Machine learning regression algorithms for biophysical parameter retrieval: Opportunities for Sentinel-2 and -3

By Jochem Verrelst, J. Muñoz, Luis Alonso, Jesús Delegido, Juan Pablo Rivera, Gustau Camps-Valls, José F. Moreno. 2012

515 citations recorded by the source corpus.

Subfields: Ecology, Environmental Engineering, Plant Science

View Paper: https://www.semanticscholar.org/paper/3e3bfbb3f6dbc83b98dc8e3c95c97039ef99837c

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Citations in the corpus

Bayesian object-based estimation of LAI and chlorophyll from a simulated Sentinel-2 top-of-atmosphere radiance image (2014, background): “Further, few studies included the varying pixel size in their simulated Sentinel-2 data (Richter, Wang, Bachmann, & Schläpfer, 2011b), and even fewer investigated the potential of the spatial characteristics of the Sentinel-2 data (Hedley, Roelfsema, Koetz, & Phinn, 2012; Verrelst et al., 2012).”
Green area index from an unmanned aerial system over wheat and rapeseed crops (2014, methodology): “They can use vegetation indices that are transformed intoGAI using a statistical relationship calibrated over experimental measurements (Liu, Pattey, & Jégo, 2012; Verrelst et al., 2012; Viña et al., 2011) or over radiative transfer model simulations (Baret & Guyot, 1991; Haboudane et al.”
Sentinel-2 Data for Land Cover/Use Mapping: A Review (2020, background): “, topographic and surface temperature data), and the results have shown promise [95].”
Hyperspectral characterization of freezing injury and its biochemical impacts in oilseed rape leaves (2017, methodology): “111 Furthermore, SVMs have been used to estimate plant biophysical and biochemical 112 parameters such as LAI, biomass, pigments and nitrogen contents (Gleason & Im, 2012; 113 Verrelst et al., 2012; Yang et al., 2011; Zhai et al., 2013).”
Optical remote sensing and the retrieval of terrestrial vegetation bio-geophysical properties - A review (2015, methodology): “Peng et al. (2011) used KRR for the detection of chlorophyll content using hyperspectral imagery.”
Estimation of biomass in wheat using random forest regression algorithm and remote sensing data (2016, methodology): “The relative RMSE was used to compare performances across different machine-learning algorithms [44].”
Experimental Sentinel-2 LAI estimation using parametric, non-parametric and physical retrieval methods - A comparison (2015, methodology): “Non-parametric algorithms can be split into linear and non-linear regression methods, the latter is also commonly referred to as machine learning regression algorithms (MLRAs) (see Verrelst et al. (2012b)).”