Multisite analysis of land surface phenology in North American temperate and boreal deciduous forests from Landsat

Ahl, 2006, Monitoring spring canopy phenology of a deciduous broadleaf forest using MODIS, Remote Sens. Environ., 104, 88, 10.1016/j.rse.2006.05.003 Badeck, 2004, Responses of spring phenology to climate change, New Phytol., 162, 295, 10.1111/j.1469-8137.2004.01059.x Bailey, 2016 Barr, 2004, Inter-annual variability in the leaf area index of a boreal aspen-hazelnut forest in relation to net ecosystem production, Agric. For. Meteorol., 126, 237, 10.1016/j.agrformet.2004.06.011 Beaubien, 2000, Spring phenology trends in Alberta, Canada: links to ocean temperature, Int. J. Biometeorol., 44, 53, 10.1007/s004840000050 Beck, 2006, Improved monitoring of vegetation dynamics at very high latitudes: a new method using MODIS NDVI, Remote Sens. Environ., 100, 321, 10.1016/j.rse.2005.10.021 Bennett, 2009, Understanding relationships among multiple ecosystem services, Ecol. Lett., 12, 1394, 10.1111/j.1461-0248.2009.01387.x Betts, 2000, Offset of the potential carbon sink from boreal forestation by decreases in surface albedo, Nature, 408, 187, 10.1038/35041545 Bonan, 2008, Forests and climate change: forcings, feedbacks, and the climate benefits of forests, Science, 320, 1444, 10.1126/science.1155121 Delbart, 2005, Determination of phenological dates in boreal regions using normalized difference water index, Remote Sens. Environ., 97, 26, 10.1016/j.rse.2005.03.011 D'Odorico, 2015, The match and mismatch between photosynthesis and land surface phenology of deciduous forests, Agric. For. Meteorol., 214–215, 25, 10.1016/j.agrformet.2015.07.005 Drolet, 2005, A MODIS-derived photochemical reflectance index to detect inter-annual variations in the photosynthetic light-use efficiency of a boreal deciduous forest, Remote Sens. Environ., 98, 212, 10.1016/j.rse.2005.07.006 Eklundh, 2011, An optical sensor network for vegetation phenology monitoring and satellite data calibration, Sensors, 11, 7678, 10.3390/s110807678 Elmore, 2012, Landscape controls on the timing of spring, autumn, and growing season length in mid-Atlantic forests, Glob. Chang. Biol., 18, 656, 10.1111/j.1365-2486.2011.02521.x Eugster, 2000, Land–atmosphere energy exchange in Arctic tundra and boreal forest: available data and feedbacks to climate, Glob. Chang. Biol., 6, 84, 10.1046/j.1365-2486.2000.06015.x Fisher, 2007, Cross-scalar satellite phenology from ground, Landsat, and MODIS data, Remote Sens. Environ., 109, 261, 10.1016/j.rse.2007.01.004 Friedl, 2014, A tale of two springs: using recent climate anomalies to characterize the sensitivity of temperate forest phenology to climate change, Environ. Res. Lett., 9, 054006, 10.1088/1748-9326/9/5/054006 Fry, 2011, Completion of the 2006 national land cover database for the conterminous United States, Photogramm. Eng. Remote. Sens., 77, 858 Gao, 2006, On the blending of the Landsat and MODIS surface reflectance: predicting daily Landsat surface reflectance, IEEE Trans. Geosci. Remote Sens., 44, 2207, 10.1109/TGRS.2006.872081 Garrity, 2011, A comparison of multiple phenology data sources for estimating seasonal transitions in deciduous forest carbon exchange, Agric. For. Meteorol., 151, 1741, 10.1016/j.agrformet.2011.07.008 Gill, 2015, Changes in autumn senescence in northern hemisphere deciduous trees: a meta-analysis of autumn phenology studies, Ann. Bot., mcv055 Goetz, 2005, Satellite-observed photosynthetic trends across boreal North America associated with climate and fire disturbance, Proc. Natl. Acad. Sci. U. S. A., 102, 13521, 10.1073/pnas.0506179102 Gough, 2008, Multi-year convergence of biometric and meteorological estimates of forest carbon storage, Agric. For. Meteorol., 148, 158, 10.1016/j.agrformet.2007.08.004 Goward, 1991, Normalized difference vegetation index measurements from the advanced very high resolution radiometer, Remote Sens. Environ., 35, 257, 10.1016/0034-4257(91)90017-Z Hmimina, 2013, Evaluation of the potential of MODIS satellite data to predict vegetation phenology in different biomes: An investigation using ground-based NDVI measurements, Remote Sens. Environ., 132, 145, 10.1016/j.rse.2013.01.010 Hogg, 2008, Impacts of a regional drought on the productivity, dieback, and biomass of western Canadian aspen forests, Can. J. For. Res., 38, 1373, 10.1139/X08-001 Huete, 2002, Overview of the radiometric and biophysical performance of the MODIS vegetation indices, Remote Sens. Environ., 83, 195, 10.1016/S0034-4257(02)00096-2 Hufkens, 2012, Linking near-surface and satellite remote sensing measurements of deciduous broadleaf forest phenology, Remote Sens. Environ., 117, 307, 10.1016/j.rse.2011.10.006 Jenkins, 2007, Refining light-use efficiency calculations for a deciduous forest canopy using simultaneous tower-based carbon flux and radiometric measurements, Agric. For. Meteorol., 143, 64, 10.1016/j.agrformet.2006.11.008 Jeong, 2011, Phenology shifts at start vs. end of growing season in temperate vegetation over the Northern Hemisphere for the period 1982–2008, Glob. Chang. Biol., 17, 2385, 10.1111/j.1365-2486.2011.02397.x Jiang, 2008, Development of a two-band enhanced vegetation index without a blue band, Remote Sens. Environ., 112, 3833, 10.1016/j.rse.2008.06.006 Jin, 2014, A physically based vegetation index for improved monitoring of plant phenology, Remote Sens. Environ., 152, 512, 10.1016/j.rse.2014.07.010 Jönsson, 2010, Annual changes in MODIS vegetation indices of Swedish coniferous forests in relation to snow dynamics and tree phenology, Remote Sens. Environ., 114, 2719, 10.1016/j.rse.2010.06.005 Justice, 1985, Analysis of the phenology of global vegetation using meteorological satellite data, Int. J. Remote Sens., 6, 1271, 10.1080/01431168508948281 Keenan, 2014, Tracking forest phenology and seasonal physiology using digital repeat photography: a critical assessment, Ecol. Appl., 24, 1478, 10.1890/13-0652.1 Keenan, 2014, Net carbon uptake has increased through warming-induced changes in temperate forest phenology, Nat. Clim. Chang., 4, 598, 10.1038/nclimate2253 Klosterman, 2014, Evaluating remote sensing of deciduous forest phenology at multiple spatial scales using PhenoCam imagery, Biogeosciences, 11, 4305, 10.5194/bg-11-4305-2014 Krishnan, 2006, Impact of changing soil moisture distribution on net ecosystem productivity of a boreal aspen forest during and following drought, Agric. For. Meteorol., 139, 208, 10.1016/j.agrformet.2006.07.002 Liu, 2016, Improved modeling of land surface phenology using MODIS land surface reflectance and temperature at evergreen needleleaf forests of central North America, Remote Sens. Environ., 176, 152, 10.1016/j.rse.2016.01.021 Masek, 2008, North American forest disturbance mapped from a decadal Landsat record, Remote Sens. Environ., 112, 2914, 10.1016/j.rse.2008.02.010 Melaas, 2013, Detecting interannual variation in deciduous broadleaf forest phenology using Landsat TM/ETM + data, Remote Sens. Environ., 132, 176, 10.1016/j.rse.2013.01.011 Melaas, 2013, Using FLUXNET data to improve models of springtime vegetation activity onset in forest ecosystems, Agric. For. Meteorol., 171–172, 46, 10.1016/j.agrformet.2012.11.018 Myneni, 1995, The interpretation of spectral vegetation indexes, IEEE Trans. Geosci. Remote Sens., 33, 481, 10.1109/TGRS.1995.8746029 Myneni, 1997, Increased plant growth in the northern high latitudes from 1981 to 1991, Nature, 386, 698, 10.1038/386698a0 Myneni, 1998, Interannual variations in satellite-sensed vegetation index data from 1981 to 1991, J. Geophys. Res.-Atmos., 103, 6145, 10.1029/97JD03603 Nijland, 2016, Imaging phenology; scaling from camera plots to landscapes, Remote Sens. Environ., 177, 13, 10.1016/j.rse.2016.02.018 O'Keefe, J. (n.d.). Phenology of Woody Species at Harvard Forest since 1990. Retrieved January 25, 2016, from http://harvardforest.fas.harvard.edu:8080/exist/apps/datasets/showData.html?id=hf003 Pan, 2011, A large and persistent carbon sink in the world's forests, Science, 333, 988, 10.1126/science.1201609 Pudas, 2007, Trends in phenology of Betula pubescens across the boreal zone in Finland, Int. J. Biometeorol., 52, 251, 10.1007/s00484-007-0126-3 Reed, 1994, Measuring phenological variability from satellite imagery, J. Veg. Sci., 5, 703, 10.2307/3235884 Richardson, 2009, Phenological differences between understory and overstory: a case study using the long-term harvard forest records, 87 Richardson, 2006, Phenology of a northern hardwood forest canopy, Glob. Chang. Biol., 12, 1174, 10.1111/j.1365-2486.2006.01164.x Richardson, 2010, Influence of spring and autumn phenological transitions on forest ecosystem productivity, 365, 3227 Richardson, 2007, Use of digital webcam images to track spring green-up in a deciduous broadleaf forest, Oecologia, 152, 323, 10.1007/s00442-006-0657-z Richardson, 2013, Climate change, phenology, and phenological control of vegetation feedbacks to the climate system, Agric. For. Meteorol., 169, 156, 10.1016/j.agrformet.2012.09.012 Riitters, 2002, Fragmentation of continental United States forests, Ecosystems, 5, 0815, 10.1007/s10021-002-0209-2 Schmid, 2000, Measurements of CO2 and energy fluxes over a mixed hardwood forest in the mid-western United States, Agric. For. Meteorol., 103, 357, 10.1016/S0168-1923(00)00140-4 Serbin, 2013, Spatial and temporal validation of the MODIS LAI and FPAR products across a boreal forest wildfire chronosequence, Remote Sens. Environ., 133, 71, 10.1016/j.rse.2013.01.022 Slayback, 2003, Northern hemisphere photosynthetic trends 1982–99, Glob. Chang. Biol., 9, 1, 10.1046/j.1365-2486.2003.00507.x Soja, 2007, Climate-induced boreal forest change: predictions versus current observations, Glob. Planet. Chang., 56, 274, 10.1016/j.gloplacha.2006.07.028 Sonnentag, 2012, Digital repeat photography for phenological research in forest ecosystems, Agric. For. Meteorol., 152, 159, 10.1016/j.agrformet.2011.09.009 Studer, 2007, A comparative study of satellite and ground-based phenology, Int. J. Biometeorol., 51, 405, 10.1007/s00484-006-0080-5 Sulla-Menashe, 2016, Sources of bias and variability in long-term Landsat time series over Canadian boreal forests, Remote Sens. Environ., 177, 206, 10.1016/j.rse.2016.02.041 Urbanski, 2007, Factors controlling CO2 exchange on timescales from hourly to decadal at Harvard Forest, J. Geophys. Res. Biogeosci., 112, 10.1029/2006JG000293 Verma, 2016, Multi-criteria evaluation of the suitability of growth functions for modeling remotely sensed phenology, Ecol. Model., 323, 123, 10.1016/j.ecolmodel.2015.12.005 Vermote, 1997, Atmospheric correction of visible to middle-infrared EOS-MODIS data over land surfaces: Background, operational algorithm and validation, J. Geophys. Res.-Atmos., 102, 17131, 10.1029/97JD00201 White, 2014, Remote sensing of spring phenology in northeastern forests: a comparison of methods, field metrics and sources of uncertainty, Remote Sens. Environ., 148, 97, 10.1016/j.rse.2014.03.017 Wu, 2012, Interannual and spatial impacts of phenological transitions, growing season length, and spring and autumn temperatures on carbon sequestration: a North America flux data synthesis, Glob. Planet. Chang., 92–93, 179, 10.1016/j.gloplacha.2012.05.021 Wulder, 2003, Operational mapping of the land cover of the forested area of Canada with Landsat data: EOSD land cover program, For. Chron., 79, 1075, 10.5558/tfc791075-6 Xu, 2013, Temperature and vegetation seasonality diminishment over northern lands, Nat. Clim. Chang., 3, 581, 10.1038/nclimate1836 Yang, 2014, Beyond leaf color: Comparing camera-based phenological metrics with leaf biochemical, biophysical, and spectral properties throughout the growing season of a temperate deciduous forest, J. Geophys. Res. Biogeosci., 119, 10.1002/2013JG002460 Zhang, 2006, Global vegetation phenology from Moderate Resolution Imaging Spectroradiometer (MODIS): evaluation of global patterns and comparison with in situ measurements, J. Geophys. Res. Biogeosci., 111, 10.1029/2006JG000217 Zhang, 2003, Monitoring vegetation phenology using MODIS, Remote Sens. Environ., 84, 471, 10.1016/S0034-4257(02)00135-9 Zhou, 2003, Relation between interannual variations in satellite measures of northern forest greenness and climate between 1982 and 1999, J. Geophys. Res.-Atmos., 108, 4004, 10.1029/2002JD002510 Zhu, 2012, Object-based cloud and cloud shadow detection in Landsat imagery, Remote Sens. Environ., 118, 83, 10.1016/j.rse.2011.10.028 Zhu, 2014, Continuous change detection and classification of land cover using all available Landsat data, Remote Sens. Environ., 144, 152, 10.1016/j.rse.2014.01.011