Scaling and assessment of GPP from MODIS using a combination of airborne lidar and eddy covariance measurements over jack pine forests

Abstract Understanding the influence of within-pixel land cover heterogeneity is essential for the extrapolation of measured and modeled CO 2 fluxes from the canopy to regional scales using remote sensing. Airborne light detection and ranging (lidar) was used to estimate spatial and temporal variations of gross primary production (GPP) across a jack pine chronosequence of four sites in Saskatchewan, Canada for comparison with the Moderate Resolution Imaging Spectroradiometer (MODIS) GPP product. This study utilizes high resolution canopy structural information obtained from airborne lidar to bridge gaps in spatial representation between plot, eddy covariance (EC), and MODIS estimates of vegetation GPP. First we investigate linkages between canopy structure obtained from measurements and light response curves at a jack pine chronosequence during the growing season of 2004. Second, we use the measured canopy height and foliage cover inputs to create a structure-based GPP model (GPP Landsberg ) which was tested in 2005. The GPP model is then run using lidar data (GPP Lidar ) and compared with eight-day cumulative MODIS GPP (GPP MODIS ) and EC observations (GPP EC ). Finally, we apply the lidar GPP model at spatial resolutions of 1 m to 1000 m to examine the influence of within-pixel heterogeneity and scaling (or pixel aggregation) on GPP Lidar . When compared over eight-day cumulative periods throughout the 2005 growing season, the standard deviation of differences between GPP lidar and GPP MODIS were less than differences between either of them and GPP EC at all sites. As might be expected, the differences between pixel aggregated GPP estimates are most pronounced at sites with the highest levels of spatial canopy heterogeneity. The results of this study demonstrate one method for using lidar to scale between eddy covariance flux towers and coarse resolution remote sensing pixels using a structure-based Landsberg light curve model.

[1]  K. Itten,et al.  Estimation of LAI and fractional cover from small footprint airborne laser scanning data based on gap fraction , 2006 .

[2]  J. Hyyppä,et al.  Automatic detection of harvested trees and determination of forest growth using airborne laser scanning , 2004 .

[3]  Donald E. Myers,et al.  Spatial interpolation: an overview , 1994 .

[4]  Lawrence B. Flanagan,et al.  The Fluxnet-Canada Research Network: Influence of climate and disturbance on carbon cycling in forests and peatlands , 2006 .

[5]  W. J. Massmana,et al.  Eddy covariance flux corrections and uncertainties in long-term studies of carbon and energy exchanges , 2002 .

[6]  A. Kuusk,et al.  Impact of understory vegetation on forest canopy reflectance and remotely sensed LAI estimates , 2006 .

[7]  D. Hollinger,et al.  Refining light-use efficiency calculations for a deciduous forest canopy using simultaneous tower-based carbon flux and radiometric measurements , 2007 .

[8]  E. Middleton,et al.  Seasonal variability in foliar characteristics and physiology for boreal forest species at the five Saskatchewan tower sites during the 1994 Boreal Ecosystem‐Atmosphere Study , 1997 .

[9]  Erik Næsset,et al.  Mapping defoliation during a severe insect attack on Scots pine using airborne laser scanning , 2006 .

[10]  J. Chen,et al.  Spatial scaling between leaf area index maps of different resolutions. , 2007, Journal of environmental management.

[11]  Nathan Phillips,et al.  Biophysical controls of carbon flows in three successional Douglas-fir stands based on eddy-covariance measurements. , 2002, Tree physiology.

[12]  John S. Kimball,et al.  Sensitivity of boreal forest regional water flux and net primary production simulations to sub‐grid‐scale land cover complexity , 1999 .

[13]  Dar A. Roberts,et al.  Modeling spatially distributed ecosystem flux of boreal forest using hyperspectral indices from AVIRIS imagery , 2001 .

[14]  E. Næsset,et al.  Estimating tree heights and number of stems in young forest stands using airborne laser scanner data , 2001 .

[15]  T. A. Black,et al.  Photosynthetic light use efficiency of three biomes across an east–west continental-scale transect in Canada , 2006 .

[16]  W. Cohen,et al.  Evaluation of MODIS NPP and GPP products across multiple biomes. , 2006 .

[17]  Oliver Sonnentag,et al.  Leaf area index measurements at Fluxnet-Canada forest sites , 2006 .

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

[19]  D. Baldocchi,et al.  Seasonal variation of carbon dioxide exchange rates above and below a boreal jack pine forest , 1997 .

[20]  C. Woodcock,et al.  Multiscale analysis and validation of the MODIS LAI product: II. Sampling strategy , 2002 .

[21]  P. Treitz,et al.  Investigating light-use efficiency across a jack pine chronosequence during dry and wet years. , 2008, Tree physiology.

[22]  J. Colby,et al.  Spatial Characterization, Resolution, and Volumetric Change of Coastal Dunes using Airborne LIDAR: Cape Hatteras, North Carolina , 2002 .

[23]  D. Turner,et al.  Integrating Remote Sensing and Ecosystem Process Models for Landscape- to Regional-Scale Analysis of the Carbon Cycle , 2004 .

[24]  Laura Chasmer,et al.  USING DISCRETE LASER PULSE RETURN INTENSITY TO MODEL CANOPY TRANSMITTANCE , 2007 .

[25]  Lars Eklundh,et al.  Net primary production and light use efficiency in a mixed coniferous forest in Sweden , 2005 .

[26]  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.

[27]  A. G. Barr,et al.  Response of Net Ecosystem Productivity of Three Boreal Forest Stands to Drought , 2005, Ecosystems.

[28]  R. Nemani,et al.  MODIS DAILY PHOTOSYNTHESIS (PSN) AND ANNUAL NET PRIMARY PRODUCTION (NPP) PRODUCT (MOD17) Algorithm Theoretical Basis Document , 1999 .

[29]  Maosheng Zhao,et al.  Improvements of the MODIS terrestrial gross and net primary production global data set , 2005 .

[30]  Laura Chasmer,et al.  Vegetation class dependent errors in lidar ground elevation and canopy height estimates in a boreal wetland environment , 2005 .

[31]  Peter E. Thornton,et al.  Modeling and measuring the effects of disturbance history and climate on carbon and water budgets in evergreen needleleaf forests , 2002 .

[32]  T. Andrew Black,et al.  Comparison of regional carbon flux estimates from CO2 concentration measurements and remote sensing based footprint integration , 2008 .

[33]  Dennis D. Baldocchi,et al.  On using eco-physiological, micrometeorological and biogeochemical theory to evaluate carbon dioxide, water vapor and trace gas fluxes over vegetation: a perspective , 1998 .

[34]  K. Omasa,et al.  3D lidar imaging for detecting and understanding plant responses and canopy structure. , 2006, Journal of experimental botany.

[35]  Natascha Kljun,et al.  Influences of vegetation structure and elevation on CO2 uptake in a mature jack pine forest in Saskatchewan, Canada , 2008 .

[36]  Warren B. Cohen,et al.  Multiscale Assessment of Binary and Continuous Landcover Variables for MODIS Validation, Mapping, and Modeling Applications , 1999 .

[37]  Abel Rodrigues,et al.  Net ecosystem carbon exchange in three contrasting Mediterranean ecosystems ? the effect of drought , 2007 .

[38]  Ronald J. Hall,et al.  The uncertainty in conifer plantation growth prediction from multi-temporal lidar datasets , 2008 .

[39]  T. Dawson,et al.  Quantifying forest above ground carbon content using LiDAR remote sensing , 2004 .

[40]  C. Woodcock,et al.  Multiscale analysis and validation of the MODIS LAI product: I. Uncertainty assessment , 2002 .

[41]  S. Rymph.  MODELING GROWTH AND COMPOSITION OF PERENNIAL TROPICAL FORAGE GRASSES , 2004 .

[42]  H. Fowells.  Silvics of forest trees of the United States. , 1965 .

[43]  R. Waring,et al.  A generalised model of forest productivity using simplified concepts of radiation-use efficiency, carbon balance and partitioning , 1997 .

[44]  Valerie A. Thomas,et al.  Spatial modelling of the fraction of photosynthetically active radiation absorbed by a boreal mixedwood forest using a lidar–hyperspectral approach , 2006 .

[45]  R. Fernandes,et al.  Effects of subpixel water area fraction on mapping leaf area index and modeling net primary productivity in Canada , 2004 .

[46]  Eric J. Jokela,et al.  Canopy Dynamics, Light Interception, and Radiation Use Efficiency of Selected Loblolly Pine Families , 1998, Forest Science.

[47]  David O'Sullivan,et al.  Geographic Information Analysis , 2002 .

[48]  Warren B. Cohen,et al.  Effects of spatial variability in light use efficiency on satellite-based NPP monitoring , 2002 .

[49]  D. Baldocchi.  ‘Breathing’ of the terrestrial biosphere: lessons learned from a global network of carbon dioxide flux measurement systems , 2008 .

[50]  Nicholas C. Coops,et al.  Comparison of MODIS, eddy covariance determined and physiologically modelled gross primary production (GPP) in a Douglas-fir forest stand , 2007 .

[51]  Laura Chasmer,et al.  Examining the Influence of Changing Laser Pulse Repetition Frequencies on Conifer Forest Canopy Returns , 2006 .

[52]  S. Magnussen,et al.  Derivations of stand heights from airborne laser scanner data with canopy-based quantile estimators , 1998 .

[53]  T. Black,et al.  Inter-annual variability in the leaf area index of a boreal aspen-hazelnut forest in relation to net ecosystem production , 2004 .

[54]  Jing M. Chen,et al.  Determining digital hemispherical photograph exposure for leaf area index estimation , 2005 .

[55]  Paul V. Bolstad,et al.  An approach to spatially distributed modeling of net primary production (NPP) at the landscape scale and its application in validation of EOS NPP products , 1999 .

[56]  C. Hopkinson,et al.  Testing LiDAR models of fractional cover across multiple forest ecozones , 2009 .

[57]  Laura Chasmer,et al.  A lidar-based hierarchical approach for assessing MODIS fPAR , 2008 .

[58]  Sylvain G. Leblanc,et al.  Methodology comparison for canopy structure parameters extraction from digital hemispherical photography in boreal forests , 2005 .

[59]  Alan G. Barr,et al.  Surface energy balance closure by the eddy-covariance method above three boreal forest stands and implications for the measurement of the CO2 flux , 2006 .

[60]  S. T. Gower,et al.  A cross‐biome comparison of daily light use efficiency for gross primary production , 2003 .