Multiple Cost Functions and Regularization Options for Improved Retrieval of Leaf Chlorophyll Content and LAI through Inversion of the PROSAIL Model
Open Access
- 9 July 2013
- journal article
- research article
- Published by MDPI AG in Remote Sensing
- Vol. 5 (7), 3280-3304
- https://doi.org/10.3390/rs5073280
Abstract
Lookup-table (LUT)-based radiative transfer model inversion is considered a physically-sound and robust method to retrieve biophysical parameters from Earth observation data but regularization strategies are needed to mitigate the drawback of ill-posedness. We systematically evaluated various regularization options to improve leaf chlorophyll content (LCC) and leaf area index (LAI) retrievals over agricultural lands, including the role of (1) cost functions (CFs); (2) added noise; and (3) multiple solutions in LUT-based inversion. Three families of CFs were compared: information measures, M-estimates and minimum contrast methods. We have only selected CFs without additional parameters to be tuned, and thus they can be immediately implemented in processing chains. The coupled leaf/canopy model PROSAIL was inverted against simulated Sentinel-2 imagery at 20 m spatial resolution (8 bands) and validated against field data from the ESA-led SPARC (Barrax, Spain) campaign. For all 18 considered CFs with noise introduction and opting for the mean of multiple best solutions considerably improved retrievals; relative errors can be twice reduced as opposed to those without these regularization options. M-estimates were found most successful, but also data normalization influences the accuracy of the retrievals. Here, best LCC retrievals were obtained using a normalized “L1 -estimate” function with a relative error of 17.6% (r2 : 0.73), while best LAI retrievals were obtained through non-normalized “least-squares estimator” (LSE) with a relative error of 15.3% (r2 : 0.74).This publication has 56 references indexed in Scilit:
- A red-edge spectral index for remote sensing estimation of green LAI over agroecosystemsEuropean Journal of Agronomy, 2013
- Generating global Leaf Area Index from Landsat: Algorithm formulation and demonstrationRemote Sensing of Environment, 2012
- Sentinels for science: Potential of Sentinel-1, -2, and -3 missions for scientific observations of ocean, cryosphere, and landRemote Sensing of Environment, 2012
- A methodological approach for defining spectral indices for assessing tomato nitrogen status and yieldEuropean Journal of Agronomy, 2011
- LAI, fAPAR and fCover CYCLOPES global products derived from VEGETATION: Part 1: Principles of the algorithmRemote Sensing of Environment, 2007
- A review on reflective remote sensing and data assimilation techniques for enhanced agroecosystem modelingInternational Journal of Applied Earth Observation and Geoinformation, 2007
- The MERIS terrestrial chlorophyll indexInternational Journal of Remote Sensing, 2004
- Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS dataRemote Sensing of Environment, 2002
- Detection of Vegetation Stress Via a New High Resolution Fluorescence Imaging SystemJournal of Plant Physiology, 1996
- [34] Chlorophylls and carotenoids: Pigments of photosynthetic biomembranesPublished by Elsevier BV ,1987