Using Thermal Time and Pixel Purity for Enhancing Biophysical Variable Time Series: An Interproduct Comparison

This paper presents a multiannual comparison at regional scale of currently available 1-km global leaf area index (LAI) products with crop-specific green area index (GAI) retrieved from 250-m spatial resolution imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS). The crop-specific GAI product benefits from the following extra processing steps: 1) spatial filtering of time series based on pixel purity; 2) transforming the time scale to thermal time; and 3) fitting a canopy structural dynamic model to smooth out the signal. In order to perform a rigorous comparison, these steps were also applied to the 1-km LAI products, namely, MODIS LAI (MCD15) and LAI produced in the CYCLOPES (Carbon cYcle and Change in Land Observational Products from an Ensemble of Satellites) project. A simple indicator was also designed to quantify the increase in temporal smoothness that can thus be obtained. The results confirm that, for winter wheat, the 250-m GAI product provides a more realistic description of the time course of the biophysical variable in terms of reaching higher values, grasping the variability, and providing smoother time series. However, the use of thermal time and pixel purity also improves the temporal consistency and coherence of the 1-km products. Overall, the results of this study suggest that these techniques could be valuable in harmonizing remote sensing data coming from different sources with varying spatial and temporal resolution for enhanced vegetation monitoring.

[1]  Sylvain G. Leblanc,et al.  Evaluation of national and global LAI products derived from optical remote sensing instruments over Canada , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[2]  Jean-François Ledent,et al.  Crop specific information extraction based on coarse resolution pixel sampling , 2005 .

[3]  Frédéric Baret,et al.  Contribution au suivi radiométrique de cultures de céréales , 1986 .

[4]  O. Hagolle,et al.  LAI, fAPAR and fCover CYCLOPES global products derived from VEGETATION: Part 1: Principles of the algorithm , 2007 .

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

[6]  Robert E. Wolfe,et al.  An Enhanced TIMESAT Algorithm for Estimating Vegetation Phenology Metrics From MODIS Data , 2011, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[7]  Shunlin Liang,et al.  Integrating MODIS and CYCLOPES Leaf Area Index Products Using Empirical Orthogonal Functions , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[8]  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 .

[9]  D. Diner,et al.  Estimation of vegetation canopy leaf area index and fraction of absorbed photosynthetically active radiation from atmosphere‐corrected MISR data , 1998 .

[10]  Frédéric Baret,et al.  Intercalibration of vegetation indices from different sensor systems , 2003 .

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

[12]  Pierre Gançarski,et al.  A global averaging method for dynamic time warping, with applications to clustering , 2011, Pattern Recognit..

[13]  F. Baret,et al.  LAI and fAPAR CYCLOPES global products derived from VEGETATION. Part 2: validation and comparison with MODIS collection 4 products , 2007 .

[14]  Frédéric Baret,et al.  Modeled analysis of the biophysical nature of spectral shifts and comparison with information content of broad bands , 1992 .

[15]  Rajesh Sharma,et al.  Leaf area index retrieval using IRS LISS-III sensor data and validation of the MODIS LAI product over central India , 2006, IEEE Transactions on Geoscience and Remote Sensing.

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

[17]  Colin G. N. Turnbull,et al.  Plants in Action: adaption in nature, performance in cultivation , 1999 .

[18]  Nadine Gobron,et al.  Theoretical limits to the estimation of the leaf area index on the basis of visible and near-infrared remote sensing data , 1997, IEEE Trans. Geosci. Remote. Sens..

[19]  F. Baret,et al.  Remotely sensed green area index for winter wheat crop monitoring:10-Year assessment at regional scale over a fragmented landscape , 2012 .

[20]  W. Verhoef,et al.  PROSPECT+SAIL models: A review of use for vegetation characterization , 2009 .

[21]  Xinyou Yin,et al.  A nonlinear model for crop development as a function of temperature , 1995 .

[22]  Terry L. Kastens,et al.  Image masking for crop yield forecasting using AVHRR NDVI time series imagery , 2005 .

[23]  W. Wilhelm,et al.  Growing degree-days: one equation, two interpretations , 1997 .

[24]  Michael E. Schaepman,et al.  A review on reflective remote sensing and data assimilation techniques for enhanced agroecosystem modeling , 2007, Int. J. Appl. Earth Obs. Geoinformation.

[25]  P. Jamieson,et al.  Sirius: a mechanistic model of wheat response to environmental variation , 1998 .

[26]  S. Liang,et al.  Validation of MODIS and CYCLOPES LAI products using global field measurement data , 2012 .

[27]  A. Kuusk.  The Hot Spot Effect in Plant Canopy Reflectance , 1991 .

[28]  J. Hill,et al.  Use of coupled canopy structure dynamic and radiative transfer models to estimate biophysical canopy characteristics , 2005 .

[29]  A. Skidmore,et al.  Mapping spatio-temporal variation of grassland quantity and quality using MERIS data and the PROSAIL model , 2012 .

[30]  Robert A. Schowengerdt,et al.  Remote sensing, models, and methods for image processing , 1997 .

[31]  Pierre Defourny,et al.  A conceptual framework to define the spatial resolution requirements for agricultural monitoring using remote sensing , 2010 .

[32]  Y. Knyazikhin,et al.  Validation and intercomparison of global Leaf Area Index products derived from remote sensing data , 2008 .

[33]  F. Baret,et al.  Crop specific green area index retrieval from MODIS data at regional scale by controlling pixel-target adequacy , 2011 .

[34]  Frédéric Baret,et al.  Albedo and LAI estimates from FORMOSAT-2 data for crop monitoring , 2009 .

[35]  Jingfeng Huang,et al.  Evaluation of MODIS surface reflectance products for wheat leaf area index (LAI) retrieval , 2008 .

[36]  Clement Atzberger,et al.  Why confining to vegetation indices? Exploiting the potential of improved spectral observations using radiative transfer models , 2011, Remote Sensing.

[37]  Rasmus Fensholt,et al.  MODIS leaf area index products: from validation to algorithm improvement , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[38]  F. Baret,et al.  Retrieving wheat Green Area Index during the growing season from optical time series measurements based on neural network radiative transfer inversion , 2011 .

[39]  W. Verhoef,et al.  Leaf area index estimation with MODIS reflectance time series and model inversion during full rotations of Eucalyptus plantations , 2011 .

[40]  Jindi Wang,et al.  A Temporally Integrated Inversion Method for Estimating Leaf Area Index From MODIS Data , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[41]  Francis Canisius,et al.  Comparison and evaluation of Medium Resolution Imaging Spectrometer leaf area index products across a range of land use , 2010 .

[42]  P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .

[43]  Berien Elbersen,et al.  Geoland2 - towards an operational GMES Land Monitoring Core Service , 2009 .

[44]  Weikai Yan,et al.  An Equation for Modelling the Temperature Response of Plants using only the Cardinal Temperatures , 1999 .

[45]  S. Running,et al.  Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data , 2002 .

[46]  J. Chen,et al.  Defining leaf area index for non‐flat leaves , 1992 .

[47]  John Angus,et al.  Phasic development in field crops II. Thermal and photoperiodic responses of spring wheat , 1981 .