Sources of uncertainty in gross primary productivity simulated by light use efficiency models: Model structure, parameters, input data, and spatial resolution
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Tong Li | Li Zhang | Wenping Yuan | Yi Zheng | Min Yan | Zhiqiang Zhang | Jingfeng Xiao | Li Zhang | Jingfeng Xiao | W. Yuan | Zhiqiang Zhang | Tong Li | Min Yan | Yi Zheng | J. Xiao
[1] Huadong Guo,et al. Net ecosystem productivity of temperate grasslands in northern China: An upscaling study , 2014 .
[2] T. Vesala,et al. On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm , 2005 .
[3] P. Cox,et al. Impact of changes in diffuse radiation on the global land carbon sink , 2009, Nature.
[4] Wenbo Xu,et al. Modelling gross primary production in the Heihe river basin and uncertainty analysis , 2012 .
[5] F. Woodward,et al. Terrestrial Gross Carbon Dioxide Uptake: Global Distribution and Covariation with Climate , 2010, Science.
[6] Zhuguo Ma,et al. Deriving maximal light use efficiency from coordinated flux measurements and satellite data for regional gross primary production modeling , 2010 .
[7] Mathias Disney,et al. Impact of land cover uncertainties on estimates of biospheric carbon fluxes , 2008 .
[8] Liu Liang-Yu. Simulation and correction of spatialscaling effects for leaf area index , 2014 .
[9] Maosheng Zhao,et al. Improvements of the MODIS terrestrial gross and net primary production global data set , 2005 .
[11] D. Sims,et al. An improved approach for remotely sensing water stress impacts on forest C uptake , 2014, Global change biology.
[12] J. Townshend,et al. A long-term Global LAnd Surface Satellite (GLASS) data-set for environmental studies , 2013 .
[13] Hirofumi Hashimoto,et al. Modeling the interannual variability and trends in gross and net primary productivity of tropical forests from 1982 to 1999 , 2005 .
[14] J. Monteith. SOLAR RADIATION AND PRODUCTIVITY IN TROPICAL ECOSYSTEMS , 1972 .
[15] Huang Huiping. China Land Cover 2000 Using SPOT VGT S10 Data , 2005 .
[16] E. Rastetter,et al. Potential Net Primary Productivity in South America: Application of a Global Model. , 1991, Ecological applications : a publication of the Ecological Society of America.
[17] Nathan M. Urban,et al. Upscaling carbon fluxes from towers to the regional scale: Influence of parameter variability and land cover representation on regional flux estimates , 2011 .
[18] Jindi Wang,et al. Long-Time-Series Global Land Surface Satellite Leaf Area Index Product Derived From MODIS and AVHRR Surface Reflectance , 2016, IEEE Transactions on Geoscience and Remote Sensing.
[19] Jie He,et al. On downward shortwave and longwave radiations over high altitude regions: Observation and modeling in the Tibetan Plateau , 2010 .
[20] Conghe Song,et al. Understanding moisture stress on light use efficiency across terrestrial ecosystems based on global flux and remote‐sensing data , 2015 .
[21] S. Wofsy,et al. Modeling gross primary production of temperate deciduous broadleaf forest using satellite images and climate data , 2004 .
[22] Erxue Chen,et al. A long-term simulation of forest carbon fluxes over the Qilian Mountains , 2016, Int. J. Appl. Earth Obs. Geoinformation.
[23] Jie He,et al. Improving land surface temperature modeling for dry land of China , 2011 .
[24] Jiquan Chen,et al. Energy balance and partition in Inner Mongolia steppe ecosystems with different land use types , 2009 .
[25] Chandra Giri,et al. A comparative analysis of the Global Land Cover 2000 and MODIS land cover data sets , 2005 .
[26] Piero Toscano,et al. Remote sensing of annual terrestrial gross primary productivity from MODIS: an assessment using the FLUXNET La Thuile data set , 2013 .
[27] W. Cohen,et al. Evaluation of MODIS NPP and GPP products across multiple biomes. , 2006 .
[28] Ranga B. Myneni,et al. The impact of gridding artifacts on the local spatial properties of MODIS data : Implications for validation, compositing, and band-to-band registration across resolutions , 2006 .
[29] Mingguo Ma,et al. Validation of MODIS-GPP product at 10 flux sites in northern China , 2013 .
[30] K. Davis,et al. Uncertainty in model parameters and regional carbon fluxes: A model-data fusion approach , 2014 .
[31] Jinwei Dong,et al. Effects of in-situ and reanalysis climate data on estimation of cropland gross primary production using the Vegetation Photosynthesis Model , 2015 .
[32] Shuqing Zhao,et al. Scale criticality in estimating ecosystem carbon dynamics , 2014, Global change biology.
[33] Ramakrishna R. Nemani,et al. Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations , 2006, IEEE Transactions on Geoscience and Remote Sensing.
[34] K. Davis,et al. Global estimates of evapotranspiration and gross primary production based on MODIS and global meteorology data , 2010 .
[35] Min Liu,et al. Large‐scale estimation and uncertainty analysis of gross primary production in Tibetan alpine grasslands , 2014 .
[36] Li Zhang,et al. A Comparison of Satellite-Derived Vegetation Indices for Approximating Gross Primary Productivity of Grasslands , 2014 .
[37] Dailiang Peng,et al. Improved modeling of gross primary production from a better representation of photosynthetic components in vegetation canopy , 2017 .
[38] Steven W. Running,et al. User's Guide Daily GPP and Annual NPP (MOD17A2/A3) Products NASA Earth Observing System MODIS Land Algorithm , 2015 .
[39] Bo Jiang,et al. Retrieval of Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) from VIIRS Time-Series Data , 2016, Remote. Sens..
[40] Qiang Liu,et al. The Global Land Surface Satellite (GLASS) Remote Sensing Data Processing System and Products , 2013, Remote. Sens..
[41] Michele Meroni,et al. Remote sensing-based estimation of gross primary production in a subalpine grassland , 2012 .
[42] Hans Peter Schmid,et al. Footprint modeling for vegetation atmosphere exchange studies: a review and perspective , 2002 .
[43] Damien Sulla-Menashe,et al. MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets , 2010 .
[44] J. Randerson,et al. Terrestrial ecosystem production: A process model based on global satellite and surface data , 1993 .
[45] B. Wylie,et al. Correction to “Upscaling carbon fluxes over the Great Plains grasslands: Sinks and sources” , 2011 .
[46] A. Huete,et al. Overview of the radiometric and biophysical performance of the MODIS vegetation indices , 2002 .
[47] A. Bondeau,et al. Comparing global models of terrestrial net primary productivity (NPP): overview and key results , 1999 .
[48] Dan Liu,et al. Global comparison of light use efficiency models for simulating terrestrial vegetation gross primary production based on the LaThuile database , 2014 .
[49] Stefano Tarantola,et al. Sensitivity analysis of spatial models , 2009, Int. J. Geogr. Inf. Sci..
[50] Maosheng Zhao,et al. Drought-Induced Reduction in Global Terrestrial Net Primary Production from 2000 Through 2009 , 2010, Science.
[51] S. Liang,et al. Improved estimations of gross primary production using satellite‐derived photosynthetically active radiation , 2014 .
[52] Dailiang Peng,et al. Monitoring the distribution of C3 and C4 grasses in a temperate grassland in northern China using moderate resolution imaging spectroradiometer normalized difference vegetation index trajectories , 2012 .
[53] B. Gao. NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space , 1996 .
[54] Ronggao Liu,et al. Characterization and intercomparison of global moderate resolution leaf area index (LAI) products: Analysis of climatologies and theoretical uncertainties , 2013 .
[55] Zhongmin Hu,et al. Comparison of four light use efficiency models for estimating terrestrial gross primary production , 2015 .
[56] Andrew E. Suyker,et al. Uncertainty in simulating gross primary production of cropland ecosystem from satellite-based models , 2015 .
[57] M. Heimann,et al. Comprehensive comparison of gap-filling techniques for eddy covariance net carbon fluxes , 2007 .
[58] Maosheng Zhao,et al. Sensitivity of Moderate Resolution Imaging Spectroradiometer (MODIS) terrestrial primary production to the accuracy of meteorological reanalyses , 2006 .
[59] S. Schubert,et al. MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications , 2011 .
[60] Jin Chen,et al. Global land cover mapping at 30 m resolution: A POK-based operational approach , 2015 .
[61] S. Ollinger,et al. Generalization and evaluation of the process‐based forest ecosystem model PnET‐CN for other biomes , 2015 .
[62] Aaron Moody,et al. Twentieth-Century Droughts and Their Impacts on Terrestrial Carbon Cycling in China , 2009 .
[63] T. Vesala,et al. Deriving a light use efficiency model from eddy covariance flux data for predicting daily gross primary production across biomes , 2007 .
[64] Guangsheng Zhou,et al. Light Use Efficiency over Two Temperate Steppes in Inner Mongolia, China , 2012, PloS one.
[65] Markus Reichstein,et al. Uncertainties of modeling gross primary productivity over Europe: A systematic study on the effects of using different drivers and terrestrial biosphere models , 2007 .
[66] Jonas Ardö,et al. Evaluation of MODIS gross primary productivity for Africa using eddy covariance data , 2013 .
[67] Prasanna H. Gowda,et al. Parameterizing ecosystem light use efficiency and water use efficiency to estimate maize gross primary production and evapotranspiration using MODIS EVI , 2016 .
[68] Yi Zheng,et al. Assimilation of Remotely-Sensed Leaf Area Index into a Dynamic Vegetation Model for Gross Primary Productivity Estimation , 2017, Remote. Sens..
[69] T. Vesala,et al. Advantages of diffuse radiation for terrestrial ecosystem productivity , 2002 .
[70] C. Frantzidis,et al. Response to Reviewers Reviewer #1 , 2010 .
[71] H. Fang,et al. Estimation of direct, diffuse, and total FPARs from Landsat surface reflectance data and ground‐based estimates over six FLUXNET sites , 2015 .
[72] T. Arkebauer,et al. Gross primary production and ecosystem respiration of irrigated maize and irrigated soybean during a growing season , 2005 .
[73] M. B. Beck,et al. Water quality modeling: A review of the analysis of uncertainty , 1987 .
[74] Martin Wild,et al. Solar radiation budgets in atmospheric model intercomparisons from a surface perspective , 2005 .
[75] K. Davis,et al. A multi-site analysis of random error in tower-based measurements of carbon and energy fluxes , 2006 .
[76] Gavin C. Cawley,et al. Efficient leave-one-out cross-validation of kernel fisher discriminant classifiers , 2003, Pattern Recognit..
[77] Mekonnen Gebremichael,et al. Evaluation of MODIS Gross Primary Productivity (GPP) in tropical monsoon regions , 2006 .
[78] Yu Xia,et al. Evaluation of MODIS Gross Primary Production across Multiple Biomes in China Using Eddy Covariance Flux Data , 2016, Remote. Sens..
[79] J. Monteith. Climate and the efficiency of crop production in Britain , 1977 .
[80] Maosheng Zhao,et al. A Continuous Satellite-Derived Measure of Global Terrestrial Primary Production , 2004 .
[81] S. Running,et al. Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data , 2002 .
[82] Stefano Tarantola,et al. Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models , 2004 .