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CCE



 

Most Recently Published 20 CCE Citations:

Meerdink, S. K., Hook, S. J., Roberts, D. A., Abbott, E. A. 2019. The ECOSTRESS spectral library version 1.0. Remote Sensing of Environment. 230, 111196. doi: 10.1016/j.rse.2019.05.015 ( Roberts (HYSPIRI 2011)  , 1 citations )
Luis, K. M., Rheuban, J. E., Kavanaugh, M. T., Glover, D. M., Wei, J., Lee, Z., Doney, S. C. 2019. Capturing coastal water clarity variability with Landsat 8. Marine Pollution Bulletin. 145, 96-104. doi: 10.1016/j.marpolbul.2019.04.078 ( Wei (SNPP 2013)   )
O'Reilly, J. E., Werdell, P. J. 2019. Chlorophyll algorithms for ocean color sensors - OC4, OC5 & OC6. Remote Sensing of Environment. 229, 32-47. doi: 10.1016/j.rse.2019.04.021 ( Werdell (TASNPP 2017)   )
Thomas, N., Simard, M., Castaneda-Moya, E., Byrd, K., Windham-Myers, L., Bevington, A., Twilley, R. R. 2019. High-resolution mapping of biomass and distribution of marsh and forested wetlands in southeastern coastal Louisiana. International Journal of Applied Earth Observation and Geoinformation. 80, 257-267. doi: 10.1016/j.jag.2019.03.013 ( Windham-Myers (CMS 2014)   )
Boyd, M. A., Berner, L. T., Doak, P., Goetz, S. J., Rogers, B. M., Wagner, D., Walker, X. J., Mack, M. C. 2019. Impacts of climate and insect herbivory on productivity and physiology of trembling aspen (Populus tremuloides) in Alaskan boreal forests. Environmental Research Letters. 14(8), 085010. doi: 10.1088/1748-9326/ab215f ( Goetz (TE 2014)  , 1 citations )
Chen, S., Hu, C., Barnes, B. B., Wanninkhof, R., Cai, W., Barbero, L., Pierrot, D. 2019. A machine learning approach to estimate surface ocean pCO2 from satellite measurements. Remote Sensing of Environment. 228, 203-226. doi: 10.1016/j.rse.2019.04.019 ( Najjar (CARBON 2013)  Najjar (CARBON 2016)  , 1 citations )
Yan, D., Zhang, X., Nagai, S., Yu, Y., Akitsu, T., Nasahara, K. N., Ide, R., Maeda, T. 2019. Evaluating land surface phenology from the Advanced Himawari Imager using observations from MODIS and the Phenological Eyes Network. International Journal of Applied Earth Observation and Geoinformation. 79, 71-83. doi: 10.1016/j.jag.2019.02.011 ( Zhang (SNPP 2013)  Zhang (TASNPP 2017)  , 1 citations )
Bogan, S. A., Antonarakis, A. S., Moorcroft, P. R. 2019. Imaging spectrometry-derived estimates of regional ecosystem composition for the Sierra Nevada, California. Remote Sensing of Environment. 228, 14-30. doi: 10.1016/j.rse.2019.03.031 ( Moorcroft (HYSPIRI 2011)   )
Miller, C. E., Griffith, P. C., Goetz, S. J., Hoy, E. E., Pinto, N., McCubbin, I. B., Thorpe, A. K., Hofton, M., Hodkinson, D., Hansen, C., Woods, J., Larson, E., Kasischke, E. S., Margolis, H. A. 2019. An overview of ABoVE airborne campaign data acquisitions and science opportunities. Environmental Research Letters. 14(8), 080201. doi: 10.1088/1748-9326/ab0d44 ( AAC Management  Goetz (TE 2014)   )
Sedano, F., Lisboa, S. N., Duncanson, L. I., Ribeiro, N., Sitoe, A., Sahajpal, R., Hurtt, G., Tucker, C. 2019. Monitoring forest degradation from charcoal production with historical Landsat imagery. A case study in southern Mozambique. Environmental Research Letters. doi: 10.1088/1748-9326/ab3186 ( Sedano (CMS 2016)   )
Viskari, T., Shiklomanov, A., Dietze, M. C., Serbin, S. P. 2019. The influence of canopy radiation parameter uncertainty on model projections of terrestrial carbon and energy cycling. PLOS ONE. 14(7), e0216512. doi: 10.1371/journal.pone.0216512 ( Serbin (2014)   )
Dashti, H., Glenn, N. F., Ustin, S., Mitchell, J. J., Qi, Y., Ilangakoon, N. T., Flores, A. N., Silvan-Cardenas, J. L., Zhao, K., Spaete, L. P., de Graaff, M. 2019. Empirical Methods for Remote Sensing of Nitrogen in Drylands May Lead to Unreliable Interpretation of Ecosystem Function. IEEE Transactions on Geoscience and Remote Sensing. 57(6), 3993-4004. doi: 10.1109/tgrs.2018.2889318 ( Glenn (TE 2013)  , 1 citations )
Huang, W., Dolan, K. A., Swatantran, A., Johnson, K. D., Tang, H., ONeil-Dunne, J., Dubayah, R., Hurtt, G. 2019. High-resolution mapping of aboveground biomass for forest carbon monitoring system in the Tri-State region of Maryland, Pennsylvania and Delaware, USA. Environmental Research Letters. doi: 10.1088/1748-9326/ab2917 ( Dubayah (CMS 2011)  Dubayah (CMS 2013)  Hurtt (CMS 2014)  Hurtt (CMS 2016)   )
Fu, Z., Stoy, P. C., Poulter, B., Gerken, T., Zhang, Z., Wakbulcho, G., Niu, S. 2019. Maximum carbon uptake rate dominates the interannual variability of global net ecosystem exchange. Global Change Biology. doi: 10.1111/gcb.14731 ( Ott (CMS 2016)   )
Chen, H., McKinley, G. A. 2019. Isopycnal processes allow for summertime heterotrophy despite net oxygen accumulation in the lower-euphotic zone of the western North Atlantic subtropical gyre. Global Biogeochemical Cycles. doi: 10.1029/2018GB006094 ( McKinley (CARBON 2010)   )
Sharma, P., Singh, A., Marinov, I., Kostadinov, T. 2019. Contrasting ENSO Types With Satellite-Derived Ocean Phytoplankton Biomass in the Tropical Pacific. Geophysical Research Letters. doi: 10.1029/2018GL080689 ( Marinov (OBB 2012)   )
Kim, K., Kimball, K., Xu, X., Dunbar, D., Colliander, C., Derksen, D. 2019. Global Assessment of the SMAP Freeze/Thaw Data Record and Regional Applications for Detecting Spring Onset and Frost Events. Remote Sensing. 11(11), 1317. doi: 10.3390/rs11111317 ( Kimball (TE 2014)   )
Signorini, S. R., Mannino, A., Friedrichs, M. A. M., St-Laurent, P., Wilkin, J., Tabatabai, A., Najjar, R. G., Hofmann, E. E., Da, F., Tian, H., Yao, Y. 2019. Estuarine Dissolved Organic Carbon Flux From Space: With Application to Chesapeake and Delaware Bays. Journal of Geophysical Research: Oceans. doi: 10.1029/2018JC014646 ( Friedrichs (IDS 2009)  Najjar (CARBON 2013)  Najjar (IDS 2012)   )
Nathan, L. R., Mamoozadeh, N., Tumas, H. R., Gunselman, S., Klass, K., Metcalfe, A., Edge, C., Waits, L. P., Spruell, P., Lowery, E., Connor, E., Bearlin, A. R., Fortin, M., Landguth, E. 2019. A spatially-explicit, individual-based demogenetic simulation framework for evaluating hybridization dynamics. Ecological Modelling. 401, 40-51. doi: 10.1016/j.ecolmodel.2019.03.002 ( Wenger (ECO4CAST 2012)   )
Patterson, P. L., Healey, S. P., Stahl, G., Saarela, S., Holm, S., Andersen, H., Dubayah, R. O., Duncanson, L., Hancock, S., Armston, J., Kellner, J. R., Cohen, W. B., Yang, Z. 2019. Statistical properties of hybrid estimators proposed for GEDI--NASA's global ecosystem dynamics investigation. Environmental Research Letters. 14(6), 065007. doi: 10.1088/1748-9326/ab18df ( Dubayah (EV 2012)  Healey (CMS 2016)  , 2 citations )  [quad chart]