Published Research

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

2016

Su, Yanjun, et al. 2016. Spatial distribution of forest aboveground biomass in China: Estimation through combination of spaceborne lidar, optical imagery, and forest inventory data. Remote Sensing of Environment 173: 187-199. doi: http://dx.doi.org/10.1016/j.rse.2015.12.002.

Su, Yanjun, Qin, and Qinghua Guo. 2016. Fine-resolution forest tree height estimation across the Sierra Nevada through the integration of spaceborne LiDAR, airborne LiDAR, and optical imagery. International Journal of Digital Earth 10(3): 307-323. doi: http://dx.doi.org/10.1080/17538947.2016.1227380.

Takaku, Junichi, et al. 2016. Validation of 'AW3D' Global DSM Generated From ALOS Prism. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences III-4: 25-31.

Tang, H., et al. 2016. Characterizing leaf area index (LAI) and vertical foliage profile (VFP) over the United States. Biogeosciences 13(1): 239-252. doi: http://dx.doi.org/10.5194/bg-13-239-2016.

Tao, Shengli, et al. 2016. Global patterns and determinants of forest canopy height. Ecology 97(12): 3265–3270. doi: http://dx.doi.org/10.1002/ecy.1580.

Toyoda, Takahiro, et al. 2016. Data assimilation of sea ice concentration into a global ocean–sea ice model with corrections for atmospheric forcing and ocean temperature fields. Journal of Oceanography 72(2): 235-262. doi: http://dx.doi.org/10.1007/s10872-015-0326-0.

Treichler, D., and A. Kääb. 2016. ICESat laser altimetry over small mountain glaciers. Cryosphere 10(5): 2129-2146. doi: http://dx.doi.org/10.5194/tc-10-2129-2016.

Visakh, S., S. Muralikrishnan and M. Sreedhar. 2016. Improving the Elevation Accuracy of CARTOSAT -1 DEM. International Journal for Innovative Research in Science & Technology 2(8): 117-128.

Wang, Qiuyu, Shuang Yi, and Wenke Sun. 2016. The changing pattern of lake and its contribution to increased mass in the Tibetan Plateau derived from GRACE and ICESat data. Geophysical Journal International 207(1): 528-541. doi: http://dx.doi.org/10.1093/gji/ggw293.

Wang, Xianwei, et al. 2016. Grounding and calving cycle of Mertz Ice Tongue revealed by shallow Mertz Bank. The Cryosphere 10(5): 2043–2056. doi: http://dx.doi.org/10.5194/tc-10-2043-2016.

Wang, Xianwei, et al. 2016. Grounding and calving cycle of Mertz Ice Tongue revealed by shallow Mertz Bank . The Cryosphere 10(5): 2043-2056. doi: http://dx.doi.org/10.5194/tc-10-2043-2016.

Wang, Yuanyuan, et al. 2016. A combined GLAS and MODIS estimation of the global distribution of mean forest canopy height. Remote Sensing of Environment 174: 24-43. doi: http://dx.doi.org/10.1016/j.rse.2015.12.005.

Wendleder, A., et al. 2016. A Method to Estimate Long-Wave Height Errors of SRTM C-Band DEM. IEEE Geoscience and Remote Sensing Letters 13(5): 696-700. doi: http://dx.doi.org/10.1109/LGRS.2016.2538822.

Xi, Xiaohuan, et al. 2016. Forest above Ground Biomass Inversion by Fusing GLAS with Optical Remote Sensing Data. International Journal of Geoinformation 5(4). Art. #45. doi: http://dx.doi.org/10.3390/ijgi5040045.

Xie, Huan, et al. 2016. A Least-Squares Adjusted Grounding Line for the Amery Ice Shelf Using ICESat and Landsat 8 OLI Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 9(11): 5113-5122. doi: http://dx.doi.org/10.1109/JSTARS.2016.2614758.

Xie, Huan, et al. 2016. Antarctic Ice Sheet Surface Mass Balance Estimates From 2003 to 2015 Using ICESat and CRYOSAT-2 Data. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLI-B8, 2016 XXIII ISPRS Congress, 12–19 July 2016, Prague, Czech Republic 41-B8. Prague: ISPRS, 549-553 . doi: http://dx.doi.org/10.5194/isprsarchives-XLI-B8-549-2016.

Xie, Huan, et al. 2016. A comparative study of changes in the Lambert Glacier/Amery Ice Shelf system, East Antarctica, during 2004–2008 using gravity and surface elevation observations. Journal of Glaciology 62(235): 888–904. doi: http://dx.doi.org/10.1017/jog.2016.76.

Xing, Yanqiu, et al. 2016. Estimation of Regional Forest AbovegroundBiomass Combining ICESat/GLAS Waveforms and HJ-1A/HSI Hyperspectral Imageries. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLI-B7, 2016 XXIII ISPRS Congress, 12–19 July 2016, Prague, Czech Republic 41(B7): 731-737. doi: http://dx.doi.org/10.5194/isprsarchives-XLI-B7-731-2016.

Yavaşlı, Doğukan Doğu. 2016. Estimation of above ground forest biomass at Muğla using ICESat/GLAS and Landsat data. Remote Sensing Applications: Society and Environment 4: 211–218. doi: http://dx.doi.org/10.1016/j.rsase.2016.11.004.

Yi, Donghui, et al. 2016. Antarctic sea-ice freeboard and estimated thickness from NASA's ICESat and IceBridge observations. Geoscience and Remote Sensing Symposium (IGARSS), 2016 IEEE International. Piscataway, NJ: Institute of Electrical and Electronics Engineers ( IEEE ), 7682-7685. doi: http://dx.doi.org/10.1109/IGARSS.2016.7731003.

Yi, Shuang, et al. 2016. Changes in Mountain Glaciers, Lake Levels, and Snow Coverage in the Tianshan Monitored by GRACE, ICESat, Altimetry, and MODIS. Remote Sensing 8(10). Art. # 798. doi: http://dx.doi.org/10.3390/rs8100798.

Yue, Ma, et al. 2016. Waveform model of a laser altimeter for an elliptical Gaussian beam. Applied Optics 55(8): 1957-1965. doi: http://dx.doi.org/10.1364/AO.55.001957.

Zhang, Shuping, et al. 2016. Bathymetric survey of water reservoirs in north-eastern Brazil based on TanDEM-X satellite data. Science of The Total Environment 571: 575–593. doi: http://dx.doi.org/10.1016/j.scitotenv.2016.07.024.

Zhang, Tengyu, and Shuanggen Jin. 2016. Ice mass balance and GIA effects in tibet estimated from GRACE and ICESat measurements. Progress in Electromagnetic Research Symposium (PIERS), Shanghai: 4780-4783. doi: http://dx.doi.org/10.1109/PIERS.2016.7735748.

Zhou, Yuhong, et al. 2016. Curve matching approaches to waveform classification: a case study using ICESat data. GIScience & Remote Sensing 53(6): 739-758. doi: http://dx.doi.org/10.1080/15481603.2016.1232147.

Zou, Fang, and Shuanggen Jin. 2016. Estimations of glacier melting in Greenland from combined satellite gravimetry and icesat. Geoscience and Remote Sensing Symposium (IGARSS), 2016 IEEE International: 6185-6188. doi: http://dx.doi.org/10.1109/IGARSS.2016.7730616.

2015

Andersen, M. L., et al. 2015. Basin-scale partitioning of Greenland ice sheet mass balance components (2007–2011). Earth and Planetary Science Letters 409: 89-95. doi: http://dx.doi.org/10.1016/j.epsl.2014.10.015.

Arthern, Robert J., Richard C. A. Hindmarsh, and C. Rosie Williams. 2015. Flow speed within the Antarctic ice sheet and its controls inferred from satellite observations. Journal of Geophysical Research - Earth Surface 120(7): 1171-1188. doi: http://dx.doi.org/10.1002/2014JF003239.

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.

Bevan, Suzanne L., et al. 2015. Seasonal dynamic thinning at Helheim Glacier. Earth and Planetary Science Letters 415: 47-53. doi: http://dx.doi.org/10.1016/j.epsl.2015.01.031.

Brinkerhoff, D., and J. Johnson. 2015. A stabilized finite element method for calculating balance velocities in ice sheets. Geoscience Model Development 8: 1275-1283. doi: http://dx.doi.org/10.5194/gmd-8-1275-2015.

Chi, Hong, et al. 2015. National Forest Aboveground Biomass Mapping from ICESat/GLAS Data and MODIS Imagery in China. Remote Sensing 7(5): 5534-5564. doi: http://dx.doi.org/10.3390/rs70505534.

Chuter, S. J., and J. L. Bamber. 2015. Antarctic ice shelf thickness from CryoSat-2 radar altimetry. Geophysical Research Letters 42(24): 10721-10729. doi: http://dx.doi.org/10.1002/2015GL066515.

Collins, M. B., and E. T. A. Mitchard. 2015. Integrated radar and lidar analysis reveals extensive loss of remaining intact forest on Sumatra 2007–2010. Biogeosciences 12: 6637-6653. doi: http://dx.doi.org/10.5194/bg-12-6637-2015.

Farrinotti, Daniel, et al. 2015. Substantial glacier mass loss in the Tien Shan over the past 50 years. Nature Geoscience 8: 716-722. doi: http://dx.doi.org/10.1038/ngeo2513.

Gao, Huilin. 2015. Satellite remote sensing of large lakes and reservoirs: from elevation and area to storage. WIRES 2(2): 147–157. doi: http://dx.doi.org/10.1002/wat2.1065.

Gwenzi, David. 2015. Lidar Remote Sensing of Savanna Biophysical Attributes. . Ph. D. Colorado State University.

Haarpaintner, J., et al. 2015. Tropical Forest Remote Sensing Services for the Democratic Republic of Congo Insidc the EU FP7 ‘Recover’ Project (Final Results 2000-2012). The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-7/W3, 2015 36th International Symposium on Remote Sensing of Environment, 11–15 May 2015, Berlin, Germany XL-7/W3: 397-402. doi: http://dx.doi.org/10.5194/isprsarchives-XL-7-W3-397-2015.

Han, Hyangsun, and Hoonyol Lee. 2015. Tide-corrected flow velocity and mass balance of Campbell Glacier Tongue, East Antarctica, derived from interferometric SAR. Remote Sensing of Environment 160: 180-192. doi: http://dx.doi.org/10.1016/j.rse.2015.01.014.

Hayashi, Masato, et al. 2015. Quantitative assessment of the impact of typhoon disturbance on a Japanese forest using satellite laser altimetry. Remote Sensing of Environment 156: 216-225. doi: http://dx.doi.org/10.1016/j.rse.2014.09.028.

Howat, I. M., et al. 2015. Brief Communication: Sudden drainage of a subglacial lake beneath the Greenland Ice Sheet. The Cryosphere 9(1): 103-108. doi: http://dx.doi.org/10.5194/tc-9-103-2015.

Hu, Deyong, et al. 2015. Parameterizing the aerodynamic roughness length on a regional scale based on multi-source remote-sensing data. International Journal of Remote Sensing 36(13): 3483-3502. doi: http://dx.doi.org/10.1080/01431161.2015.1059967.

Jarihani, Abdollah A., et al. 2015. Satellite-derived Digital Elevation Model (DEM) selection, preparation and correction for hydrodynamic modelling in large, low-gradient and data-sparse catchments. Journal of Hydrology 524: 489-506. doi: http://dx.doi.org/10.1016/j.jhydrol.2015.02.049.

Jiao, Jiu Jimmy, Xiaotao Zhang, and Xusheng Wang. 2015. Satellite-based estimates of groundwater depletion in the Badain Jaran Desert, China. Scientific Reports 5. #8960. doi: http://dx.doi.org/10.1038/srep08960.

Kääb, A., et al. 2015. Brief Communication: Contending estimates of 2003–2008 glacier mass balance over the Pamir–Karakoram–Himalaya. The Cryosphere 9(2): 557-564. doi: http://dx.doi.org/10.5194/tc-9-557-2015.

Ke, Linghong, Xiaoli Ding, and Chunqiao Song. 2015. Estimation of mass balance of Dongkemadi glaciers with multiple methods based on multi-mission satellite data. Quaternary International 371: 58-66. doi: http://dx.doi.org/10.1016/j.quaint.2015.02.043.

Ke, Linghong, Xiaoli Ding, and Chunqiao Song. 2015. Heterogeneous changes of glaciers over the western Kunlun Mountains based on ICESat and Landsat-8 derived glacier inventory. Remote Sensing of Environment 168: 13-23. doi: http://dx.doi.org/10.1016/j.rse.2015.06.019.

Kern, Stefan, and Gunnar Spreen. 2015. Uncertainties in Antarctic sea-ice thickness retrieval from ICESat. Annals of Glaciology 56(69): 107-119. doi: http://dx.doi.org/10.3189/2015AoG69A736.

Khan, Shfaqat A., et al. 2015. Greenland ice sheet mass balance: a review. Reports on Progress in Physics 78(4). #046801. doi: http://dx.doi.org/10.1088/0034-4885/78/4/046801.

Kinyanjui, Mwangi James, et al. 2015. Comparing Tree Heights among Montane Forest Blocks of Kenya Using LiDAR Data from GLAS. Open Journal of Forestry 5(1). Art. #53470. doi: http://dx.doi.org/10.4236/ojf.2015.51009.

Kjeldsen, Kristian K., et al. 2015. Spatial and temporal distribution of mass loss from the Greenland Ice Sheet since AD 1900. Nature 528: 396-400. doi: http://dx.doi.org/10.1038/nature16183.

Kropáček, Jan, et al. 2015. Remote Sensing for Characterisation and Kinematic Analysis of Large Slope Failures: Debre Sina Landslide, Main Ethiopian Rift Escarpment. Remote Sensing 7(12): 16183-16203. doi: http://dx.doi.org/10.3390/rs71215821.

Landy, Jack C., Jens K. Ehn, and David G. Barber. 2015. Albedo feedback enhanced by smoother Arctic sea ice. Geophysical Research Letters 42(24): 10,714–10,720. doi: http://dx.doi.org/10.1002/2015GL066712.

Lee, Changno, et al. 2015. Automated Generation of a Digital Elevation Model Over Steep Terrain in Antarctica From High-Resolution Satellite Imagery. IEEE Transactions on Geoscience and Remote Sensing 53(3): 1186-1194. doi: http://dx.doi.org/10.1109/TGRS.2014.2335773.

Levinsen, J. F., et al. 2015. ESA ice sheet CCI: derivation of the optimal method for surface elevation change detection of the Greenland ice sheet-round robin results. International Journal of Remote Sensing 36(2): 551-573. doi: http://dx.doi.org/10.1080/01431161.2014.999385.

Li, Zhiguo, et al. 2015. Changes in the glacier extent and surface elevation in Xiongcaigangri region, Southern Karakoram Mountains, China. Quaternary International 371: 67-75. doi: http://dx.doi.org/10.1016/j.quaint.2014.12.004.

Liu, Caixia, et al. 2015. Joint Use of ICESat/GLAS and Landsat Data in Land Cover Classification: A Case Study in Henan Province, China. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 8(2): 511-522. doi: http://dx.doi.org/10.1109/JSTARS.2014.2327032.

Lu, Xiaomei, and Yongxiang Hu. 2015. Accuracy of land surface elevation from CALIPSO mission data. Optical Engineering 54(3). Art. #031102. doi: http://dx.doi.org/10.1117/1.OE.54.3.031102.

Luo, She-Zhou, et al. 2015. Forest leaf area index estimation using combined ICESat/ GLAS and optical remote sensing image. Journal of Infrared and Millimeter Waves 34(2): 243-249. doi: http://dx.doi.org/10. 11972 / j. issn. 1001 - 9014. 2015. 02. 020.

Margolis, Hank A., et al. 2015. Combining satellite lidar, airborne lidar, and ground plots to estimate the amount and distribution of aboveground biomass in the boreal forest of North America. Canadian Journal of Forest Research 45(7): 838-855. doi: http://dx.doi.org/10.1139/cjfr-2015-0006.

Massom, R. A., et al. 2015. External influences on the Mertz Glacier Tongue (East Antarctica) in the decade leading up to its calving in 2010. Journal of Geophysical Research - Earth Surface 120(1): 490–506. doi: http://dx.doi.org/10.1002/2014JF003223.

Ni, Xiliang, et al. 2015. Mapping Forest Canopy Height over Continental China Using Multi-Source Remote Sensing Data. Remote Sensing 7(7): 8436-8452. doi: http://dx.doi.org/10.3390/rs70708436.

Nie, Sheng, et al. 2015. A revised terrain correction method for forest canopy height estimation using ICESat/GLAS data. ISPRS Journal of Photogrammetry and Remote Sensing 108(1): 183-190. doi: http://dx.doi.org/10.1016/j.isprsjprs.2015.07.008.

Nilsson, J., et al. 2015. Mass changes in Arctic ice caps and glaciers: implications of regionalizing elevation changes. The Cryosphere 9: 130-150. doi: http://dx.doi.org/10.5194/tc-9-139-2015.

Nuimura, T., et al. 2015. The GAMDAM glacier inventory: a quality-controlled inventory of Asian glaciers. The Cryosphere 9: 849-864. doi: http://dx.doi.org/10.5194/tc-9-849-2015.

Palmer, Steven, Malcolm McMillan, and Mathieu Morlighem. 2015. Subglacial lake drainage detected beneath the Greenland ice sheet. Nature Communications 6. Art. #8408. doi: http://dx.doi.org/10.1038/ncomms9408.

Phan, Vu Hien. 2015. Observing changes in lake level and glacial thickness on the Tibetan Plateau with the ICESat laser altimeter.

Rastogi, Gunjan, Ritesh Agrawala, and Ajai. 2015. Bias corrections of CartoDEM using ICESat-GLAS data in hilly regions. GIScience & Remote Sensing 52(5): 571-585. doi: http://dx.doi.org/10.1080/15481603.2015.1060923.

Roy, François, et al. 2015. Arctic sea ice and freshwater sensitivity to the treatment of the atmosphere-ice-ocean surface layer. Journal of Geophysical Research - Oceans 120(6): 4392-4417. doi: http://dx.doi.org/10.1002/2014JC010677.

Satgé, F., et al. 2015. Accuracy assessment of SRTM v4 and ASTER GDEM v2 over the Altiplano watershed using ICESat/GLAS data. International Journal of Remote Sensing 36(22): 465-488. doi: http://dx.doi.org/10.1080/01431161.2014.999166.

Sawada, Yoshito, et al. 2015. A new 500-m resolution map of canopy height for Amazon forest using spaceborne LiDAR and cloud-free MODIS imagery. International Journal of Applied Earth Observation and Geoinformation 43: 92-101. doi: http://dx.doi.org/10.1016/j.jag.2015.04.003.

Schoen, N., et al. 2015. Simultaneous solution for mass trends on the West Antarctic Ice Sheet. The Cryosphere 9: 805-819. doi: http://dx.doi.org/10.5194/tc-9-805-2015.

Seehaus, Thorsten, et al. 2015. Changes in ice dynamics, elevation and mass discharge of Dinsmoor–Bombardier–Edgeworth glacier system, Antarctic Peninsula. Earth and Planetary Letters 427: 125-135. doi: http://dx.doi.org/10.1016/j.epsl.2015.06.047.

Song, Chunqiao, Bo Huang, and Linghong Ke. 2015. Heterogeneous change patterns of water level for inland lakes in High Mountain Asia derived from multi-mission satellite altimetry. Hydrological Processes 29(12): 2769-2781. doi: http://dx.doi.org/10.1002/hyp.10399.

Song, Chunqiao, et al. 2015. Combined ICESat and CryoSat-2 Altimetry for Accessing Water Level Dynamics of Tibetan Lakes over 2003–2014. Water 7(9): 4685-4700. doi: http://dx.doi.org/10.3390/w7094685.

Su, Xialoi, et al. 2015. High resolution Greenland ice sheet inter-annual mass variations combining GRACE gravimetry and Envisat altimetry. Earth and Planetary Science Letters 422: 11-17. doi: http://dx.doi.org/10.1016/j.epsl.2015.04.016.

Su, Yanjun, et al. 2015. SRTM DEM Correction in Vegetated Mountain Areas through the Integration of Spaceborne LiDAR, Airborne LiDAR, and Optical Imagery. Remote Sensing 7(9): 11202-11225. doi: http://dx.doi.org/10.3390/rs70911202.

Sørensen, Louise Sandberg, et al. 2015. Envisat-derived elevation changes of the Greenland ice sheet, and a comparison with ICESat results in the accumulation area. Remote Sensing of Environment 160: 56-62. doi: http://dx.doi.org/10.1016/j.rse.2014.12.022.

Tian, Jinyan, Le Wang, and Xiaojuan Li. 2015. Sub-footprint analysis to uncover tree height variation using ICESat/GLAS. International Journal of Applied Earth Observation and Geoinformation 35B: 284-293. doi: http://dx.doi.org/10.1016/j.jag.2014.09.016.

Wang, Fang, Bamber, J.L., and Xiao Cheng. 2015. Accuracy and Performance of CryoSat-2 SARIn Mode Data Over Antarctica. IEEE Geoscience and Remote Sensing Letters 12(7): 1516-1520. doi: http://dx.doi.org/10.1109/LGRS.2015.2411434.

Wang, Ninglian, et al. 2015. Variations of the glacier mass balance and lake water storage in the Tarim Basin, northwest China, over the period of 2003-2009 estimated by the ICESat-GLAS data. Environmental Earth Sciences 74: 1997-2008. doi: http://dx.doi.org/10.1007/s12665-015-4662-6.

Willis, Michael J., et al. 2015. Outlet glacier response to the 2012 collapse of the Matusevich Ice Shelf, Severnaya Zemlya, Russian Arctic. Journal of Geophysical Research - Earth Surface 120(10): 2040-2055. doi: http://dx.doi.org/10.1002/2015JF003544.

Willis, Michael J., et al. 2015. Recharge of a subglacial lake by surface meltwater in northeast Greenland. Nature 518: 223-227. doi: http://dx.doi.org/10.1038/nature14116.

Wuite, J., et al. 2015. Evolution of surface velocities and ice discharge of Larsen B outlet glaciers from 1995 to 2013. The Cryosphere 9: 957-969. doi: http://dx.doi.org/10.5194/tc-9-957-2015.

Yang, Ting, et al. 2015. Forest canopy height mapping over China using GLAS and MODIS data. Science China-Earth Sciences 57: 96-105. doi: http://dx.doi.org/10.1007/s11430-014-4905-5.

Yu, Ying, Xiguang Yang, and Wenyi Fan. 2015. Estimates of forest structure parameters from GLAS data and multi-angle imaging spectrometer data. International Journal of Applied Earth Observation and Geoinformation 38(1): 65-71. doi: http://dx.doi.org/10.1016/j.jag.2014.12.013.

Zhao, Shangmin, et al. 2015. Rectification methods comparison for the ASTER GDEM V2 data using the ICESat/GLA14 data in the Lvliang mountains, China. Environmental Earth Sciences Thematic Issue. doi: http://dx.doi.org/10.1007/s12665-015-4614-1.

Zhou, Yu, et al. 2015. Improving InSAR elevation models in Antarctica using laser altimetry, accounting for ice motion, orbital errors and atmospheric delays. Remote Sensing of Environment 162: 112-118. doi: http://dx.doi.org/10.1016/j.rse.2015.01.017.

Zhou, Yuhong, et al. 2015. ICESat waveform-based land-cover classification using a curve matching approach. International Journal of Remote Sensing 36(1): 36-60. doi: http://dx.doi.org/10.1080/01431161.2014.990648.

Zwally, H. Jay, et al. 2015. Mass gains of the Antarctic ice sheet. Journal of Glaciology 61(230): 1019-1036. doi: http://dx.doi.org/10.3189/2015JoG15J071.

2014

Arsen, Adalbert, et al. 2014. Remote Sensing-Derived Bathymetry of Lake Poopó. Remote Sensing 6: 407-420. doi: http://dx.doi.org/10.3390/rs6010407.

Baghdadi, N., et ak, 2014. Estimation of forest height and above ground biomass from ICESat/GLAS data in Eucalyptus plantations in Brazil. Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International: 725-728. doi: http://dx.doi.org/10.1109/IGARSS.2014.6946526.

Baghdadi, N., et al. 2014. Testing Different Methods of Forest Height and Aboveground Biomass Estimations From ICESat/GLAS Data in Eucalyptus Plantations in Brazil. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 7(1): 290-299. doi: http://dx.doi.org/10.1109/JSTARS.2013.2261978.

Baghdadi, N., et al. 2014. Viability Statistics of GLAS/ICESat Data Acquired Over Tropical Forests. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 7(5): 1658-1664. doi: http://dx.doi.org/10.1109/JSTARS.2013.2273563.

Betbeder, J., et al. 2014. Mapping of Central Africa Forested Wetlands Using Remote Sensing. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 7(2): 531-542. doi: http://dx.doi.org/10.1109/JSTARS.2013.2269733.

Borsa, A. A., et al. 2014. A Range Correction for ICESat and its Potential Impact on Ice-sheet Mass Balance Studies. The Cryosphere 8(2): 345-357. doi: http://dx.doi.org/10.5194/tc-8-345-2014.

Bosch, Wolfgang, Denise Dettmering, and Christian Schwatke. 2014. Multi-Mission Cross-Calibration of Satellite Altimeters: Constructing a Long-Term Data Record for Global and Regional Sea Level Change Studies . Remote Sensing 6(3): 2255-2281. doi: http://dx.doi.org/10.3390/rs6032255.

Chander, S., et al. 2014. Ice Height and Backscattering Coefficient Variability over Greenland Ice Sheets Using SARAL Radar Altimeter. Marine Geodesy. doi: http://dx.doi.org/10.1080/01490419.2014.990590.

Cochran, J. R., et al. 2014. Bathymetric and Oceanic Controls on Abbot Ice Shelf Thickness and Stability. The Cryosphere 8(3): 877-889. doi: http://dx.doi.org/10.5194/tc-8-877-2014.

Csatho, B., et al. 2014. Laser altimetry reveals complex pattern of Greenland Ice Sheet dynamics. PNAS 111(52): 18478-18483. doi: http://dx.doi.org/10.1073/pnas.1411680112.

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