Since the 1960s, canopy photography has been widely used in forestry. Hemispherical photography has been the most widely used technique, but a great drawback of this method is its perceived sensitivity to hemispherical image acquisition and processing. Over the last decade, several alternative photographic approaches using restricted view angle have been proposed. Cover photography acquired via a normal lens was the first of the recently introduced photographic techniques. Use of a restricted view (often fixed) lens has subsequently contributed to the extension of canopy photography to new sensors and platforms, which ultimately have provided answers to some previous challenges regarding within-crown clumping correction, isolated and urban tree measurements, understory assessment, operational leaf inclination angle measurements, and phenological monitoring. This study provides a comprehensive review of the use of canopy photography in forestry and describes the theory and definitions of the variables used to quantify canopy structure. A case study is presented to illustrate and compare the different features and performance of the existing overstory photographic techniques; the results make it possible to suggest sampling strategies for consistent overstory canopy photographic measurements. Emerging operational fields of canopy photography are also described and discussed. © 2020, Canadian Science Publishing. All rights reserved.

Hemispherical photography is a relevant tool to estimate canopy attributes such as leaf area index (LAI). Advancements in digital photography and image processing tools have supported long-lasting use of digital hemispherical photography (DHP). While some open-source tools exists for DHP, very few solutions have been made available in R programming packages, and none of these allows a full processing workflow to retrieve LAI and other canopy attributes from fisheye images. To fill this gap, we developed an R package (hemispheR) to support the whole processing of DHP images in an automated, fast, and reproducible way. The package functions, which are designed for step-by-step single-image analysis, can be performed sequentially in a pipeline, while allowing inspecting the quality of each image processing step. The package allows to analyze both circular and fullframe fisheye images, collected either with upward facing (forest canopies) or downward facing (short canopies and crops) camera orientation. In addition, the package allows to implement two consolidated LAI methods (LAI-2000/2200 and 57° method). A case study is presented to demonstrate the reliability of canopy attributes derived from hemispheR in temperate deciduous forests with variable canopy density and structure. Canopy attributes were validated against either results obtained from a reference proprietary software, either by benchmarking plot-level LAI with measurements obtained from littertraps. Results indicated hemispheR provide reliable openness and leaf area index in forest canopies as compared with reference values. We also found that combining hemispheR with other R packages further advance analysis of hemispherical canopy images, by reducing the sensitivity of results to camera exposure in both raw and non-raw canopy imagery. By providing a simple, transparent, and flexible image processing procedure, hemispheR supported the use of DHP for routine measurements and monitoring of forest canopy attributes. Hosting the package in a Git repository can further support development of the package, through either collaborative coding or forking projects. © 2023 Elsevier B.V.