Published Research

The following references cite studies that used MODIS data from NSIDC. Please contact User Services if you have a reference you would like to share on this page.

2016

Bruggeman, Jason E., et al. 2016. Multi-season occupancy models identify biotic and abiotic factors influencing a recovering Arctic Peregrine Falcon Falco peregrinus tundrius population. IBIS 158(1): 61-74. doi: http://dx.doi.org/10.1111/ibi.12313.

Morriss, B. F., et al. 2016. Persistence-based temporal filtering for MODIS snow products. Remote Sensing of Environment 175: 130-137. doi: http://dx.doi.org/10.1016/j.rse.2015.12.030.

Muto, Atsuhiro, et al. 2016. Subglacial bathymetry and sediment distribution beneath Pine Island Glacier ice shelf modeled using aerogravity and in situ geophysical data: New results. Earth and Planetary Letters 433: 63-75. doi: http://dx.doi.org/10.1016/j.epsl.2015.10.037.

Naeem, Usman Ali, et al. 2016. Investigation of temporal change in glacial extent of Chitral watershed using Landsat data. Environmental Monitoring and Assessment 188. Art. #43. doi: http://dx.doi.org/10.1007/s10661-015-5026-0.

Willmes, Sacha, and Gunther Heinemann. 2016. Sea-Ice Wintertime Lead Frequencies and Regional Characteristics in the Arctic, 2003–2015. Remote Sensing 8(1). Art. #4. doi: http://dx.doi.org/10.3390/rs8010004.

2015

André, C. , et al. 2015. Land surface temperature retrieval over circumpolar Arctic using SSM/I–SSMIS and MODIS data. Remote Sensing of Environment 162: 1-10. doi: http://dx.doi.org/10.1016/j.rse.2015.01.028.

Azmat, Muhammed. 2015. Water Resources Availability and Hydropower Production under Current and Future Climate Scenarios: The Case of Jhelum River Basin, Pakistan. : viii, 223. Ph. D. Politecnico di Torino. doi: http://dx.doi.org/10.6092/polito/porto/2594956.

Bao, Wei-jia, et al. 2015. Glacier changes during the past 40 years in the west Kunlun Shan. Journal of Mountain Science 12(2): 344-357. doi: http://dx.doi.org/10.1007/s11629-014-3220-0.

Berezowski, Tomasz, Jarosław Chormańskia, and Okke Batelaan. 2015. Skill of remote sensing snow products for distributed runoff prediction. Journal of Hydrology 524: 718-732. doi: http://dx.doi.org/10.1016/j.jhydrol.2015.03.025.

Bi, Yunbo, et al. 2015. Snow Cover Variations and Controlling Factors at Upper Heihe River Basin, Northwestern China. Remote Sensing 7(6): 6741-6762. doi: http://dx.doi.org/10.3390/rs70606741.

Bookhagen, Bodo. 2015. Glaciers and monsoon systems. Monsoon and Climate Change. New York, NY: Springer International Publishing, 225-249. doi: http://dx.doi.org/10.1007/978-3-319-21650-8_11.

Boori, Mukesh, and Ralph Ferraro. 2015. Global Land Cover Classification Based on Microwave Polarization and Gradient Ratio (MPGR). Geoinformatics for Intelligent Transportation. New York, NY: Springer International Publishing, 17-37. doi: http://dx.doi.org/10.1007/978-3-319-11463-7_2.

Brun, F., et al. 2015. Seasonal changes in surface albedo of Himalayan glaciers from MODIS data and links with the annual mass balance. The Cryosphere 9(1): 341-355. doi: http://dx.doi.org/10.5194/tc-9-341-2015.

Burakowski, Elizabeth A., et al. 2015. Spatial scaling of reflectance and surface albedo over a mixed-use, temperate forest landscape during snow-covered periods. Remote Sensing of Environment 158: 465-477. doi: http://dx.doi.org/10.1016/j.rse.2014.11.023.

Crawford, Christopher J. 2015. MODIS Terra Collection 6 fractional snow cover validation in mountainous terrain during spring snowmelt using Landsat TM and ETM. Hydrological Processes 29(1): 128-138. doi: http://dx.doi.org/10.1002/hyp.10134.

Delbart, Nicolas, et al. 2015. Remote sensing of Andean mountain snow cover to forecast water discharge of Cuyo rivers. Journal of Alpine Research 103(2). doi: http://dx.doi.org/10.4000/rga.2903.

Deng, Jie, et al. 2015. Toward Improved Daily Cloud-Free Fractional Snow Cover Mapping with Multi-Source Remote Sensing Data in China. Remote Sensing 7(6): 6986-7006. doi: http://dx.doi.org/10.3390/rs70606986.

Dietz, Andreas J., Claudia Kuenzer, and Stefan Dech. 2015. Analysis of snow cover time series -- Opportunities and Techniques. Remote Sensing Time Series: Revealing Land Surface Dynamics. New York, NY: Springer, 75-98..

Finger, David, et al. 2015. The value of multiple data set calibration versus model complexity for improving the performance of hydrological models in mountain catchments. Water Resources Research 51(4): 1939-1958. doi: http://dx.doi.org/10.1002/2014WR015712.

Gafurov, A., et al. 2015. Snow-cover reconstruction methodology for mountainous regions based on historic in situ observations and recent remote sensing data. The Cryosphere 9(2): 451-463. doi: http://dx.doi.org/10.5194/tc-9-451-2015.

Gascoin, S., et al. 2015. A snow cover climatology for the Pyrenees from MODIS snow products. Hydrology and Earth System Sciences 19: 2337-2351. doi: http://dx.doi.org/10.5194/hess-19-2337-2015.

Haizhu, Pan, Wang Jian, and Li Hongyi. 2015. Accuracy validation of the MODIS snow albedo products and estimate of the snow albedo under cloud over the Qilian Mountains. Journal of Glaciology and Geocryology 37(1): 49-57. doi: http://dx.doi.org/10.7522/j.issn.1000-0240.2015.0005.

Isenstein, Elizabeth M., et al. 2015. Calibration of a Distributed Hydrologic Model Using Streamflow and Remote Sensing Snow Data. World Environmental and Water Resources Congress 2015: 973 Floods, Droughts, and Ecosystems © ASCE 2015 . Reston, VA: ASCE, 973-982..

Ismail, Muhammad Fraz, et al. 2015. Degree day factor models for forecasting the snowmelt runoff for Naran Watershed. Science International 27(3): 1951-1960.

Jin, Xin, et al. 2015. Spatial and temporal variations of snow cover in the Loess Plateau, China. International Journal of Climatology 35(8): 1721-1731. doi: http://dx.doi.org/10.1002/joc.4086.

Joshi, Rajesh, et al. 2015. Variations in the Seasonal Snow Cover Area (SCA) for Upper Bhagirathi Basin, India. Dynamics of Climate Change and Water Resources of Northwestern Himalaya. New York, NY: Springer International Publishing, 9-21. doi: http://dx.doi.org/10.1007/978-3-319-13743-8_2.

Kang, H.-J., et al. 2015. Uncertainties of satellite-derived surface skin temperatures in the polar oceans: MODIS, AIRS/AMSU, and AIRS only. Atmospheric Measurement Techniques 8: 4025-4041. doi: http://dx.doi.org/10.5194/amt-8-4025-2015.

Karlsson, K. -G., E. Johansson, and A. Devasthale. 2015. Advancing the uncertainty characterisation of cloud masking in passive satellite imagery: Probabilistic formulations for NOAA AVHRR data. Remote Sensing of Environment 158: 126-139. doi: http://dx.doi.org/10.1016/j.rse.2014.10.028.

Khan, Asif, Bibi S. Naz, and Laura C. Bowling. 2015. Separating snow, clean and debris covered ice in the Upper Indus Basin, Hindukush-Karakoram-Himalayas, using Landsat images between 1998 and 2002. Journal of Hydrology 521(1): 46-64. doi: http://dx.doi.org/10.1016/j.jhydrol.2014.11.048.

Kim, Miae, et al. 2015. Landfast sea ice monitoring using multisensor fusion in the Antarctic. GIScience & Remote Sensing 52(2): 239-256. doi: http://dx.doi.org/10.1080/15481603.2015.1026050.

Klein, Igor, et al. 2015. Results of the Global WaterPack: a novel product to assess inland water body dynamics on a daily basis. Remote Sensing Letters 6(1): 78-87. doi: http://dx.doi.org/10.1080/2150704X.2014.1002945.

Klein, Igor, et al. 2015. Global WaterPack: Intra-annual Assessment of Spatio-Temporal Variability of Inland Water Bodies. Remote Sensing and Digital Image Processing . Zurich: Springer International Publishing Switzerland, 99-117. doi: http://dx.doi.org/10.1007/978-3-319-15967-6_5.

Kostadinov, Tihomir Sabinov, et al. 2015. Snow cover variability in a forest ecotone of the Oregon Cascades via MODIS Terra products. Remote Sensing of Environment 164: 155-169. doi: http://dx.doi.org/10.1016/j.rse.2015.04.002.

Kostyuchenko, Yuriy V. 2015. Infrastructure Vulnerability Assessment Toward Extreme Meteorological Events Using Satellite Data. Numerical Methods for Reliability and Safety Assessment: Multiscale and Multiphysics Systems. Zurich: Springer International Publishing Switzerland, 425-438. doi: http://dx.doi.org/10.1007/978-3-319-07167-1__15.

Kuenzer, Claudia, et al. 2015. Remote Sensing of River Delta Inundation: Exploiting the Potential of Coarse Spatial Resolution, Temporally-Dense MODIS Time Series. Remote Sensing 7(7): 8516-8542. doi: http://dx.doi.org/10.3390/rs70708516.

Kumar, Sujay V., et al. 2015. Quantifying the Added Value of Snow Cover Area Observations in Passive Microwave Snow Depth Data Assimilation. Journal of Hydrometeorology 16(4): 1736-1741. doi: http://dx.doi.org/10.1175/JHM-D-15-0021.1.

Lavoie, C., et al. 2015. Configuration of the Northern Antarctic Peninsula Ice Sheet at LGM based on a new synthesis of seabed imagery. The Cryosphere 9: 613-629. doi: http://dx.doi.org/10.5194/tc-9-613-2015.

Li, Hong Yi, et al. 2015. Downscaling Snow Cover Fraction Data in Mountainous Regions Based on Simulated Inhomogeneous Snow Ablation. Remote Sensing 7(7): 8995-9019. doi: http://dx.doi.org/10.3390/rs70708995.

Liang, Tian Gang, et al. 2015. An application of MODIS data to snow cover monitoring in a pastoral area: A case study in Northern Xinjiang, China. Remote Sensing of Environment 112(4): 1514-1526. doi: http://dx.doi.org/10.1016/j.rse.2007.06.001.

Lindsay, Chuck, et al. 2015. Deriving Snow Cover Metrics for Alaska from MODIS. Remote Sensing 7(10): 12961-12985. doi: http://dx.doi.org/10.3390/rs71012961.

Liu, Xun Chang-Qing Ke, and Zhu-De Shao. 2015. Snow cover variations in Gansu, China, from 2002 to 2013. Theoretical and Applied Climatology 122(3): 487-496. doi: http://dx.doi.org/10.1007/s00704-014-1306-9.

Liu, Yuqiong, et al. 2015. Blending satellite-based snow depth products with in situ observations for streamflow predictions in the Upper Colorado River Basin. Water Resources Research 51(2): 1182-1202. doi: http://dx.doi.org/10.1002/2014WR016606.

Lomidze, N., et al. 2015. Application of Remote sensing and GIS technologies for study of seasonal snow cover in Georgia. Journal of the Georgian Geophysical Society 17. Art. #1647.

Macander, Matthew J., et al. 2015. Landsat-based snow persistence map for northwest Alaska. Remote Sensing of Environment 163: 23-31. doi: http://dx.doi.org/10.1016/j.rse.2015.02.028.

Marchane, A., et al. 2015. Assessment of daily MODIS snow cover products to monitor snow cover dynamics over the Moroccan Atlas mountain range. Remote Sensing of Environment 160: 72-86. doi: http://dx.doi.org/10.1016/j.rse.2015.01.002.

Metsamaki, Sari, et al. 2015. Introduction to GlobSnow Snow Extent products with considerations for accuracy assessment. Remote Sensing of Environment 156: 96-108. doi: http://dx.doi.org/10.1016/j.rse.2014.09.018.

Ming, Jing, et al. 2015. Widespread Albedo Decreasing and Induced Melting of Himalayan Snow and Ice in the Early 21st Century. PLOS One 10(6). Art. #e0126235. doi: http://dx.doi.org/10.1371/journal.pone.0126235.

Mir, Riyaz Ahmad, et al. 2015. Accuracy assessment and trend analysis of MODIS-derived data on snow-covered areas in the Sutlej basin, Western Himalayas. International Journal of Remote Sensing 36(15): 3837-3858. doi: http://dx.doi.org/10.1080/01431161.2015.1070320.

Mir, Riyaz Ahmad, et al. 2015. Decline in snowfall in response to temperature in Satluj basin, western Himalaya. Journal of Earth System Science 124(2): 365-382. doi: http://dx.doi.org/10.1007/s12040-015-0539-z.

Mir, Riyaz Ahmad, Sanjay K. Jain, and Arun K. Saraf. 2015. Analysis of current trends in climatic parameters and its effect on discharge of Satluj River basin, western Himalaya. Natural Hazards 79(1): 587-619. doi: http://dx.doi.org/10.1007/s11069-015-1864-x.

Moore, Cara, et al. 2015. A GIS-based method for defining snow zones: application to the western United States. Geocarta International 30(1): 62-81. doi: http://dx.doi.org/10.1080/10106049.2014.885089.

Moustafa, S. E., et al. 2015. Multi-modal albedo distributions in the ablation area of the southwestern Greenland Ice Sheet. The Cryosphere 9: 905-923. doi: http://dx.doi.org/10.5194/tc-9-905-2015.

Naud, C. M., et al. 2015. A Satellite View of the Radiative Impact of Clouds on Surface Downward Fluxes in the Tibetan Plateau. Journal of Applied Meteorology and Climatology 54(2): 479-493. doi: http://dx.doi.org/10.1175/JAMC-D-14-0183.1.

Niu, X., and Rachel T. Pinker. 2015. An improved methodology for deriving high-resolution surface shortwave radiative fluxes from MODIS in the Arctic region. Journal of Geophysical Research - Atmospheres 120(6): 2382-2393. doi: http://dx.doi.org/10.1002/2014JD022151.

Ossi, Federico, et al. 2015. Snow sinking depth and forest canopy drive winter resource selection more than supplemental feeding in an alpine population of roe deer. European Journal of Wildlife Research 61(1): 111-124. doi: http://dx.doi.org/10.1007/s10344-014-0879-z.

Pan, Paipai, et al. 2015. Snow cover detection based on two-dimensional scatter plots from MODIS imagery data. Journal of Applied Remote Sensing 9. Art. #096083. doi: http://dx.doi.org/10.1117/1.JRS.9.096083.

Paul, Stephan, et al. 2015. Spatial Feature Reconstruction of Cloud-Covered Areas in Daily MODIS Composites. Remote Sensing 7(5): 5042-5056. doi: http://dx.doi.org/10.3390/rs70505042.

Paul, Stephan, S. Willmes, and G. Heinemann. 2015. Long-term coastal-polynya dynamics in the southern Weddell Sea from MODIS thermal-infrared imagery. The Cryosphere 9: 2027-2041. doi: http://dx.doi.org/10.5194/tc-9-2027-2015.

Perez-Luque, A. J., et al. 2015. An ontological system based on MODIS images to assess ecosystem functioning of Natura 2000 habitats: A case study for Quercus pyrenaica forests. International Journal of Applied Earth Observation and Geoinformation 37(SI): 142-151. doi: http://dx.doi.org/10.1016/j.jag.2014.09.003.

Poggio, Laura, and Alessandro Gimona. 2015. Sequence-based mapping approach to spatio-temporal snow patterns from MODIS time-series applied to Scotland. International Journal of Applied Earth Observation and Geoinformation 34: 122-135. doi: http://dx.doi.org/10.1016/j.jag.2014.08.005.

Pohl, Eric, Richard Gloaguen, and Ralf Seiler. 2015. Remote Sensing-Based Assessment of the Variability of Winter and Summer Precipitation in the Pamirs and Their Effects on Hydrology and Hazards Using Harmonic Time Series Analysis. Remote Sensing 7(8): 9727-9752. doi: http://dx.doi.org/10.3390/rs70809727.

Preußer, Andreas, et al. 2015. Multi-Decadal Variability of Polynya Characteristics and Ice Production in the North Water Polynya by Means of Passive Microwave and Thermal Infrared Satellite Imagery. Remote Sensing 7(12): 15844-15867. doi: http://dx.doi.org/10.3390/rs71215807.

Ragettli, S., et al. 2015. Unraveling the hydrology of a Himalayan catchment through integration of high resolution in situ data and remote sensing with an advanced simulation model. Advances in Water Resources 78: 94-111. doi: http://dx.doi.org/10.1016/j.advwatres.2015.01.013.

Randall-Goodwin, E., et al. 2015. Freshwater distributions and water mass structure in the Amundsen Sea Polynya region, Antarctica. Elementa. doi: http://dx.doi.org/10.12952/journal.elementa.000065#sthash.vKJcMS15.dpuf.

Romshoo, Shakil Ahmad, et al. 2015. Implications of Shrinking Cryosphere Under Changing Climate on the Streamflows in the Lidder Catchment in the Upper Indus Basin, India. Arctic, Antarctic and Alpine Research 47(4): 627-644. doi: http://dx.doi.org/10.1657/AAAR0014-088.

Roy, A., et al. 2015. Evaluation of Spaceborne L-Band Radiometer Measurements for Terrestrial Freeze/Thaw Retrievals in Canada. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 8(9): 4442-4459. doi: http://dx.doi.org/10.1109/JSTARS.2015.2476358.

She, Jiangfeng, et al. 2015. Spatial and Temporal Characteristics of Snow Cover in the Tizinafu Watershed of the Western Kunlun Mountains. Remote Sensing 7(4): 3426-3445. doi: http://dx.doi.org/10.3390/rs70403426.

Spieß, M., et al. 2015. MODIS derived equilibrium line altitude estimates for Purogangri ice cap, Tibetan Plateau, and their relation to climatic predictors (2001–2012). Geografiska Annaler: Series A, Physical Geography: 1-17. doi: http://dx.doi.org/10.1111/geoa.12102.

Su, W., et al. 2015. Next-generation angular distribution models for top-of-atmosphere radiative flux calculation from CERES instruments: methodology. Atmospheric Measurements and Techniques 8: 611-632. doi: http://dx.doi.org/10.5194/amt-8-611-2015.

Suzuki, Kazuyoshi, Glen E. Liston, and Koji Matsuo. 2015. Estimation of Continental-Basin-Scale Sublimation in the Lena River Basin, Siberia. Advances in Meteorology 2015. Art. #286206. doi: http://dx.doi.org/10.1155/2015/286206.

Tahir, Adnan Ahmad, et al. 2015. Snow cover trend and hydrological characteristics of the Astore River basin (Western Himalayas) and its comparison to the Hunza basin (Karakoram region). Science of the Total Environment 505: 748-761. doi: http://dx.doi.org/10.1016/j.scitotenv.2014.10.065.

Tamura-Wicks, Helen, Ralf Toumi, and W. Paul Budgell. 2015. Sensitivity of Caspian sea-ice to air temperature. Quarterly Journal of the Royal Meteorological Society 141(693): 3089-3096. doi: http://dx.doi.org/10.1002/qj.2592.

Toure, Ally M., et al. 2015. Evaluation of the Snow Simulations from the Community Land Model, Version 4 (CLM4). Journal of Hydrometeorology 17(1): 153–170. doi: http://dx.doi.org/10.1175/JHM-D-14-0165.1.

Walker, Catherine C., et al. 2015. Observations of interannual and spatial variability in rift propagation in the Amery Ice Shelf, Antarctica, 2002–14. Journal of Glaciology 61(226): 243-252. doi: http://dx.doi.org/10.3189/2015JoG14J151.

Wang, Jie, et al. 2015. Surface Albedo Variation and Its Influencing Factors over Dongkemadi Glacier, Central Tibetan Plateau. Advances in Meteorology. Art. #852098.

Wang, Kun. 2015. Snow effects on alpine vegetation in the Qinghai-Tibetan Plateau. International Journal of Digital Earth 8(1): 56-73. doi: http://dx.doi.org/10.1080/17538947.2013.848946.

Wang, Rong, et al. 2015. Linkages between Quaternary climate change and sedimentary processes in Hala Lake, northern Tibetan Plateau, China. Journal or Asian Earth Sciences 107: 140-150. doi: http://dx.doi.org/10.1016/j.jseaes.2015.04.008.

Wang, Tao, et al. 2015. Spring snow cover deficit controlled by intraseasonal variability of the surface energy fluxes. Environmental Research Letters 10(2). Art. #024018. doi: http://dx.doi.org/10.1088/1748-9326/10/2/024018.

Wang, Wei, et al. 2015. Spatio-Temporal Change of Snow Cover and Its Response to Climate over the Tibetan Plateau Based on an Improved Daily Cloud-Free Snow Cover Product. Remote Sensing 7(1): 169-194. doi: http://dx.doi.org/10.3390/rs70100169.

Willmes, S., and G. Heinemann. 2015. Pan-Arctic lead detection from MODIS thermal infrared imagery. Annals of Glaciology 56(69): 29-37. doi: http://dx.doi.org/10.3189/2015AoG69A615.

Wu, Xuejiao, et al. 2015. Variations in albedo on Dongkemadi Glacier in Tanggula Range on the Tibetan Plateau during 2002–2012 and its linkage with mass balance. Arctic, Antarctic, and Alpine Research 47(2): 71-82.

Yang, Juntao, et al. 2015. Evaluation of snow products over the Tibetan Plateau. Hydrological Processes 29(15): 3247-3260. doi: http://dx.doi.org/10.1002/hyp.10427.

Yasunari, Teppei J., et al. 2015. Impact of snow darkening via dust, black carbon, and organic carbon on boreal spring climate in the Earth system. Journal of Geophysical Research - Atmospheres 120(11): 5485-5503. doi: http://dx.doi.org/10.1002/2014JD022977.

Zhang, Guoqing, et al. 2015. Quantitative water resources assessment of Qinghai Lake basin using Snowmelt Runoff Model (SRM). Journal of Hydrology 519: 976-987. doi: http://dx.doi.org/10.1016/j.jhydrol.2014.08.022.

Zhang, Xiuyu, and Qiting Zuo. 2015. Analysis of Water Resource Situation of the Tarim River Basin and the System Evolution under the Changing Environment. Journal of Coastal Research 73: 9-16. doi: http://dx.doi.org/10.2112/SI73-003.1.

2014

Abake, Gulijianati et al. 2014. Potential Hazard Map for Snow Disaster Prevention Using GIS-Based Weighted Linear Combination Analysis and Remote Sensing Techniques: A Case Study in Northern Xinjiang, China. Advances in Remote Sensing 3(4). Art. #52718. doi: http://dx.doi.org/10.4236/ars.2014.34018.

Abeli, Thomas et al. 2014. Geographical pattern in the response of the arctic-alpine Silene suecica (Cariophyllaceae) to the interaction between water availability and photoperiod. Ecological Research 30(2). doi: http://dx.doi.org/10.1007/s11284-014-1225-3.

Alemohammad, Seyed H. Dara Entekhabi, and Dennis B. McLaughlin. 2014. Evaluation of Long-Term SSM/I-Based Precipitation Records over Land. Journal of Hydrometeorology 15(5): 2012–2029. doi: http://dx.doi.org/10.1175/JHM-D-13-0171.1.

Alexander, P. M. et al. 2014. Assessing spatio-temporal variability and trends in modelled and measured Greenland Ice Sheet albedo (2000–2013). The Cryosphere 8: 2293-2312. doi: http://dx.doi.org/10.5194/tc-8-2293-2014.

Arsenault, Kristi R., Paul R. Houser, and Gabriëlle J. M. De Lannoy. 2014. Evaluation of the MODIS snow cover fraction product. Hydrological Processes 28(3): 980-988. doi: http://dx.doi.org/10.1002/hyp.9636.

Bavera, D., et al. 2014. A comparison between two statistical and a physically-based model in snow water equivalent mapping. Advances in Water Resources 63: 167-178. doi: http://dx.doi.org/10.1016/j.advwatres.2013.11.011.

Bennartz, Ralf, Philip Lorenz, and Daniela Jacob. 2014. A comparison of the BALTIMOS coupled climate model with atmospheric and sea surface parameters derived from AMSR-E. Theoretical and Applied Climatology 118(4): 617-625. doi: http://dx.doi.org/10.1007/s00704-009-0178-x.

Bergeron, Jean et al. 2014. Snow cover estimation using blended MODIS and AMSR-E data for improved watershed-scale spring streamflow simulation in Quebec, Canada. Hydrological Processes 28(16): 4626-4639. doi: http://dx.doi.org/10.1002/hyp.10123.

Brisbourne, A. M., et al. 2014. Seabed topography beneath Larsen C Ice Shelf from seismic soundings. The Cryosphere 8(1): 1-13. doi: http://dx.doi.org/10.5194/tc-8-1-2014.

Byun, Kyuhyun, and and Minha Choi 2014. Uncertainty of snow water equivalent retrieved from AMSR-E brightness temperature in northeast Asia. Hydrological Processes 28(7): 3173–3184. doi: http://dx.doi.org/10.1002/hyp.9846.

Chen, Siyu, et al. 2014. Interrelation among climate factors, snow cover, grassland vegetation, and lake in the Nam Co basin of the Tibetan Plateau. J. of Applied Remote Sensing 8(1). Art. #084694. doi: http://dx.doi.org/10.1117/1.JRS.8.084694.

Cortés, Gonzalo et al. 2014. Analysis of sub-pixel snow and ice extent over the extratropical Andes using spectral unmixing of historical Landsat imagery. Remote Sensing of Environment 141: 64-78. doi: http://dx.doi.org/10.1016/j.rse.2013.10.023.

Culibrk, D., et al. 2014. Sources of remote sensing data for precision irrigation. Sensing Technologies for Precision Irrigation. New York: Springer, 53-67.

Da Ronco, P. and C. De Michele. 2014. Cloud obstruction and snow cover in Alpine areas from MODIS products. Hydrology and Earth System Sciences 18: 4579-4600. doi: http://dx.doi.org/10.5194/hess-18-4579-2014.

Dedieu, J. P. et al. 2014. Shifting mountain snow patterns in a changing climate from remote sensing retrieval. Science of the Total Environment 493: 1267-1279. doi: http://dx.doi.org/10.1016/j.scitotenv.2014.04.078.

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