bRaw: an R package for digital raw canopy imagery

Abstract

AbstractDigital photography is an increasingly popular tool to estimate forest canopy attributes. However, estimates of gap fraction, upon which calculations of canopy attributes are based, are sensitive to photographic exposure in upward-facing images. Recent studies have indicated that analyzing RAW imagery, rather than other inbuilt camera format (e.g. jpeg, png, tiff) allows to obtain largely-insensitive gap fraction retrieval from digital photography. The package bRaw implemented the method proposed by Macfarlane et al. (2014). They found that shooting raw with one stop of underexposure and applying a linear contrast stretch yielded largely insensitive results, thus providing a way for standardizing and optimizing photographic exposure. The package replicate the methodology and thus it provides an effective tool to use raw imagery in canopy photography.