On the exposure of hemispherical photographs in forests

Beckschäfer, Philip; Seidel, Dominik; Kleinn, Christoph; Xu, Jianchu

doi:10.3832/ifor0957-006

Cited by 85 publications

(87 citation statements)

References 57 publications

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“…Beckschäfer et al [43] found that auto-exposure might overestimate the canopy gap fraction, but for forests with low canopy density, the gap fraction overestimation caused by auto-exposure would be less than 5%. In these experiments, the maximum LAI as measured by LAI-2000 was 3.48 m 2 /m 2 , which can be considered as a low-density canopy most of the time.…”

Section: Discussionmentioning

confidence: 99%

Potential and Limits of Retrieving Conifer Leaf Area Index Using Smartphone-Based Method

Qu¹,

Wang²,

Song³

et al. 2017

Forests

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Forest leaf area index (LAI) is a key characteristic affecting a field canopy microclimate. In addition to traditional professional measuring instruments, smartphone-based methods have been used to measure forest LAI. However, when smartphone methods were used to measure conifer forest LAI, very different performances were obtained depending on whether the smartphone was held at the zenith angle or at a 57.5 • angle. To further validate the potential of smartphone sensors for measuring conifer LAI and to find the limits of this method, this paper reports the results of a comparison of two smartphone methods with an LAI-2000 instrument. It is shown that the method with the smartphone oriented vertically upwards always produced better consistency in magnitude with LAI-2000. The bias of the LAI between the smartphone method and the LAI-2000 instrument was explained with regards to four aspects that can affect LAI: gap fraction; leaf projection ratio; sensor field of view (FOV); and viewing zenith angle (VZA). It was concluded that large FOV and large VZA cause the 57.5 • method to overestimate the gap fraction and hence underestimate conifer LAI. For the vertically upward method, the bias caused by the overestimated gap fraction is compensated for by an underestimated leaf projection ratio.

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Section: Discussionmentioning

confidence: 99%

Potential and Limits of Retrieving Conifer Leaf Area Index Using Smartphone-Based Method

Qu¹,

Wang²,

Song³

et al. 2017

Forests

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“…In the case of eight positions, the images were taken from 3 m and 9 m distance to each cardinal direction. In order to determine the exposure setting, we followed the histogram method of Beckschäfer et al (2013). The image processing included the classification of images to the canopy and sky pixels using the blue band and automatic thresholding algorithm (Nobis and Hunziker, 2005).…”

Section: Field Estimates Of CCmentioning

confidence: 99%

Comparison of field and airborne laser scanning based crown cover estimates across land cover types in Kenya

Heiskanen

Korhonen

Hietanen

et al. 2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Tree crown cover (CC) provides means for the continuous land cover characterization of complex tropical landscapes with multiple land uses and variable degrees of degradation. It is also a key parameter in the international forest definitions that are basis for monitoring global forest cover changes. Recently, airborne laser scanning (ALS) has emerged as a practical method for accurate CC mapping, but ALS derived CC estimates have rarely been assessed with field data in the tropics. Here, our objective was to compare the various field and ALS based CC estimates across multiple land cover types in the Taita Hills, Kenya. The field data was measured from a total of 178 sample plots (0.1 ha) in 2013 and 2014. The most accurate field measurement method, line intersect sampling using Cajanus tube, was used in 37 plots. Other methods included CC estimate based on the tree inventory data (144 plots), crown relascope (43 plots) and hemispherical photography (30 plots). Three ALS data sets, including two scanners and flying heights, were acquired concurrently with the field data collection. According to the results, the first echo cover index (FCI) from ALS data had good agreement with the most accurate field based CC estimates (RMSD 7.1% and 2.7% depending on the area and scan). The agreement with other field based methods was considerably worse. Furthermore, we observed that ALS cover indices were robust between the different scans in the overlapping area. In conclusion, our results suggest that ALS provides a reliable method for continuous CC mapping across tropical land cover types although dense shrub layer and tree-like herbaceous plants can cause overestimation of CC.

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“…For this reason, the effective LAI (Le) has been proposed to describe optically derived LAI estimates in the literature (Chen & Black 1992). Additionally, recent studies reported that an incorrect exposure setting in DHP LAI estimation may be a significant source of error (Chen et al 1991, Cescatti 2007, Chianucci & Cutini 2012, Beckschäfer et al 2013, Song et al 2013 by decreasing the contrast between the sky and foliage, further affecting the calculation of the LAI by DHP. Comparisons of the LAI estimated from DHP and the LAI-2000 techniques with those obtained from direct measurements have often been reported (Dufrêne & Bréda 1995, Chen et al 1997, Thimonier et al 2010, Mason et al 2012, Olivas et al 2013.…”

Section: Introductionmentioning

confidence: 99%

“…The leaf area index (LAI), which is defined as half the total green leaf area per unit ground surface area (Chen & Black 1992), is an important canopy parameter required for many physiological and ecosystem studies (Macfarlane et al 2007, Bequet et al 2012, Beckschäfer et al 2013. For instance, an accurate LAI estimation is essential for modeling light and precipitation interception, CO2 fluxes, evapotranspiration, and dry deposition (Jonckheere et al 2005, Beckschäfer et al 2014, Gonsamo & Chen 2014, Zhao et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Evaluation and correction of optically derived leaf area index in different temperate forests

Liu¹,

Jin²,

Zhou³

2016

iForest

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In recent years optical techniques for rapid LAI measurements have been developed, but few studies have been performed to evaluate the accuracy of optical estimation of LAI in mixed deciduous-evergreen forest stands. In this paper, we assessed the accuracy of digital hemispherical photography (DHP) and the LAI-2000 for the estimation of effective LAI (Le) by comparison with litter collection LAI (LAIlit) in four mixed deciduous broadleaf and evergreen needleleaf forests and one deciduous needleleaf forest. We also evaluated the relative contribution of major error sources to the determination of LAI by optical methods, including the woody-to-total area ratio (α), the element clumping index (ΩE) and the needle-to-shoot area ratio (γE). Additionally, incorrect automatic photographic exposure has been considered for DHP.

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On the exposure of hemispherical photographs in forests

Cited by 85 publications

References 57 publications

Potential and Limits of Retrieving Conifer Leaf Area Index Using Smartphone-Based Method

Potential and Limits of Retrieving Conifer Leaf Area Index Using Smartphone-Based Method

Comparison of field and airborne laser scanning based crown cover estimates across land cover types in Kenya

Evaluation and correction of optically derived leaf area index in different temperate forests

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