Comparison of four different programs for the analysis of hemispherical photographs using parameters of canopy structure and solar radiation transmittance

There have been many studies involving the use of hemispherical photographs to indirectly estimate canopy structures and forest light environments. A variety of commercial and free software packages are available for the analysis of hemispherical photographs. The costs of investment might represent an advantage of the free programmes over the commercial, but as yet little has been documented about the differences in their outputs and in the technical applications from a user (ecologist and forester) perspective. The objective of the study was to compare the canopy structure variables (canopy openness and effective plant area index) and solar radiation transmission estimates (direct, diffuse and global solar radiation transmittances) from digital hemispherical photographs taken under two forest canopy conditions (gap and closed canopy) in three different broadleaf forest regions (Chile, Germany, Venezuela) and calculated using four different programmes. The hemispherical photographs were analysed using one commercial (HemiView) and three free programmes (Gap Light Analyzer, hemIMAGE and Winphot). The results obtained revealed that all of the programmes computed similar estimates of both canopy structures and below-canopy solar radiation. Only the results relating to the effective plant area index with an ellipsoidal leaf angle distribution made with HemiView and Winphot deviated significantly. Other user aspects are also discussed, such as costs, image formats, computer system requirements, etc.In vielen Studien werden Hemisphärenphotos genutzt um indirekt die Kronenstruktur und die Belichtungsverhältnisse zu schätzen. Verschiedene kommerzielle und kostenfreie Softwarepakete sind zu Analyse von Hemisphärenphotos verfügbar. Es gibt bisher keine umfassende Vergleichsstudie zu Ergebnissen oder technischer Handhabung aus Sicht der Nutzer dieser Programme (Ökologen und Forstwissenschaftler). Das Ziel dieser Studie war der Vergleich der Schätzungen von Kronenstrukturvariablen (Kronenöffnung und effektiver Pflanzenflächenindex) Solartransmission (direkte, diffuse und Global-Strahlung) aus digitalen Hemisphärenphotos berechnet mit vier verschiedenen Programmen (kostenpflichtig: Hemi- View und frei: Gap Light Analyzer, hemIMAGE and Winphot). Die verwendeten Photos stammen aus drei verschiedenen Laubwaldregionen (Chile, Deutschland und Venezuela) und repräsentieren jeweils Verhältnisse unter geschlossenem Kronendach und in Lücken. Die ermittelten Schätzungen für die verschiedenen Strukturvariablen und Einstrahlungsverhältnisse zeigten eine sehr hohe Übereinstimmung. Einzig der effektive Pflanzenflächenindex basierend auf ellipsoider Blattwinkelverteilung unterschied sich signifikant zwischen den Programmen. Weitere für Nutzer interessante Aspekte wie Kosten, Bildformate, Systemvoraussetzungen und mehr wurden verglichen und diskutiert

Estimating leaf area index in different types of mature forest stands in Switzerland: a comparison of methods

Leaf area index (LAI) was estimated at 15 sites in the Swiss Long-Term Forest Ecosystem Research Programme (LWF) in 2004-2005 using two indirect techniques: the LAI-2000 plant canopy analyzer (Licor Inc.) and digital hemispherical photography, applying several exposure settings. Hemispherical photographs of the canopy were analysed using Hemisfer, a software package that offers several new features, which were tested here: (1) automatic thresholding taking the gamma value of the picture into account; (2) implementation of several equations to solve the gap-fraction inversion model from which LAI estimates are derived; (3) correction for ground slope effects, and (4) correction for clumped canopies. In seven broadleaved stands in our sample set, LAI was also estimated semi-directly from litterfall. The various equations used to solve the gap-fraction inversion model generated significantly different estimates for the LAI-2000 measurements. In contrast, the same equations applied in Hemisfer did not produce significantly different estimates. The best relationship between the LAI-2000 and the Hemisfer estimates was obtained when the hemispherical photographs were overexposed by one to two stops compared with the exposure setting derived from the reading of a spotmeter in a canopy gap. There was no clear general relationship between the litterfall and the LAI-2000 or the hemispherical photographs estimates. This was probably due to the heterogeneity of the canopy, or to biased litterfall collection at sites on steep slopes or sites subject to strong winds. This study introduces new arguments into the comparison of the advantages and drawbacks of the LAI-2000 and hemispherical photography in terms of applicability and accurac

A comparison of different methods for assessing leaf area index in four canopy types

The agreement of Leaf Area Index (LAI) assessments from three indirect methods, i.e. the LAI–2200 Plant Canopy Analyzer, the SS1 SunScan Canopy Analysis System and Digital Hemispherical Photography (DHP) was evaluated for four canopy types, i.e. a short rotation coppice plantation (SRC) with poplar, a Scots pine stand, a Pedunculate oak stand and amaize field. In the SRC and in the maize field, the indirect measurements were compared with direct measurements (litter fall and harvesting). In the low LAI range (0 to 2) the discrepancies of the SS1 were partly explained by the inability to properly account for clumping and the uncertainty of the ellipsoidal leaf angle distribu tion parameter. The higher values for SS1 in the medium (2 to 6) to high (6 to 8) ranges might be explained by gap fraction saturation for LAI–2200 and DHP above certain values. Wood area index –understood as the woody light blocking elements from the canopy with respect to diameter growth– accounted for overestimation by all indirect methods when compared to direct methods in the SRC. The inter-comparison of the three indirect methods in the four canopy types showed a general agreement for all methods in the medium LAI range (2 to 6). LAI–2200 and DHP revealed the best agreement among the indirect methods along the entire range of LAI (0 to 8) in all canopy types. SS1 showed some discrepancies with the LAI–2200 and DHP at low (0 to 2) and high ranges of LAI (6 to 8

Estimation of leaf area index in eucalypt forest with vertical foliage, using cover and fullframe fisheye photography

This study compared fullframe fisheye photography and cover photography with destructive leaf area index (L) estimation and the Licor LAI-2000 plant canopy analyser (PCA) in plantations of the vertical leaved species Eucalyptus globulus. Fullframe fisheye photography differs from circular fisheye photography in that the images have reduced field of view such that the zenithal range of 0-90° extends to the corners of the rectangular image, roughly doubling image resolution compared to circular images. Cover images instead are obtained by pointing a 70 mm equivalent focal length lens (in 35 mm format) straight upwards. Measurements of cover and indirect estimates of plant area index (Lt) were made in 12 stands of 6-8 years old Eucalyptus globulus. L was measured using destructive sampling and allometry in nine of these stands and ranged from 2.5 to 6.6. Both foliage cover and Lt from the PCA were well correlated with L from allometry, but fullframe fisheye photography provided poor estimates of L despite corrections for foliage clumping. Sampling location had a significant effect on estimates of crown porosity, crown cover and zenithal clumping index from cover photography. The zenithal extinction coefficient (k), calculated from L, crown porosity and cover, ranged from 0.14 to 0.25 and appeared to decrease as L increased; hence, we were unable to obtain an unambiguous estimate of k for E. globulus stands. Nonetheless, the study showed that L can be estimated from foliage cover with similar certainty to that of the PCA. We conclude that the greatest challenge facing indirect estimation of L in forests using photographic methods is to separate the effects of foliage angle from those of foliage clumping. © 2007 Elsevier B.V. All rights reserved

Comparing canopy density measurement from UAV and hemispherical photography: an evaluation for medium resolution of remote sensing-based mapping

UAV and hemispherical photography are common methods used in canopy density measurement. These two methods have opposite viewing angles where hemispherical photography measures canopy density upwardly, while UAV captures images downwardly. This study aims to analyze and compare both methods to be used as the input data for canopy density estimation when linked with a lower spatial resolution of remote sensing data i.e. Landsat image. We correlated the field data of canopy density with vegetation indices (NDVI, MSAVI, and AFRI) from Landsat-8. The canopy density values measured from UAV and hemispherical photography displayed a strong relationship with 0.706 coefficient of correlation. Further results showed that both measurements can be used in canopy density estimation using satellite imagery based on their high correlations with Landsat-based vegetation indices. The highest correlation from downward and upward measurement appeared when linked with NDVI with a correlation of 0.962 and 0.652, respectively. Downward measurement using UAV exhibited a higher relationship compared to hemispherical photography. The strong correlation between UAV data and Landsat data is because both are captured from the vertical direction, and 30 m pixel of Landsat is a downscaled image of the aerial photograph. Moreover, field data collection can be easily conducted by deploying drone to cover inaccessible sample plots

Leaf Area Index Derived From Hemispherical Photograph and Its Correlation with Aboveground Forest Biomass

Leaf area index (LAI) is one of the key physical factors in the energy exchange between terrestrial ecosystem and atmosphere. It determines the photosynthesis process to produce biomass and plays an important role in performing forest stand reflectance. Therefore building relationship between LAI and biomass from field measurements can be used to develop allometric equations for biomass estimation. This paper studies the relationship between diameter at breast height (DBH) and leaves biomass, DBH and crown biomass (sum up of leaves, twigs and branches) as well as between LAI and leaves biomass; LAI and crown biomass; LAI and Total Above-ground Biomass (TAGB) in East Kalimantan Province. Destructive sampling was conducted to develop allometric equations. The DBH measurements from 52 sample plots were used as training data for model development (35 plots) and for validation (17 plots). A hemispherical photograph was used to record LAI. The result shows that strong corelation (r) exists between natural logarithmic (ln) DBH and crown biomass ranging from 0.88 to 0.98. The correlation (r) between LAI and biomass of leaves; leaves + twigs + branches; TAGB were 0.742, 0.768 and 0.772, respectively. Improvement of (r) between LAI and biomass can be conducted by proper time of LAI measurement, when the sky is uniformly overcast

Remote sensing of leaf area index : enhanced retrieval from close-range and remotely sensed optical observations

A wide range of models used in agriculture, ecology, carbon cycling, climate and other related studies require information on the amount of leaf material present in a given environment to correctly represent radiation, heat, momentum, water, and various gas exchanges with the overlying atmosphere or the underlying soil. Leaf area index (LAI) thus often features as a critical land surface variable in parameterisations of global and regional climate models, e.g., radiation uptake, precipitation interception, energy conversion, gas exchange and momentum, as all areas are substantially determined by the vegetation surface. Optical wavelengths of remote sensing are the common electromagnetic regions used for LAI estimations and generally for vegetation studies. The main purpose of this dissertation was to enhance the determination of LAI using close-range remote sensing (hemispherical photography), airborne remote sensing (high resolution colour and colour infrared imagery), and satellite remote sensing (high resolution SPOT 5 HRG imagery) optical observations. The commonly used light extinction models are applied at all levels of optical observations. For the sake of comparative analysis, LAI was further determined using statistical relationships between spectral vegetation index (SVI) and ground based LAI. The study areas of this dissertation focus on two regions, one located in Taita Hills, South-East Kenya characterised by tropical cloud forest and exotic plantations, and the other in Gatineau Park, Southern Quebec, Canada dominated by temperate hardwood forest. The sampling procedure of sky map of gap fraction and size from hemispherical photographs was proven to be one of the most crucial steps in the accurate determination of LAI. LAI and clumping index estimates were significantly affected by the variation of the size of sky segments for given zenith angle ranges. On sloping ground, gap fraction and size distributions present strong upslope/downslope asymmetry of foliage elements, and thus the correction and the sensitivity analysis for both LAI and clumping index computations were demonstrated. Several SVIs can be used for LAI mapping using empirical regression analysis provided that the sensitivities of SVIs at varying ranges of LAI are large enough. Large scale LAI inversion algorithms were demonstrated and were proven to be a considerably efficient alternative approach for LAI mapping. LAI can be estimated nonparametrically from the information contained solely in the remotely sensed dataset given that the upper-end (saturated SVI) value is accurately determined. However, further study is still required to devise a methodology as well as instrumentation to retrieve on-ground green leaf area index . Subsequently, the large scale LAI inversion algorithms presented in this work can be precisely validated. Finally, based on literature review and this dissertation, potential future research prospects and directions were recommended.Ei saatavill

Evaluation of remote sensing methods for continuous cover forestry

The overall aim of the project was to investigate the potential and challenges in the application of high spatial and spectral resolution remote sensing to forest stands in the UK for Continuous Cover Forestry (CCF) purposes. Within the context of CCF, a relatively new forest management strategy that has been implemented in several European countries, the usefulness of digital remote sensing techniques lie in their potential ability to retrieve parameters at sub-stand level and, in particular, in the assessment of natural regeneration and light regimes. The idea behind CCF is the support of a sustainable forest management system reducing disturbance of the forest ecosystem and encouraging the use of more natural methods, e.g. natural regeneration, for which the light environment beneath the forest canopy plays a fundamental role.The study was carried out at a test area in central Scotland, situated within the Queen Elizabeth II Forest Park (lat. 56°10' N, long. 4° 23' W). Six plots containing three different species (Norway spruce, European larch and Sessile oak), characterized by their different light regimes, were established within the area for the measurement of forest variables using a forest inventory approach and hemispherical photography. The remote sensing data available for the study consisted of Landsat ETM+ imagery, a small footprint multi-return lidar dataset over the study area, Airborne Thematic Mapper (ATM) data, and aerial photography with same acquisition date as the lidar data.Landsat ETM+ imagery was used for the spectral characterisation of the species under study and the evaluation of phenological change as a factor to consider for future acquisitions of remotely sensed imagery. Three approaches were used for the discrimination between species: raw data, NDVI, and Principal Component Analysis (PCA). It can be concluded that no single date is ideal for discriminating the species studied (early summer was best) and that a combination of two or three datasets covering their phenological cycles is optimal for the differentiation. Although the approaches used helped to characterize the forest species, especially to the discrimination between spruces, larch and the deciduous oak species, further work is needed in order to define an optimum approach to discriminate between spruce species (e.g. Sitka spruce and Norway spruce) for which spectral responses are very similar. In general, the useful ranges of the indices were small, so a careful and accurate preprocessing of the imagery is highly recommended.Lidar, ATM, and aerial photographic datasets were analysed for the characterisation of vertical and horizontal forest structure. A slope-based algorithm was developed for the extraction of ground elevation and tree heights from multiple return lidar data, the production of a Digital Terrain Model (DTM) and Digital Surface Model (DSM) of the area under study, and for the comparison of the predicted lidar tree heights with the true tree heights, followed by the building of a Digital Canopy Model (DCM) for the determination of percentage canopy cover and tree crown delineation. Mean height and individual tree heights were estimated for all sample plots. The results showed that lidar underestimated tree heights by an average of 1.49 m. The standard deviation of the lidar estimates was 3.58 m and the mean standard error was 0.38 m.This study assessed the utility of an object-oriented approach for deciduous and coniferous crown delineation, based on small-footprint, multiple return lidar data, high resolution ATM imagery, and aerial photography. Special emphasis in the analysis was made in the fusion of aerial photography and lidar data for tree crown detection and classification, as it was expected that the high vertical accuracy of lidar, combined with the high spatial resolution aerial photography would render the best results and would provide the forestry sector with an affordable and accurate means for forest management and planning. Most of the field surveyed trees could be automatically and correctly detected, especially for the spruce and larch plots, but the complexity of the deciduous plots hindered the tree recognition approach, leading to poor crown extent and gap estimations. Indicators of light availability were calculated from the lidar data by calculation of laser hit penetration rates and percentage canopy cover. These results were compared to estimates of canopy openness obtained from hemispherical pictures for the same locations.Finally, the synergistic benefits of all datasets were evaluated and the forest structural variables determined from remote sensing and hemispherical photography were examined as indicators of light availability for regenerating seedlings

Uncrewed aircraft system spherical photography for the vertical characterization of canopy structural traits

The plant area index (PAI) is a structural trait that succinctly parametrizes the foliage distribution of a canopy and is usually estimated using indirect optical techniques such as digital hemispherical photography. Critically, on-the-ground photographic measurements forgo the vertical variation of canopy structure which regulates the local light environment. Hence new approaches are sought for vertical sampling of traits. We present an uncrewed aircraft system (UAS) spherical photographic method to obtain structural traits throughout the depth of tree canopies. Our method explained 89% of the variation in PAI when compared with ground-based hemispherical photography. When comparing UAS vertical trait profiles with airborne laser scanning data, we found highest agreement in an open birch (Betula pendula/pubescens) canopy. Minor disagreement was found in dense spruce (Picea abies) stands, especially in the lower canopy. Our new method enables easy estimation of the vertical dimension of canopy structural traits in previously inaccessible spaces. The method is affordable and safe and therefore readily usable by plant scientists.Peer reviewe

Spatial Relationships between Trees and Snow in a Cold Regions Montane Forest

Vegetation structure is one of the primary factors that drives spatial variation of snow accumulation in forests due to interactions between falling snow, intercepted snow, and the forest canopy. These processes result in spatially heterogeneous snowpacks and snowpack energy fluxes, driving areal snow cover depletion rates during melt periods with repercussions for stand- and basin-scale ablation rates and snowmelt runoff quantities and timings. While spatial variation of forest snowpack has been documented at scales from individual tree branches to forest stands, the underlying processes are not fully understood. Understanding these relationships is critical to understanding the combined effects of climate and vegetation changes on streamflow and ecology in basins with seasonal snowpacks. To better understand these processes, this study examined the spatial relationships between branch-scale canopy structure and subcanopy snow accumulation over two accumulation events in February of 2019, at an instrumented montane forest site in Marmot Creek Research Basin on the eastern slope of the Canadian Rockies. Repeated UAV lidar surveys were paired with manual snow surveys to produce estimates of snowpack snow water equivalent (SWE) and change in snowpack (ΔSWE) over each event at high spatial resolutions. Lidar observations of the forest canopy were combined with contemporary hemispherical photography to produce a diverse set of canopy metrics, including light transmittance metrics from a novel voxel ray sampling method. Results showed that over 75% of the spatial variance in subcanopy ΔSWE for each event was found within 2.0 m of horizontal distance, indicating that the spatial scale of canopy effects on snow interception and redistribution were primarily found at the scale of tree branches in this forest. Significant vertical asymmetry was seen in the relationships between snow accumulation and surrounding vegetation which was explained by prevailing wind directions. A descriptive Gaussian snowfall model that was consistent with the tight coupling observed between near-overhead canopy characteristics and snow accumulation explained more of the spatial variation in observed ΔSWE than any canopy metric considered and performed better than two other forest snow accumulation models based on larger scale canopy characteristics found in the literature. These findings emphasize the importance of representing branch-scale forest heterogeneity in models of snow accumulation and suggest that representation of vertical asymmetry in parametrizations of snow-vegetation relationships may yield more physically realistic models