Published Research

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

2015

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.

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.

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..

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.isn.100240.2015.005.

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.

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. 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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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, 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.

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.

Dietze, Andreas J. et al. 2014. Identifying Changing Snow Cover Characteristics in Central Asia between 1986 and 2014 from Remote Sensing Data. Remote Sensing 6: 12752-12775. doi: http://dx.doi.org/10.3390/rs61212752.

Doherty, Sarah J. 2014. Black carbon and other light-absorbing particles in snow of central North America. Journal of Geophysical Research - Atmospheres 119(22): 12807-12831. doi: http://dx.doi.org/10.1002/2014JD022350.

Dong, Jiarui et al. 2014. Using Air Temperature to Quantitatively Predict the MODIS Fractional Snow Cover Retrieval Errors over the Continental United States. Journal of Hydrometeorology 15(2): 551-562. doi: http://dx.doi.org/10.1175/JHM-D-13-060.1.

Dumont, M., et al. 2014. Contribution of light-absorbing impurities in snow to Greenland's darkening since 2009. Nature Geoscience 7: 509-512. doi: http://dx.doi.org/10.1038/ngeo2180.

Duo, Chu, et al. 2014. Snow cover variation over the Tibetan Plateau from MODIS and comparison with ground observations. J. of Applied Remote Sensing 8(1). Art. #084690. doi: http://dx.doi.org/10.1117/1.JRS.8.084690.

Eisner, Lisa B. et al. 2014. Climate-mediated changes in zooplankton community structure for the eastern Bering Sea. Deep-Sea Research Part II - Topical Studies in Oceanography 109: 157-171. doi: http://dx.doi.org/10.1016/j.dsr2.2014.03.004.

Farhan, Suhaib Bin et al. 2014. Hydrological regimes under the conjunction of westerly and monsoon climates: a case investigation in the Astore Basin, Northwestern Himalaya. Climate Dynamics. doi: http://dx.doi.org/10.1007/s00382-014-2409-9.

Fernandes, R. Fuqun Zhou, and Hyungkeon Song. 2014. Evaluation of multiple datasets for snow cover indicators for Canada. Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International: 239-242. doi: http://dx.doi.org/10.1109/IGARSS.2014.6946401.

González, E. Perez and P. Garcia Rodriguez. 2014. Evolution in sea ice from 1978 to 2012. Environmental Earth Sciences 72(9): 3467-3477. doi: http://dx.doi.org/10.1007/s12665-014-3254-1.

Grab, S. W. and J. H. Linde. 2014. Mapping exposure to snow in a developing African context: implications for human and livestock vulnerability in Lesotho. Natural Hazards 71(3): 1537-1560. doi: http://dx.doi.org/10.1007/s11069-013-0964-8.

Gu, Lingjia, et al. 2014. Snow depth and snow cover retrieval from FengYun3B microwave radiation imagery based on a snow passive microwave unmixing method in Northeast China. Journal of Applied Remote Sensing 8(1). Art. #084682. doi: http://dx.doi.org/10.1117/1.JRS.8.084682.

Hakeem, Samreen Abdul, et al. 2014. Remote Sensing Data Application to Monitor Snow Cover Variation and Hydrological Regime in a Poorly Gauged River CatchmentÑNorthern Pakistan. International J. of Geosciences 5(1): 27-37. doi: http://dx.doi.org/10.4236/ijg.2014.51005.

Hancock, Steven, et al. 2014. Biases in Reanalysis Snowfall Found by Comparing the JULES Land Surface Model to GlobSnow. J. of Climate 27(2): 624-632. doi: http://dx.doi.org/10.1175/JCLI-D-13-00382.1.

Hasson, S. et al. 2014. Early 21st century snow cover state over the western river basins of the Indus River system. Hydrology and Earth System Sciences 18: 4077-4100. doi: http://dx.doi.org/10.5194/hess-18-4077-2014.

He, Z. H. et al. 2014. Estimating degree-day factors from MODIS for snowmelt runoff modeling. Hydrology and Earth System Sciences 18: 4773-4789. doi: http://dx.doi.org/10.5194/hess-18-4773-2014.

Hou, Jinliang and Chunlin Huang. 2014. Improving Mountainous Snow Cover Fraction Mapping via Artificial Neural Networks Combined With MODIS and Ancillary Topographic Data. IEEE Transactions on Geoscience and Remote Sensing 52(9): 5601-5611. doi: http://dx.doi.org/10.1109/TGRS.2013.2290996.

Jayaprasad, P. et al. 2014. Ice calving and deformation from Antarctic ice margins using RISAT-1 Circular Polarization SAR data. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8: 525-529. doi: http://dx.doi.org/10.5194/isprsarchives-XL-8-525-2014.

Kang, Daehyun, et al. 2014. The MODIS ice surface temperature product as an indicator of sea ice minimum over the Arctic Ocean. Remote Sensing of Environment 152: 99-108. doi: http://dx.doi.org/10.1016/j.rse.2014.05.012.

Ke, C.-Q. and Xun Liu. 2014. MODIS-observed spatial and temporal variation in snow cover in Xinjiang, China. Climate Research 59: 15-26. doi: http://dx.doi.org/10.335/cr01206.

Kheyrollah Pour, Homa, et al. 2014. Impact of satellite-based lake surface observations on the initial state of HIRLAM. Part I: evaluation of remotely-sensed lake surface water temperature observations. Tellus Series A-Dynamic Meteorology and Oceanography 66. Art. #21534. doi: http://dx.doi.org/10.3402/tellusa.v66.21534.

Kim, Youngwook, et al. 2014. Attribution of divergent northern vegetation growth responses to lengthening non-frozen seasons using satellite optical-NIR and microwave remote sensing. International Journal of Remote Sensing 35(10): 3700-3721. doi: http://dx.doi.org/10.1080/01431161.2014.915595.

Klein, Igor, et al. 2014. Evaluation of seasonal water body extents in Central Asia over the past 27 years derived from medium-resolution remote sensing data. International J. of Applied Earth Observation and Geoinformation 26: 335-349. doi: http://dx.doi.org/10.1016/j.jag.2013.08.004.

Krajčí, Pavel et al. 2014. Estimation of regional snowline elevation (RSLE) from MODIS images for seasonally snow covered mountain basins. Journal of Hydrology 519B: 1769-1778. doi: http://dx.doi.org/10.1016/j.jhydrol.2014.08.064.

Kult, Jonathan Woonsup Choi, and Jinmu Choi. 2014. Sensitivity of the Snowmelt Runoff Model to snow covered area and temperature inputs. Applied Geography 55: 30-38. doi: http://dx.doi.org/10.1016/j.apgeog.2014.08.011.

Lhermitte, S., J. Abermann, and C. Kinnard. 2014. Albedo over rough snow and ice surfaces. The Cryosphere 8: 1069-1086 . doi: http://dx.doi.org/10.5194/tc-8-1069-2014.

Li, Hongyi, et al. 2014. Synthesis method for simulating snow distribution utilizing remotely sensed data for the Tibetan Plateau. J. of Applied Remote Sensing 8(1). Art. #084696. doi: http://dx.doi.org/10.1117/1.JRS.8.084696.

Li, Lan-Yu and Chang-Qing Ke. 2014. Analysis of spatiotemporal snow cover variations in Northeast China based on moderate-resolution-imaging spectroradiometer data. J. of Applied Remote Sensing 8(1). Art. #084695. doi: http://dx.doi.org/10.1117/1.JRS.8.084695.

Li, Xinxin et al. 2014. Measurement and Simulation of Topographic Effects on Passive Microwave Remote Sensing Over Mountain Areas: A Case Study From the Tibetan Plateau. IEEE Transactions on Geoscience and Remote Sensing 52(2): 1489-1501. doi: http://dx.doi.org/10.1109/TGRS.2013.2251887.

Liang, Jiayong et al. 2014. Improved snow depth retrieval by integrating microwave brightness temperature and visible/infrared reflectance. Remote Sensing of Environment 156: 500-509. doi: http://dx.doi.org/10.1016/j.rse.2014.10.016.

Liu, Xun Chang-Qing Ke, and Zhu-De Shao. 2014. Snow cover variations in Gansu, China, from 2002 to 2013. Theoretical and Applied Climatology. doi: http://dx.doi.org/10.1007/s00704-014-1306-9.

Lomidze, N., et al. 2014. Application of Remote sensing and GIS technologies Application of Remote sensing and GIS technologies technologies for study of for study of seasonal snow cover in Georgia seasonal snow cover in Georgia easonal snow cover in Georgia . Journal of the Georgian Geophysical Society, Issue (B), Physics of Atmosphere, Ocean, and Space Plasma 17: 107-111.

Luckman, Adrian et al. 2014. Surface melt and ponding on Larsen C Ice Shelf and the impact of föhn winds. Antarctic Science 26(6): 625-635. doi: http://dx.doi.org/10.1017/S0954102014000339.

Magand, Claire, et al. 2014. Introducing Hysteresis in Snow Depletion Curves to Improve the Water Budget of a Land Surface Model in an Alpine Catchment. J. of Hydrometeorology 15(2): 631-649. doi: http://dx.doi.org/10.1175/JHM-D-13-091.1.

Malik, M. Jahanzeb et al. 2014. Improving modeled snow albedo estimates during the spring melt season. Journal of Geophysical Research - Atmospheres 119(12): 7311–7331. doi: http://dx.doi.org/10.1002/2013JD021344.

Mhawej, Mario, et al. 2014. Towards an enhanced method to map snow cover areas and derive snow-water equivalent in Lebanon. Journal of Hydrology 513: 274-282. doi: http://dx.doi.org/10.1016/j.jhydrol.2014.03.058.

Micheletty, P. D. A. M. Kinoshita, and T. S. Hogue. 2014. Application of MODIS snow cover products: wildfire impacts on snow and melt in the Sierra Nevada. Hydrology and Earth System Sciences 18: 4601-4615. doi: http://dx.doi.org/10.5194/hess-18-4601-2014.

Mishra, Bhogendra, Mukand S. Babel, and Nitin K. Tripathi. 2014. Analysis of climatic variability and snow cover in the Kaligandaki River Basin, Himalaya, Nepal. Theoretical and Applied Climatology 116: 681–694. doi: http://dx.doi.org/10.1007/s00704-013-0966-1.

Mishra, Bhogendra, Nitin K. Tripathi, and Mukand S. Babel. 2014. An Artificial Neural Network-Based Snow Cover Predictive Modeling in the Higher Himalayas. J. of Mountain Science 11(4): 825-837. doi: http://dx.doi.org/10.1007/s11629-014-2985-5.

Möller, Rebecca, et al. 2014. MODIS-derived albedo changes of Vatnajškull (Iceland) due to tephra deposition from the 2004 Grímsvötn eruption. International J. of Applied Earth Observation and Geoinformation 26: 256-269. doi: http://dx.doi.org/10.1016/j.jag.2013.08.005.

Molotch, Noah P. and Leah Meromy. 2014. Physiographic and climatic controls on snow cover persistence in the Sierra Nevada Mountains. Hydrological Processes 28(16): 4573–4586. doi: http://dx.doi.org/10.1002/hyp.10254.

Moore, Cara, et al. 2014. A GIS-based method for defining snow zones: application to the western United States. Geocarta International. doi: http://dx.doi.org/10.1080/10106049.2014.885089.

Moradi, Ayoub et al. 2014. Evaluation of MODIS data for improved monitoring of the Caspian Sea. International Journal of Remote Sensing 35(16): 6060-6075. doi: http://dx.doi.org/10.1080/01431161.2014.943324.

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