Vertical distributions of leaf area and inclination angle, and their relationship in a 46-year-old Chamaecyparis obtusa stand

Utsugi, Hajime; Araki, Masami; Kawasaki, T.; Ishizuka, Moriyoshi

doi:10.1016/j.foreco.2005.12.028

Cited by 38 publications

(27 citation statements)

References 37 publications

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“…The vertical distributions of leaf angle for a 46-year-old stand of Japanese cypress (Chamaecyparis obtusa Endl.) in central Japan decreased exponentially from top to bottom of the canopy, ranging in value from greater than 55˚ to 30.3˚ [35]. Again, these studies show a general pattern similar to the simulated summer case at 40˚N.…”

Section: Resultssupporting

confidence: 71%

Simulations of Seasonal and Latitudinal Variations in Leaf Inclination Angle Distribution: Implications for Remote Sensing

Huemmrich¹

2013

ARS

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The leaf inclination angle distribution (LAD) is an important characteristic of vegetation canopy structure affecting light interception within the canopy. However, LADs are difficult and time consuming to measure. To examine possible global patterns of LAD and their implications in remote sensing, a model was developed to predict leaf angles within canopies. Canopies were simulated using the SAIL radiative transfer model combined with a simple photosynthesis model. This model calculated leaf inclination angles for horizontal layers of leaves within the canopy by choosing the leaf inclination angle that maximized production over a day in each layer. LADs were calculated for five latitude bands for spring and summer solar declinations. Three distinct LAD types emerged: tropical, boreal, and an intermediate temperate distribution. In tropical LAD, the upper layers have a leaf angle around 35˚ with the lower layers having horizontal inclination angles. While the boreal LAD has vertical leaf inclination angles throughout the canopy. The latitude bands where each LAD type occurred changed with the seasons. The different LADs affected the fraction of absorbed photosynthetically active radiation (fAPAR) and Normalized Difference Vegetation Index (NDVI) with similar relationships between fAPAR and leaf area index (LAI), but different relationships between NDVI and LAI for the different LAD types. These differences resulted in significantly different relationships between NDVI and fAPAR for each LAD type. Since leaf inclination angles affect light interception, variations in LAD also affect the estimation of leaf area based on transmittance of light or lidar returns.

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Section: Resultssupporting

confidence: 71%

Simulations of Seasonal and Latitudinal Variations in Leaf Inclination Angle Distribution: Implications for Remote Sensing

Huemmrich¹

2013

ARS

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“…LIA distribution has been often related to light environment within the canopy and photosynthetic productivity (Muraoka et al, 1998;Niinemets and Fleck, 2002;Niinemets, 2010;Utsugi et al, 2006). It has been also reported that plants decrease the leaf temperature by adjusting the LIA more vertically (Medina et al, 1978;Muraoka et al, 1998).…”

Section: Introductionmentioning

confidence: 99%

“…However, the LIA distribution changes depending on the position in the canopy. For instance, it has been often observed that LIA changes gradually from more vertical in the upper canopy to more horizontal in the lower canopy (Niinemets, 2010; Utsugi et al, 2006). Such variation improves light interception in the lower canopy and enables the upper canopy to intercept less potentially damage from midday solar radiation and to allow more light to reach the lower canopy (Niinemets, 2010).…”

Section: Introductionmentioning

confidence: 99%

Estimating leaf inclination angle distribution of broad-leaved trees in each part of the canopies by a high-resolution portable scanning lidar

Hosoi

Omasa

2015

J. Agric. Meteorol.

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We estimated the distribution of leaf inclination angle (LIA) throughout the canopy of three broad-leaved trees by a portable high-resolution scanning lidar. Each canopy was scanned from three positions surrounding it and the data were co-registered. The 3-D images were divided into five horizontal layers, and the LIA distribution of each layer was estimated by a fitted plane to each leaf and taking the zenith angle of the plane. The LIA decreased significantly with increasing canopy height. The degree of the LIA decrease was different in each specimen. The mean LIA values of each layer were 36.7° to 43.8° in Camellia sasanqua, 34.6° to 45.9° in Osmanthus fragrans, and 48.9° to 65.4° in Camellia japonica. The differences in LIA distribution were explained mainly by the light conditions around the trees.

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“…Forest structure, captured by forest inventories, provides valuable information about the ecosystem. This includes the three-dimensional (3-D) canopy architecture information that greatly affects the radiation regime within the canopy [17], and many other biochemical and ecological processes such as photosynthesis [16], evaporation [11], and transpiration [18]. Most of traditional forest structure mensuration methods using digital hemisphere photographs [19] and range finders cannot capture the 3-D structural information for the single tree and forest stand.…”

Section: Introductionmentioning

confidence: 99%

Retrieving Forest Inventory Variables with Terrestrial Laser Scanning (TLS) in Urban Heterogeneous Forest

2011

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Abstract:We present the point cloud slicing (PCS) algorithm, to post process point cloud data (PCD) from terrestrial laser scanning (TLS). We then test this tool for forest inventory application in urban heterogeneous forests. The methodology was based on a voxel data structure derived from TLS PCD. We retrieved biophysical tree parameters including diameter at breast height (DBH), tree height, basal area, and volume. Our results showed that TLS-based metrics explained 91.17% (RMSE = 9.1739 cm, p < 0.001) of the variation in DBH at individual tree level. Though the scanner generated a high-density PCD, only 57.27% (RMSE = 0.7543 m, p < 0.001) accuracy was achieved for predicting tree heights in these very heterogeneous stands. Furthermore, we developed a voxel-based TLS volume estimation method. Our results showed that PCD generated from TLS single location scans only captures 18% of the total tree volume due to an occlusion effect; yet there are significant relationships between the TLS data and field measured parameters for DBH and height, giving promise to the utility of a side scanning approach. Using our method, a terrestrial LiDAR-based inventory, also applicable to mobile-or vehicle-based laser scanning (MLS or VLS), was produced for future calibration of Aerial Laser Scanning (ALS) data and urban forest canopy assessments. OPEN ACCESSRemote Sens. 2012, 4 2

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Vertical distributions of leaf area and inclination angle, and their relationship in a 46-year-old Chamaecyparis obtusa stand

Cited by 38 publications

References 37 publications

Simulations of Seasonal and Latitudinal Variations in Leaf Inclination Angle Distribution: Implications for Remote Sensing

Simulations of Seasonal and Latitudinal Variations in Leaf Inclination Angle Distribution: Implications for Remote Sensing

Estimating leaf inclination angle distribution of broad-leaved trees in each part of the canopies by a high-resolution portable scanning lidar

Retrieving Forest Inventory Variables with Terrestrial Laser Scanning (TLS) in Urban Heterogeneous Forest

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