Forest understory may be strongly affected by silvicultural practices such as thinning, which simultaneously modulates the overstory canopy cover and influences the availability of light. However, the understory layer is rarely considered in management decisions, partly because methods to estimate understory leaf area index are poorly developed. In this study we used two different restricted view angle photographic methods to estimate overstory plant area index L<inf>O</inf> (zenith cover photography), understory leaf area index L<inf>U</inf> (nadir cover photography) and their related canopy attributes (foliage clumping, foliage cover, crown cover, crown porosity). These measurements were performed in beech stands under different management regime. Results from photography indicated that not only overstory but also understory canopy attributes were significantly influenced by forest management. In addition, a significant negative correlation was found between L<inf>O</inf> and L<inf>U</inf>. We conclude that the photographic methods are effective for monitoring (overstory and understory) canopy status in managed stands, on account of their rapid and not destructive procedures, which allows large scale implementation of the methods. © 2014 Estonian University of Life Sciences. All rights reserved.

Accurate estimates of forest canopy are essential for the characterization of forest ecosystems. Remotely-sensed techniques provide a unique way to obtain estimates over spatially extensive areas, but their application is limited by the spectral and temporal resolution available from these systems, which is often not suited to meet regional or local objectives. The use of unmanned aerial vehicles (UAV) as remote sensing platforms has recently gained increasing attention, but their applications in forestry are still at an experimental stage. In this study we described a methodology to obtain rapid and reliable estimates of forest canopy from a small UAV equipped with a commercial RGB camera. The red, green and blue digital numbers were converted to the green leaf algorithm (GLA) and to the CIE L^*a^*b^* colour space to obtain estimates of canopy cover, foliage clumping and leaf area index (L) from aerial images. Canopy attributes were compared with in situ estimates obtained from two digital canopy photographic techniques (cover and fisheye photography). The method was tested in beech forests. UAV images accurately quantified canopy cover even in very dense stand conditions, despite a tendency to not detecting small within-crown gaps in aerial images, leading to a measurement of a quantity much closer to crown cover estimated from in situ cover photography. Estimates of L from UAV images significantly agreed with that obtained from fisheye images, but the accuracy of UAV estimates is influenced by the appropriate assumption of leaf angle distribution. We concluded that true colour UAV images can be effectively used to obtain rapid, cheap and meaningful estimates of forest canopy attributes at medium-large scales. UAV can combine the advantage of high resolution imagery with quick turnaround series, being therefore suitable for routine forest stand monitoring and real-time applications. © 2015 Elsevier B.V.

Fast and accurate estimates of canopy cover are central for a wide range of forestry studies. As direct measurements are impractical, indirect optical methods have often been used in forestry to estimate canopy cover. In this paper the accuracy of canopy cover estimates from two widely used canopy photographic methods, hemispherical photography (DHP) and cover photography (DCP) was evaluated. Canopy cover was approximated in DHP as the complement of gap fraction data at narrow viewing zenith angle range (0°–15°), which was comparable with that of DCP. The methodology was tested using artificial images with known canopy cover; this allowed exploring the influence of actual canopy cover and mean gap size on canopy cover estimation from photography. DCP provided robust estimates of canopy cover, whose accuracy was not influenced by variation in actual canopy cover and mean gap size, based on comparison with artificial images; by contrast, the accuracy of cover estimates from DHP was influenced by both actual canopy cover and mean gap size, because of the lower ability of DHP to detect small gaps within crown. The results were replicated in both DHP and DCP images collected in real forest canopies. Finally, the influence of canopy cover on foliage clumping index and leaf area index was evaluated using a theoretical gap fraction model. The main findings indicate that DCP can overcome the limits of indirect techniques for obtaining unbiased and precise estimates of canopy cover, which are comparable to those obtainable from direct, more labour-intensive techniques, being therefore highly suitable for routine monitoring and inventory purposes. © 2016, Silva Fennica. All rights reserved.

Rapid, reliable and meaningful estimates of forest canopy are essential to the characterization of forest ecosystems. In this paper the accuracy of digital hemispherical (DHP) and cover (DCP) photography for the estimation of canopy properties in deciduous forests was evaluated. Leaf area index (LAI) estimated from both these photographic methods and from light transmittance data derived from DHP were compared with direct measurements obtained by litter traps (LAI<inf>LT</inf>) and an AccuPAR ceptometer. Also, comparison with different gap fraction methods used to calculate LAI in DHP and LAI-2000 PCA were performed.We applied these methods in four forest stands of Quercus cerris, two stands of Castanea sativa and four stands of Fagus sylvatica, the most common deciduous species in Italy, where LAI<inf>LT</inf> ranged from 3.9 to 7.3. Both photographic methods provided good indirect estimates of LAI<inf>LT</inf>. The DCP method provided estimates of crown porosity, crown cover, foliage cover and the clumping index at the zenith, but required assumptions about the light extinction coefficient at the zenith (k), to accurately estimate LAI. Cover photography provided good indirect estimates of LAI assuming a spherical leaf angle distribution, even though k appeared to decrease as LAI increased, thus affecting the accuracy of LAI estimates in DCP. In contrast, the accuracy of LAI estimates in DHP appeared insensitive to LAI<inf>LT</inf> values, but the method was sensitive to photographic exposure and more time-consuming than DCP.The studied stands were characterized by higher within-crown clumping than between-crowns clumping; only the segmented analysis of gap fraction for each ring of the fisheye images was found to provide reliable and useful clumping index in DHP. The 1-azimuth segment method employed in PCA poorly detected clumping in dense canopies.The correlation between transmittance estimates by DHP with values measured at noon with the AccuPAR ceptometer was linear and significant, although the variability observed in reference measures suggested that results obtained with the ceptometer should be treated with caution.We conclude both photographic methods are suitable for dense deciduous forests. Cover photography holds great promise as a means to quickly obtain inexpensive estimates of LAI over large areas. However, in situations where no direct reference measurements of . k are available, we recommend using both DHP and DCP, in order to cross-calibrate the two methods; DCP could then be used for more routinely indirect measurement and monitoring of LAI. © 2012 Elsevier B.V.