Estimation of vegetation biophysical parameters in grasslands and crops in Chile through hemispheric digital photography by a GoPro camera - D. Uribe; C. Mattar; F. Camacho (Revista de Teledetección, 2018)
The estimation of the biophysical parameters of vegetation such as LAI (Leaf Area Index), FAPAR (Fraction of Absorbed Photosynthetically Active Radiation) and FCOVER (Fraction of Green Vegetation) have many climatic, hydrologic, ecosystem and silvo-agricultural applications. Despite the various satellite products that estimate these parameters continuously and globally, it’s necessary to continue generating in situ estimations to validate these remote data. It’s in this context where Digital Hemispheric Photography (DHP) technique stands out as being one of the most accurate an adaptable to operate continuously with diverse photographic equipment and field scenarios. The objective of this paper is to estimate effective LAI (LAIeff), true LAI (LAItrue), FAPAR and FCOVER through the DHP method on several agricultural land covers in Chile, between the years 2015 and 2016 using a GoPro camera and the CAN-EYE software to process hemispheric photographs. The results obtained were initially compared with those provided by a CANON EOS 6D camera mounted together with a SIGMA 8mm F3.5-EX DG fisheye lens and subsequently with satellite products provided by the Copernicus Global Land service, derived from PROBA-V mission at 333 m2 spatial resolution. The comparison between the CANON and GoPro shows similar values and R2 over 0,72 for all parameters. The comparison with PROBA-V resulted in values over 0,52 of R2 for the parameters, and similar multitemporal patterns. It’s concluded that it’s possible to estimates LAIeff, FAPAR and FCOVER like other fish eyes cameras. Concerning PROBA-V, except for FAPAR, the estimates with the GoPro do not show much correlation. In both campaigns significant discrepancies were observed in the LAItrue, which could be related to the calculation of CAN-EYE canopy clumping with the characteristics of the camera itself.