Assimilating canopy reflectance data into an ecosystem model with an Ensemble Kalman Filter

[1]  Jean-Luc Widlowski,et al.  Third Radiation Transfer Model Intercomparison (RAMI) exercise: Documenting progress in canopy reflectance models , 2007 .

[2]  Dirk Pflugmacher,et al.  Numerical Terradynamic Simulation Group 7-2006 MODIS land cover and LAI Collection 4 product quality across nine sites in the western hemisphere , 2018 .

[3]  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.

[4]  Will Steffen,et al.  Establishing A Earth Observation Product Service For The Terrestrial Carbon Community: The Globcarbon Initiative , 2006 .

[5]  Xiangming Xiao,et al.  Spatial analysis of growing season length control over net ecosystem exchange , 2005 .

[6]  R. Giering,et al.  Two decades of terrestrial carbon fluxes from a carbon cycle data assimilation system (CCDAS) , 2005 .

[7]  W. Cohen,et al.  Site‐level evaluation of satellite‐based global terrestrial gross primary production and net primary production monitoring , 2005 .

[8]  Shaun Quegan,et al.  Model–data synthesis in terrestrial carbon observation: methods, data requirements and data uncertainty specifications , 2005 .

[9]  B. Law,et al.  An improved analysis of forest carbon dynamics using data assimilation , 2005 .

[10]  D. Roya,et al.  Prototyping a global algorithm for systematic fire-affected area mapping using MODIS time series data , 2005 .

[11]  M. R. R A U Pa C H,et al.  Model – data synthesis in terrestrial carbon observation : methods , data requirements and data uncertainty specifications , 2005 .

[12]  Beverly E. Law,et al.  Climatic versus biotic constraints on carbon and water fluxes in seasonally drought‐affected ponderosa pine ecosystems , 2004 .

[13]  C. D. Keeling,et al.  Seasonal and long‐term dynamics of the upper ocean carbon cycle at Station ALOHA near Hawaii , 2004 .

[14]  B. Law,et al.  Age-related changes in ecosystem structure and function and effects on water and carbon exchange in ponderosa pine. , 2004, Tree physiology.

[15]  B. Law,et al.  Forest Attributes from Radar Interferometric Structure and Its Fusion with Optical Remote Sensing , 2004 .

[16]  Lu Su,et al.  Radiation Transfer Model Intercomparison (RAMI) exercise: Results from the second phase , 2004 .

[17]  Wolfgang Lucht,et al.  Comparative evaluation of seasonal patterns in long time series of satellite image data and simulations of a global vegetation model , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[18]  B. Duchemin,et al.  VEGETATION/SPOT: an operational mission for the Earth monitoring; presentation of new standard products , 2004 .

[19]  John C. Lin,et al.  Toward constraining regional‐scale fluxes of CO2 with atmospheric observations over a continent: 1. Observed spatial variability from airborne platforms , 2003 .

[20]  John C. Lin,et al.  Toward constraining regional‐scale fluxes of CO2 with atmospheric observations over a continent: 2. Analysis of COBRA data using a receptor‐oriented framework , 2003 .

[21]  Kenneth J. Davis,et al.  The annual cycles of CO2 and H2O exchange over a northern mixed forest as observed from a very tall tower , 2003 .

[22]  Geir Evensen,et al.  The Ensemble Kalman Filter: theoretical formulation and practical implementation , 2003 .

[23]  William K. Lauenroth,et al.  Models in Ecosystem Science , 2003, Models in Ecosystem Science.

[24]  E. Rastetter,et al.  Using Mechanistic Models to Scale Ecological Processes across Space and Time , 2003 .

[25]  R. O N A L,et al.  The annual cycles of CO 2 and H 2 O exchange over a northern mixed forest as observed from a very tall tower , 2003 .

[26]  B. Law,et al.  Contrasting soil respiration in young and old‐growth ponderosa pine forests , 2002 .

[27]  C. Justice,et al.  Atmospheric correction of MODIS data in the visible to middle infrared: first results , 2002 .

[28]  D. Roy,et al.  Achieving sub-pixel geolocation accuracy in support of MODIS land science , 2002 .

[29]  D. Roy,et al.  An overview of MODIS Land data processing and product status , 2002 .

[30]  Dennis D. Baldocchi,et al.  Seasonal differences in carbon and water vapor exchange in young and old-growth ponderosa pine ecosystems , 2002 .

[31]  B. Law,et al.  Water limitations to carbon exchange in old-growth and young ponderosa pine stands. , 2002, Tree physiology.

[32]  J. Houghton,et al.  Climate change 2001 : the scientific basis , 2001 .

[33]  J. Canadell,et al.  Recent patterns and mechanisms of carbon exchange by terrestrial ecosystems , 2001, Nature.

[34]  B. Law,et al.  Carbon storage and fluxes in ponderosa pine forests at different developmental stages , 2001 .

[35]  M. S. Moran,et al.  Coupling a grassland ecosystem model with Landsat imagery for a 10-year simulation of carbon and water budgets , 2001 .

[36]  Nadine Gobron,et al.  Radiation transfer model intercomparison (RAMI) exercise , 2001 .

[37]  D. Baldocchi,et al.  Estimation of leaf area index in open-canopy ponderosa pine forests at different successional stages and management regimes in Oregon , 2001 .

[38]  B. Law,et al.  Use of a simulation model and ecosystem flux data to examine carbon-water interactions in ponderosa pine. , 2001, Tree physiology.

[39]  W Ogana,et al.  Contribution of Working Group 1 to the Third Assessment Report of the Intergovernmental Panel on Climate Change , 2001 .

[40]  Ü. Rannik,et al.  Respiration as the main determinant of carbon balance in European forests , 2000, Nature.

[41]  X. Lee,et al.  Nocturnal mixing in a forest subcanopy , 2000 .

[42]  Yu Zhang,et al.  Prototyping of MODIS LAI and FPAR algorithm with LASUR and LANDSAT data , 2000, IEEE Trans. Geosci. Remote. Sens..

[43]  S. Running,et al.  Global Terrestrial Gross and Net Primary Productivity from the Earth Observing System , 2000 .

[44]  R. B. Jackson,et al.  Methods in Ecosystem Science , 2000, Springer New York.

[45]  R. Myneni,et al.  Investigation of a model inversion technique to estimate canopy biophysical variables from spectral and directional reflectance data , 2000 .

[46]  K. Hibbard,et al.  A Global Terrestrial Monitoring Network Integrating Tower Fluxes, Flask Sampling, Ecosystem Modeling and EOS Satellite Data , 1999 .

[47]  Alan H. Strahler,et al.  An analytical hybrid GORT model for bidirectional reflectance over discontinuous plant canopies , 1999, IEEE Trans. Geosci. Remote. Sens..

[48]  Michael G. Ryan,et al.  Seasonal and annual respiration of a ponderosa pine ecosystem , 1999 .

[49]  S. Running,et al.  Synergistic algorithm for estimating vegetation canopy leaf area index and fraction of absorbed photosynthetically active , 1998 .

[50]  W. Knorr.  Constraining a global mechanistic vegetation model with satellite data , 1998, IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174).

[51]  E. Rastetter,et al.  PREDICTING GROSS PRIMARY PRODUCTIVITY IN TERRESTRIAL ECOSYSTEMS , 1997 .

[52]  C. Justice,et al.  Atmospheric correction of visible to middle-infrared EOS-MODIS data over land surfaces: Background, operational algorithm and validation , 1997 .

[53]  Dean Vickers,et al.  Quality Control and Flux Sampling Problems for Tower and Aircraft Data , 1997 .

[54]  N. Gobron,et al.  A semidiscrete model for the scattering of light by vegetation , 1997 .

[55]  S. Wofsy,et al.  Modelling the soil-plant-atmosphere continuum in a Quercus-Acer stand at Harvard Forest : the regulation of stomatal conductance by light, nitrogen and soil/plant hydraulic properties , 1996 .

[56]  A. Strahler,et al.  On the derivation of kernels for kernel‐driven models of bidirectional reflectance , 1995 .

[57]  A. Kuusk.  A fast, invertible canopy reflectance model , 1995 .

[58]  Alan H. Strahler,et al.  A hybrid geometric optical-radiative transfer approach for modeling albedo and directional reflectance of discontinuous canopies , 1995, IEEE Transactions on Geoscience and Remote Sensing.

[59]  G. Müller,et al.  The Scientific Basis , 1995 .

[60]  Richard H. Waring,et al.  Combining Remote Sensing and Climatic Data to Estimate Net Primary Production Across Oregon , 1994 .

[61]  G. Evensen.  Sequential data assimilation with a nonlinear quasi‐geostrophic model using Monte Carlo methods to forecast error statistics , 1994 .

[62]  Alan H. Strahler,et al.  Remote Estimation of Crown Size, Stand Density, and Biomass on the Oregon Transect , 1994 .

[63]  Alan H. Strahler,et al.  Modeling bidirectional radiance measurements collected by the advanced Solid-State Array Spectroradiometer (ASAS) over oregon transect conifer forests☆ , 1994 .

[64]  J. Randerson,et al.  Terrestrial ecosystem production: A process model based on global satellite and surface data , 1993 .

[65]  Alan H. Strahler,et al.  Geometric-optical bidirectional reflectance modeling of the discrete crown vegetation canopy: effect of crown shape and mutual shadowing , 1992, IEEE Trans. Geosci. Remote. Sens..

[66]  F. Baret,et al.  PROSPECT: A model of leaf optical properties spectra , 1990 .

[67]  J. C. Price.  Using spatial context in satellite data to infer regional scale evapotranspiration , 1990 .

[68]  A. Granier,et al.  Evaluation of transpiration in a Douglas-fir stand by means of sap flow measurements. , 1987, Tree physiology.

[69]  Bernard J. Cosby,et al.  Dissolved Oxygen Dynamics of a Stream: Model Discrimination and Estimation of Parameter Variability Using an Extended Kalman Filter , 1984 .

[70]  W. Verhoef.  Light scattering by leaf layers with application to canopy reflectance modelling: The SAIL model , 1984 .

[71]  W. Verhoef.  Light scattering by leaf layers with application to canopy reflectance modeling: The Scattering by Arbitrarily Inclined Leaves (SAIL) model , 1984 .