition Status of Neighboring Indigenous and non-Indigenous Populations in Kanungu District, Southwestern UgandaClose proximity, distant health realities. Social Science & Medicine, 217, 55-64. doi:10.1016/j.socscimed.2018.09.027
Becker-Reshef I, Franch B, Barker B, Murphy E, Santamaria-Artigas A, Humber M, Skakun S, Vermote E. Prior Season Crop Type Masks for Winter Wheat Yield Forecasting: A US Case Study. Remote Sensing. 2018; 10(10):1659. Becker-Reshef et al. - 2018 - Prior Season Crop Type Masks for Winter Wheat Yield Forecasting A US Case Study.pdf4.23 MB
Franch B, Vermote E, Skakun S, Roger J-C, Santamaria-Artigas A, Villaescusa-Nadal JL and Masek J (2018) Toward Landsat and Sentinel-2 BRDF Normalization and Albedo Estimation: A Case Study in the Peruvian Amazon Forest. Front. Earth Sci. 6:185.doi: 10.3389/feart.2018.00185 feart-06-00185.pdf677.41 KB
Jimenez J.C., Barichivich J., Mattar C., Takahashi K., Santamaría-Artigas A., Sobrino J.A., Malhi Y. 2018. Spatio-temporal patterns of thermal anomalies and drought over tropical forests driven by recent extreme climatic anomalies. Phil. Trans. R. Soc. B373: 20170300. http://dx.doi.org/10.1098/rstb.2017.0300
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.(2018 IF: 2.347), Vol. 28, No. 11, pp. 1700-1714.
Ziqi Li, A. Stewart Fotheringham, Wenwen Li & Taylor Oshan (2019) “Fast Geographically Weighted Regression (FastGWR): a scalable algorithm to investigate spatial process heterogeneity in millions of observations”,International Journal of Geographical Information Science 33:1, 155-175.
Li, Xiaoying, Yin-Fang Zhang, and Laixiang Sun. 2018. “Industry agglomeration, sub-national institutions and the profitability of foreign subsidiaries.” Management International Review (2018 IF: 2.689). 58(6), 969–993.https://doi.org/10.1007/s11575-018-0361-3.
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