The purpose of this code is to take a generically formatted csv database of foliar chemistries and spectra, and run PLSR calibrations on those data. While multiple methods of running this analysis are viable using this code (through use of the associated settings file), this is adapted directly from Chadwick, K.D. and G.P. Asner. "Organismic-scale remote sensing of canopy foliar traits in lowland tropical forests." Remote Sensing 8.2 (2016):87. The original code used the autopls package, and was slow to execute. This updated code adapts large portions of that work in a more clearly documented, easier to modify, and faster way. The paper for the autopls package is Schmidtlein, S., H. Feilhauer, and H. Bruelheide. "Mapping plant strategy types using remote sensing." Journal of Vegetation Science 23.3 (2012):395-405. These adaptations were originally performed by Phil Brodrick under CAO research contract to The Rainforest Trust (CIW #10719). Contact P. Brodrick ([email protected]) for code questions. Contact G.P. Asner ([email protected]) or R.E. Martin ([email protected]) for programmatic or applications questions.
More specifically, this code uses crown-based subsets of chemistry and spectra to construct a series of different individual PLSR models, and then aggregates those individual models. The number of latent vectors used within each PLSR model is selected my minimizing a 10-fold average test set RMSE for increasing numbers of vectors (similar, though slightly different, than the A0 mode of the autoPLS package in R).
Code was updated 09/09/2019 to work with Python 3.
Example input and settings files are provided. Input data is expected as a CSV with required columns for: CSP_CODE [a unique identifier for each crown], Band_# [all reflectance data for n bands included] CalVal [indication of the calibration and validation subsets] Chemistry values
Use of this code for any purpose requires citation of the following publication: R.E. Martin, K.D. Chadwick, P.G. Brodrick, L. Carranza-Jimenez, N.R. Vaughn, and G.P. Asner. An approach for foliar trait retrieval from airborne imaging spectroscopy of tropical forests. Remote Sensing, 10(2), 2018. http://www.mdpi.com/2072-4292/10/2/199/htm