Myneni, Ranga - Boston University - Department of Earth & Environment

近期论文

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Fauchald et al., 2017. Arctic greening from warming promotes declines in caribou populations. Science Advances, 3, e1601365 (2017) Zeng et al., 2017. Climate mitigation from vegetation biophysical feedbacks during the past three decades. Nature Climate Change, doi: 10.1038/NCLIMATE3299 Piao et al., 2017. Weakening temperature control on the interannual variations of spring carbon uptake across northern lands. Nature Climate Change, doi: 10.1038/NCLIMATE3277 Zhu et al., 2017. Attribution of seasonal leaf area index trends in the northern latitudes with “optimally” integrated ecosystem models. Global Change Biol., doi: 10.1111/gcb.13723 Bastos et al., 2017. Was the extreme Northern Hemisphere greening in 2015 predictable? Environ. Res. Lett., doi.org/10.1088/1748-9326/aa67b5 Chen et al., 2017. Prototyping of LAI and FPAR Retrievals from MODIS Multi-Angle Implementation of Atmospheric Correction (MAIAC) Data. Remote Sensing, doi:10.3390/rs9040370 Yang et al., 2017. Estimation of leaf area index and its sunlit portion from DSCOVR EPIC data: Theoretical basis. Remote Sens. Environ., http://dx.doi.org/10.1016/j.rse.2017.05.033 Jiang et al., 2017. Inconsistencies of interannual variability and trends in long-term satellite leaf area index products. Global Change Biology, doi: 10.1111/gcb.13787 Zhu et al., 2016. Greening of the Earth and its Drivers. Nature Climate Change, doi:10.1038/nclimate3004 Mao et al., 2016. Human-induced Greening of the Northern Extratropical Land Surface. Nature Climate Change, doi: 10.1038/nclimate3056 Li et al., 2016. Reducing uncertainties in decadal variability of the global carbon budget with multiple datasets. PNAS, doi: 10.1073/pnas.1603956113 Choi et al., 2016. Application of the metabolic scaling theory and water–energy balance equation to model large-scale patterns of maximum forest canopy height. Global Ecol. Biogeography, doi:10.1111/geb.12503 Park et al., 2016. Changes in growing season duration and productivity of northern vegetation inferred from long-term remote sensing data. Env. Res. Lett., doi:10.1088/1748-9326/11/8/084001 Yan et al., 2016. Evaluation of MODIS LAI/FPAR Product Collection 6. Part 1: Consistency and Improvements, Remote Sensing, doi:10.3390/rs8050359 Yan et al., 2016. Evaluation of MODIS LAI/FPAR Product Collection 6. Part 2: Validation and Intercomparison, Remote Sensing, doi:10.3390/rs8060460 Bi et al., 2016. Amazon Forests’ Response to Droughts: A Perspective from the MAIAC Product, Remote Sensing, doi:10.3390/rs8040356 Yang et al., 2016. Abiotic Controls on Macroscale Variations of Humid Tropical Forest Height, Remote Sensing, doi:10.3390/rs8060494 Yang et al., 2016. Analyses of Impact of Needle Surface Properties on Estimation of Needle Absorption Spectrum: Case Study with Coniferous Needle and Shoot Samples, Remote Sensing, doi:10.3390/rs8070563 Chen et al., 2016. Satellite-observed changes in terrestrial vegetation growth trends across the Asia-Pacific region associated with land cover and climate from 1982 to 2011. Int. J. Digital Earth (doi:10.1080/17538947.2016.1180549) Yan et al., 2016. Assessing spatiotemporal variation of drought in China and its impact on agriculture during 1982-2011 by using PDSI indices and agriculture drought survey data. J. Geophys. Res., (Atmos.), (doi:10.1002/2015JD024285) Yin et al., 2016. Nonlinear variations of forest leaf area index over China during 1982–2010 based on EEMD method. Int J Biometeorol., DOI 10.1007/s00484-016-1277-x Catalano et al., 2016. Observationally based analysis of land–atmosphere coupling. Earth Syst. Dynam. Discuss., Earth Syst. Dynam., 7, 251–266, 2016 (doi:10.5194/esd-7-251-2016) Ukkola et al., 2015. Reduced streamflow in water-stressed climates consistent with CO2 effects on vegetation. Nature Climate Change, 2015 (DOI: 10.1038/NCLIMATE2831) Piao et al., 2015. Leaf onset in the northern hemisphere triggered by daytime temperature. Nature Communications, 2015 (doi: 10.1038/ncomms7911) Anderegg et al., 2015. Tropical nighttime warming as a dominant driver of variability in the terrestrial carbon sink. Proc. Natl. Acad. Sci. USA, 2015 (www.pnas.org/cgi/doi/10.1073/pnas.1521479112)

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近期论文