id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_kamarykukzgkpgdhwn6og5a5yi	Gianluca Filippa	Phenopix: A R package for image-based vegetation phenology	2016.0	29	.pdf	application/pdf	6797	760	56	extract red green and blue digital numbers (DN) from a seasonal series of images; depict greenness index trajectories; fit a curve to the seasonal trajectories; One of the novelties introduced by the package is the spatially explicit, pixel-based analysis, which potentially allows to extract withinecosystem or within-individual variability of phenology. ting/smoothing methods for extracting dates from phenological time-series (i.e. phenophases, see e.g. Zhang et al. phenological thresholds (phenophases) extracted from the average seasonal trajectory of greenness over a region of interest (ROI-averaged approach) and from50 Fit a curve to the GCC seasonal course and extract phenophases135 Table 4: Estimated computation time (hours) required to complete different steps of the pixelbased analysis processing 10000 pixels from a seasonal time series of 5000 images using one We evaluate the relationship between approaches (i.e. ROI-average vs pixelbased) and fitting/phenophase methods across sites in fig. phenophases extracted with two different approaches (pixel-based and ROI-averaged) and	./cache/work_kamarykukzgkpgdhwn6og5a5yi.pdf	./txt/work_kamarykukzgkpgdhwn6og5a5yi.txt