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.

2017

Huang, Xiaodong, et al. 2017. Impact of climate and elevation on snow cover using integrated remote sensing snow products in Tibetan Plateau. Remote Sensing of Environment 190: 274–288. doi: http://dx.doi.org/10.1016/j.rse.2016.12.028.

Kwon, Yonghwan, et al. 2017. Estimating Snow Water Storage in North America Using CLM4, DART, and Snow Radiance Data Assimilation . Journal of Hydrometeorology 17(11): 2853–2874. doi: http://dx.doi.org/10.1175/JHM-D-16-0028.1.

2016

Azmat, Muhammad, et al. 2016. Hydrological modeling to simulate streamflow under changing climate in a scarcely gauged cryosphere catchment. Environmental Earth Sciences 75. Art. #186. doi: http://dx.doi.org/10.1007/s12665-015-5059-2.

Boike, Julia, et al. 2016. Satellite-derived changes in the permafrost landscape of central Yakutia, 2000–2011: Wetting, drying, and fires. Global and Planetary Change 139: 116-127. doi: http://dx.doi.org/10.1016/j.gloplacha.2016.01.001.

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.

Chen, Xiaona, Shunlin Liang, and Yunfeng Cao. 2016. Satellite observed changes in the Northern Hemisphere snow cover phenology and the associated radiative forcing and feedback between 1982 and 2013. Environmental Research Letters 11. Art. #084002. doi: http://dx.doi.org/10.1088/1748-9326/11/8/084002.

Cornwell, E., N. P. Molotch, and J. McPhee. 2016. Spatio-temporal variability of snow water equivalent in the extra-tropical Andes Cordillera from distributed energy balance modeling and remotely sensed snow cover . Hydrology and Earth System Sciences 20: 411-430. doi: http://dx.doi.org/10.5194/hess-20-411-2016.

Da Ronco, Pierfrancesco, et al. 2016. Comparing COSMO-CLM simulations and MODIS data of snow cover extent and distribution over Italian Alps. Climate Dynamics. doi: http://dx.doi.org/10.1007/s00382-016-3054-2.

Dedieu, Jean-Pierre, et al. 2016. On the Importance of High-Resolution Time Series of Optical Imagery for Quantifying the Effects of Snow Cover Duration on Alpine Plant Habitat. Remote Sensing 8(6). Art. #481. doi: http://dx.doi.org/10.3390/rs8060481.

Dong, Chunyu, and Lucas Menzel. 2016. Improving the accuracy of MODIS 8-day snow products with in situ temperature and precipitation data. Journal of Hydrology 534: 466-477. doi: http://dx.doi.org/10.1016/j.jhydrol.2015.12.065.

Dong, Chunyu, and Lucas Menzel. 2016. Producing cloud-free MODIS snow cover products with conditional probability interpolation and meteorological data. Remote Sensing of Environment 186: 439–451. doi: http://dx.doi.org/10.1016/j.rse.2016.09.019.

Fassnacht, Steven R. et al. 2016. Deriving snow-cover depletion curves for different spatial scales from remote sensing and snow telemetry data. Hydrological Processes 30(11): 1708-1717. doi: http://dx.doi.org/10.1002/hyp.10730.

Gafurov, A., et al. 2016. MODSNOW-Tool: an operational tool for daily snow cover monitoring using MODIS data. Environmental Earth Sciences 75(14). Art. #1078. doi: http://dx.doi.org/10.1007/s12665-016-5869-x.

Good, Elizabeth J. 2016. An in situ-based analysis of the relationship between land surface “skin” and screen-level air temperatures. Journal of Geophysical Research - Atmospheres 121(15): 8801-8819. doi: http://dx.doi.org/10.1002/2016JD025318.

Gutjahr, Oliver, et al. 2016. Quantification of ice production in Laptev Sea polynyas and its sensitivity to thin-ice parameterizations in a regional climate model. The Cryosphere 10: 2999-3019. doi: http://dx.doi.org/10.5194/tc-10-2999-2016.

Hawotte, Florent, et al. 2016. Assessment of Automated Snow Cover Detection at High Solar Zenith Angles with PROBA-V. Remote Sensing 8(9). Art. #699. doi: http://dx.doi.org/10.3390/rs8090699.

Huang, Xiaodong, et al. 2016. Spatiotemporaldynamicsofsnowcoverbased onmulti-sourceremotesensingdatainChina. Cryosphere 10(5): 2453-2463. doi: http://dx.doi.org/10.5194/tc-10-2453-2016.

Jeong, Dae Il, Laxmi Sushama, and M. Naveed Khaliq. 2016. Attribution of spring snow water equivalent (SWE) changes over the northern hemisphere to anthropogenic effects. Climate Dynamics. doi: http://dx.doi.org/10.1007/s00382-016-3291-4.

Jiang, Youyan, et al. 2016. Variation in the snow cover on the Qilian Mountains and its causes in the early 21st century. Geomatics, Natural Hazards and Risk. doi: http://dx.doi.org/10.1080/19475705.2016.1176078.

Kadlec, J., A. Woodruff Miller, and Daniel P. Ames. 2016. Extracting Snow Cover Time Series Data from Open Access Web Mapping Tile Services. Journal of the American Water Resources Association (JAWRA) 52(4): 916-932. doi: http://dx.doi.org/10.1111/1752-1688.12387.

Kar, Sarat C., and Sarita Tiwari. 2016. Model simulations of heavy precipitation in Kashmir, India, in September 2014. Natural Hazards 81(1): 167-188. doi: http://dx.doi.org/10.1007/s11069-015-2073-3.

Karimi, Hamid, et al. 2016. Comparison of SRM and WetSpa models efficiency for snowmelt runoff simulation. Environmental Earth Sciences 75(8). Art. #664. doi: http://dx.doi.org/10.1007/s12665-016-5490-z.

Krajčí, Pavel, Ladislav Holko, and Juraj Parajka. 2016. Variability of snow line elevation, snow cover area and depletion in the main Slovak basins in winters 2001–2014. Journal of Hydrology and Hydromechanics 64(1): 12-22. doi: http://dx.doi.org/10.1515/johh-2016-0011.

Li, Haixing, Xingong Li, and Pengfeng Xiao. 2016. Impact of Sensor Zenith Angle on MOD10A1 Data Reliability and Modification of Snow Cover Data for the Tarim River Basin. Remote Sensing 8(9). Art. #750. doi: http://dx.doi.org/10.3390/rs8090750.

Li, Yue, et al. 2016. Evaluating biases in simulated land surface albedo from CMIP5 global climate models. Journal of Geophysical Research - Atmospheres 121(11): 6178–6190. doi: http://dx.doi.org/10.1002/2016JD024774.

Marcil, Gino-Karl, Mélanie Trudel, and Robert Leconte. 2016. Using Remotely Sensed MODIS Snow Product for the Management of Reservoirs in a Mountainous Canadian Watershed. Water Resources Management 30(8): 2735–2747. doi: http://dx.doi.org/10.1007/s11269-016-1319-5.

Martin, Eric, et al. 2016. On the Use of Hydrological Models and Satellite Data to Study the Water Budget of River Basins Affected by Human Activities: Examples from the Garonne Basin of France. Surveys in Geophysics 37(2): 223-247. doi: http://dx.doi.org/10.1007/s10712-016-9366-2.

Meng, Chunlei. 2016. Quantifying the impacts of snow on surface energy balance through assimilating snow cover fraction and snow depth. Meteorology and Atmospheric Physics. doi: http://dx.doi.org/10.1007/s00703-016-0486-5.

Meng, Fanchong, et al. 2016. Impacts of recent climate change on the hydrology in the source region of the Yellow River basin. Journal of Hydrology: Regional Studies 6: 66–81. doi: http://dx.doi.org/10.1016/j.ejrh.2016.03.003.

Mishra, P. et al. 2016. Accuracy Assessment of MODIS Fractional Snow Cover Product for Eastern Himalayan Catchment. Journal of the Indian Society of Remote Sensing. doi: http://dx.doi.org/10.1007/s12524-016-0548-7.

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.

Mozaffari, A., et al. 2016. A hierarchical selective ensemble randomized neural network hybridized with heuristic feature selection for estimation of sea-ice thickness. Applied Intelligence. doi: http://dx.doi.org/10.1007/s10489-016-0815-x.

Mozaffari, A., et al. 2016. A modular ridge randomized neural network with differential evolutionary distributor applied to the estimation of sea ice thickness. Soft Computing. doi: http://dx.doi.org/10.1007/s00500-016-2074-5.

Muhammad, P., C. Duguay, and K.-K. Kang. 2016. Monitoring ice break-up on the Mackenzie River using MODIS data. Cryosphere 10(2): 569-584. doi: http://dx.doi.org/10.5194/tc-10-569-2016.

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.

Painter, Tom, et al. 2016. The Airborne Snow Observatory: Fusion of scanning lidar, imaging spectrometer, and physically-based modeling for mapping snow water equivalent and snow albedo. Remote Sensing of Environment 184: 139-152. doi: http://dx.doi.org/10.1016/j.rse.2016.06.018.

Preußer, Andreas, et al. 2016. Circumpolar polynya regions and ice production in the Arctic: results from MODIS thermal infrared imagery from 2002/2003 to 2014/2015 with a regional focus on the Laptev Sea. The Cryosphere 10: 3021-3042. doi: http://dx.doi.org/10.5194/tc-10-3021-2016.

Rani, Seema, and S. Sreekesh. 2016. An Analysis of Pattern of Changes in Snow Cover in the Upper Beas River Basin, Western Himalaya. Geostatistical and Geospatial Approaches for the Characterization of Natural Resources in the Environment: 899-903. New Dehli: Springer International Publishing. N. Janardhana Raju, editor.. doi: http://dx.doi.org/10.1007/978-3-319-18663-4_139.

Rhoades, Alan, et al. 2016. Characterizing Sierra Nevada Snowpack Using Variable-Resolution CESM. Journal of Applied Meteorology and Climatology 55(1): 173-196. doi: http://dx.doi.org/10.1175/JAMC-D-15-0156.1.

Rondeau-Genesse, Gabriel, Mélanie Trudel, and Robert Leconte. 2016. Monitoring snow wetness in an Alpine Basin using combined C-band SAR and MODIS data. Remote Sensing of Environment 183: 304-317. doi: http://dx.doi.org/10.1016/j.rse.2016.06.003.

Rondeau-Genesse, Gabriel, Mélanie Trudel, and Robert Leconte. 2016. Monitoring snow wetness in an Alpine Basin using combined C-band SAR and MODIS data. Remote Sensing of Environment 183: 304-317. doi: http://dx.doi.org/10.1016/j.rse.2016.06.003.

Saleh, Mahdi, and Ghaleb Faour. 2016. Implementation of an automated snow monitoring system using MODIS products in Lebanon . 2016 18th Mediterranean Electrotechnical Conference (MELECON) : 1-4. Lemesos: IEEE. doi: http://dx.doi.org/10.1109/MELCON.2016.7495479.

Snehmani, et al. 2016. Analysis of snow cover and climatic variability in Bhaga basin located in western Himalaya. Geocarta International 31(10): 1094-1107.

Song, Chengyun, and Li Jia. 2016. A Method for Downscaling FengYun-3B Soil Moisture Based on Apparent Thermal Inertia. Remote Sensing 8(9): Art. #703. doi: http://dx.doi.org/10.3390/rs8090703.

Spiess, Marina, Eva Huintjes, and Christoph Schneider. 2016. Comparison of modelled- and remote sensing- derived daily snow line altitudes at Ulugh Muztagh, northern Tibetan Plateau. Journal of Mountain Science 13(4): 593-613. doi: http://dx.doi.org/10.1007/s11629-015-3818-x.

Sugg, Johnathan W., et al. 2016. Sub-regional snow cover distribution across the southern Appalachian Mountains. Physical Geography. doi: http://dx.doi.org/10.1080/02723646.2016.1162020.

Tahir, Adnan Ahmad, et al. 2016. Comparative assessment of spatiotemporal snow cover changes and hydrological behavior of the Gilgit, Astore and Hunza River basins (Hindukush–Karakoram–Himalaya region, Pakistan). Meteorology and Atmospheric Physics. doi: http://dx.doi.org/10.1007/s00703-016-0440-6.

Tarasova, L., et al. 2016. Effects of input discretization, model complexity, and calibration strategy on model performance in a data-scarce glacierized catchment in Central Asia. Water Resources Research 52(6): 4674–4699. doi: http://dx.doi.org/10.1002/2015WR018551.

Toure, Ally M., et al. 2016. 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.

Trubilowicz, Joel William. 2016. Hydrometeorology and streamflow response during rain-on-snow events in a coastal mountain region. . Ph. D. University of British Columbia.

Uysal, Gökçen, Aynur Şensoy, and Arda Şorman. 2016. Improving daily streamflow forecasts in mountainous Upper Euphrates basin by multi-layer perceptron model with satellite snow products. Journal of Hydrology 543B: 630–650. doi: http://dx.doi.org/10.1016/j.jhydrol.2016.10.037.

Wang, Jun, Yang Wang, and Shiji Wang. 2016. Biophysical and socioeconomic drivers of the dynamics in snow hazard impacts across scales and over heterogeneous landscape in Northern Tibet. Natural Hazards 81(3): 1499-1514. doi: http://dx.doi.org/10.1007/s11069-015-2142-7.

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.

Wu, Xuejiao, et al. 2016. Coupling the WRF model with a temperature index model based on remote sensing for snowmelt simulations in a river basin in the Altay Mountains, north-west China. Hydrological Processes 30(21): 3967–3977. doi: http://dx.doi.org/10.1002/hyp.10924.

Wulf, Hendrik, Bodo Bookhagena, and Dirk Scherlera. 2016. Differentiating between rain, snow, and glacier contributions to river discharge in the western Himalaya using remote-sensing data and distributed hydrological modeling. Advances in Water Resources 88: 152–169. doi: http://dx.doi.org/10.1016/j.advwatres.2015.12.004.

Wunderle, Stefan, Timm Gross, and Fabia Hüsler. 2016. Snow Extent Variability in Lesotho Derived from MODIS Data (2000–2014). Remote Sensing 8(6). Art. #448. doi: http://dx.doi.org/10.3390/rs8060448.

Xu, Jianhui, et al. 2016. Joint DEnKF-albedo assimilation scheme that considers the common land model subgrid heterogeneity and a snow density-based observation operator for improving snow depth simulations. Journal of Applied Remote Sensing 10(3). Art. #036001. doi: http://dx.doi.org/10.1117/1.JRS.10.036001.

Xu, Jianhui, et al. 2016. Improvement of the Snow Depth in the Common Land Model by Coupling a Two-Dimensional Deterministic Ensemble Model with a Variational Hybrid Snow Cover Fraction Data Assimilation Scheme and a New Observation Operator. Journal of Hydrometeorology 18(1): 119-138. doi: http://dx.doi.org/10.1175/JHM-D-16-0149.1.

Xu, Y., V. Ramanathan, and W. M. Washington. 2016. Observed high-altitude warming and snow cover retreat over Tibet and the Himalayas enhanced by black carbon aerosols. Atmospheric Chemistry and Physics 16: 1303-1315. doi: http://dx.doi.org/10.5194/acp-16-1303-2016.

Yi, Shuang, Qiuyu Wang, and Wenke Sun. 2016. Is it possible that a gravity increase of 20μ Galyr-1 in southern Tibet comes from a wide-range density increase?. Geophysical Research Letters 43(4): 1481-1486. doi: http://dx.doi.org/10.1002/2015GL067509.

Yuan, Jian 2016. Variability of oceanic deep convective system vertical structures observed by CloudSat in Indo-Pacific regions associated with the Madden-Julian oscillation. Journal of Geophysical Research - Atmospheres 121(18): 10,761–10,785. doi: http://dx.doi.org/10.1002/2016JD025262.

Yuang, Wenping, et al. 2016. Improved snow cover model in terrestrial ecosystem models over the Qinghai–Tibetan Plateau. Agricultural and Forest Meteorology 218-219: 161-170. doi: http://dx.doi.org/10.1016/j.agrformet.2015.12.004.

Zhang, Yong-Fei, and and Zong Liang-Yang. 2016. Estimating uncertainties in the newly developed multi-source land snow data assimilation system. Journal of Geophysical Research - Atmospheres 121(14): 8254–8268. doi: http://dx.doi.org/10.1002/2015JD024248.

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.

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.

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