Abstract
Upcoming satellite hyperspectral sensors require powerful and robust methodologies for making optimum use of the rich spectral data. This paper reviews the widely applied coupled PROSPECT and SAIL radiative transfer models (PROSAIL), regarding their suitability for the retrieval of biophysical and biochemical variables in the context of agricultural crop monitoring. Evaluation was carried out using a systematic literature review of 281 scientific publications with regard to their (i) spectral exploitation, (ii) vegetation type analyzed, (iii) variables retrieved, and (iv) choice of retrieval methods. From the analysis, current trends were derived, and problems identified and discussed. Our analysis clearly shows that the PROSAIL model is well suited for the analysis of imaging spectrometer data from future satellite missions and that the model should be integrated in appropriate software tools that are being developed in this context for agricultural applications. The review supports the decision of potential users to employ PROSAIL for their specific data analysis and provides guidelines for choosing between the diverse retrieval techniques.
Highlights
For the retrieval of vegetation biophysical and biochemical properties, most studies traditionally proposed empirical relationships between the variables and optical data [1,2,3]
Methods to derive canopy characteristics from optical remotely sensed data [4,77]; assimilation techniques for agroecosystem modeling [106]; Earth Observation (E.O.) products for operational irrigation management [107]; reviews of thirteen special issue papers that focused on novel approaches for exploiting current and future advancements in remote sensor technologies [108]; the first PROSPECT and Scattering by Arbitrary Inclined Leaves (SAIL) radiative transfer models (PROSAIL) review paper [20]; the estimation of canopy water content from spectroscopy [109]; the first review paper about terrestrial imaging spectroscopy and potential applications [29]
Look-up table based model inversion schemes were applied by 25% of all retrieval studies
Summary
For the retrieval of vegetation biophysical and biochemical properties, most studies traditionally proposed empirical relationships between the variables and optical data [1,2,3]. Not all relevant spectral information for the specific target application might be exploited when using only parts of the spectral data cube for modeling This is the case for VIs mostly only using two or three bands concurrently and limiting the estimation of variables that exhibit certain levels of nonlinearity with reflectance measurements, such as leaf area index (LAI) or chlorophyll content [4,5,6]. GeoEye sensors), and temporal domains (e.g., from the Copernicus mission) Due to this growing interest, the PROSAIL model requires a new evaluation in terms of accuracy and possibilities of application. All these issues are disputed focusing on the performance of the model and retrievals regarding current trends and existing problems.
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