scholarly journals Extraction of Leaf Biophysical Attributes Based on a Computer Graphic-based Algorithm Using Terrestrial Laser Scanning Data

2018 ◽  
Vol 11 (1) ◽  
pp. 15 ◽  
Author(s):  
Qiangfa Xu ◽  
Lin Cao ◽  
Lianfeng Xue ◽  
Bangqian Chen ◽  
Feng An ◽  
...  
Keyword(s):  
Leaf Area ◽  
Inclination Angle ◽  
Azimuthal Angle ◽  
Central Area ◽  
Azimuth Angle ◽  
Estimation Accuracy ◽  
Leaf Angle ◽  
Single Leaf ◽  
Fatsia Japonica ◽  
Leaf Inclination

Leaf attribute estimation is crucial for understanding photosynthesis, respiration, transpiration, and carbon and nutrient cycling in vegetation and evaluating the biological parameters of plants or forests. Terrestrial laser scanning (TLS) has the capability to provide detailed characterisations of individual trees at both the branch and leaf scales and to extract accurate structural parameters of stems and crowns. In this paper, we developed a computer graphic-based 3D point cloud segmentation approach for accurately and efficiently detecting tree leaves and their morphological features (i.e., leaf area and leaf angle distributions (leaf azimuthal angle and leaf inclination angle)) from single leaves. To this end, we adopted a sphere neighbourhood model with an adaptive radius to extract the central area points of individual leaves with different morphological structures and complex spatial distributions; meanwhile, four auxiliary criteria were defined to ensure the accuracy of the extracted central area points of individual leaf surfaces. Then, the density-based spatial clustering of applications with noise (DBSCAN) algorithm was used to cluster the central area points of leaves and to obtain the centre point corresponding to each leaf surface. We also achieved segmentation of individual leaf blades using an advanced 3D watershed algorithm based on the extracted centre point of each leaf surface and two morphology-related parameters. Finally, the leaf attributes (leaf area and leaf angle distributions) were calculated and assessed by analysing the segmented single-leaf point cloud. To validate the final results, the actual leaf area, leaf inclination and azimuthal angle data of designated leaves on the experimental trees were manually measured during field activities. In addition, a sensitivity analysis investigated the effect of the parameters in our segmentation algorithm. The results demonstrated that the segmentation accuracy of Ehretia macrophylla (94.0%) was higher than that of crape myrtle (90.6%) and Fatsia japonica (88.8%). The segmentation accuracy of Fatsia japonica was the lowest of the three experimental trees. In addition, the single-leaf area estimation accuracy for Ehretia macrophylla (95.39%) was still the highest among the three experimental trees, and the single-leaf area estimation accuracy for crape myrtle (91.92%) was lower than that for Ehretia macrophylla (95.39%) and Fatsia japonica (92.48%). Third, the method proposed in this paper provided accurate leaf inclination and azimuthal angles for the three experimental trees (Ehretia macrophylla: leaf inclination angle: R 2 = 0.908, RMSE = 6.806° and leaf azimuth angle: R 2 = 0.981, RMSE = 7.680°; crape myrtle: leaf inclination angle: R 2 = 0.901, RMSE = 8.365° and leaf azimuth angle: R 2 = 0.938, RMSE = 7.573°; Fatsia japonica: leaf inclination angle: R 2 = 0.849, RMSE = 6.158° and leaf azimuth angle: R 2 = 0.947, RMSE = 3.946°). The results indicate that the proposed method is effective and operational for providing accurate, detailed information on single leaves and vegetation structure from scanned data. This capability facilitates improvements in applications such as the estimation of leaf area, leaf angle distribution and biomass.

scholarly journals Quantitative Evaluation of Leaf Inclination Angle Distribution on Leaf Area Index Retrieval of Coniferous Canopies

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Guangjian Yan ◽  
Hailan Jiang ◽  
Jinghui Luo ◽  
Xihan Mu ◽  
Fan Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Inclination Angle ◽  
Three Dimensional ◽  
Good Choice ◽  
Optical Remote Sensing ◽  
Angle Distribution ◽  
Area Index ◽  
Leaf Inclination

Both leaf inclination angle distribution (LAD) and leaf area index (LAI) dominate optical remote sensing signals. The G-function, which is a function of LAD and remote sensing geometry, is often set to 0.5 in the LAI retrieval of coniferous canopies even though this assumption is only valid for spherical LAD. Large uncertainties are thus introduced. However, because numerous tiny leaves grow on conifers, it is nearly impossible to quantitatively evaluate such uncertainties in LAI retrieval. In this study, we proposed a method to characterize the possible change of G-function of coniferous canopies as well as its effect on LAI retrieval. Specifically, a Multi-Directional Imager (MDI) was developed to capture stereo images of the branches, and the needles were reconstructed. The accuracy of the inclination angles calculated from the reconstructed needles was high. Moreover, we analyzed whether a spherical distribution is a valid assumption for coniferous canopies by calculating the possible range of the G-function from the measured LADs of branches of Larch and Spruce and the true G-functions of other species from some existing inventory data and three-dimensional (3D) tree models. Results show that the constant G assumption introduces large errors in LAI retrieval, which could be as large as 53% in the zenithal viewing direction used by spaceborne LiDAR. As a result, accurate LAD estimation is recommended. In the absence of such data, our results show that a viewing zenith angle between 45 and 65 degrees is a good choice, at which the errors of LAI retrieval caused by the spherical assumption will be less than 10% for coniferous canopies.

scholarly journals Automatic Leaf Segmentation for Estimating Leaf Area and Leaf Inclination Angle in 3D Plant Images

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3576 ◽  
Author(s):  
Kenta Itakura ◽  
Fumiki Hosoi
Keyword(s):  
Leaf Area ◽  
Inclination Angle ◽  
Spatial Information ◽  
Structural Parameters ◽  
Plant Management ◽  
Seed Region ◽  
3D Images ◽  
Initial Segmentation ◽  
Leaf Inclination ◽  
Leaf Segmentation

Automatic and efficient plant monitoring offers accurate plant management. Construction of three-dimensional (3D) models of plants and acquisition of their spatial information is an effective method for obtaining plant structural parameters. Here, 3D images of leaves constructed with multiple scenes taken from different positions were segmented automatically for the automatic retrieval of leaf areas and inclination angles. First, for the initial segmentation, leave images were viewed from the top, then leaves in the top-view images were segmented using distance transform and the watershed algorithm. Next, the images of leaves after the initial segmentation were reduced by 90%, and the seed regions for each leaf were produced. The seed region was re-projected onto the 3D images, and each leaf was segmented by expanding the seed region with the 3D information. After leaf segmentation, the leaf area of each leaf and its inclination angle were estimated accurately via a voxel-based calculation. As a result, leaf area and leaf inclination angle were estimated accurately after automatic leaf segmentation. This method for automatic plant structure analysis allows accurate and efficient plant breeding and growth management.

scholarly journals Dynamic Simulation on Canopy Light Distribution and Dry Matter Accumulation of Natural Colored Cotton in Alar Reclamation Area of Xinjiang

2020 ◽  
Vol 10 (3) ◽  
pp. 123-134
Author(s):  
Zhenqi Fan ◽  
◽  
Lixin Zhang
Keyword(s):  
Leaf Area ◽  
Inclination Angle ◽  
Dry Matter ◽  
Light Distribution ◽  
Physiological Age ◽  
Dry Matter Accumulation ◽  
Angle Distribution ◽  
Area Index ◽  
Colored Cotton ◽  
Leaf Inclination

Based on Ross’s theory of optical radiation transmission and full consideration of influences of vertical distribution of canopy leaf area and leaf inclination angle distribution of colored cotton on the light distribution, the Gaussian 5-point distance was used to divide the canopy into 5 layers on basis of the leaf area index. The leaf inclination angle on each layer was divided into 6 equal parts by 15°. The types of radiation in canopy, spatial distribution of light radiation, as well as diurnal variation with solar hour angles were quantified in detail. After comprehensively considering influences of temperature, physiological age and other factors on photosynthesis and respiration, the canopy light distribution, photosynthetic production and dry matter accumulation of colored cotton were simulated with strong mechanistic and physiological & ecological significance. The colored cotton samples sown on April 16, 2019 were used to verify the model. The RMSEs of simulated and measured canopy PAR values at Beijing time 10:00, 12:00, 14:00 and 16:00 on July 30 were 58.2, 64.1, 43.4 and 39.7 µmol•m-2•s-1, respectively. The RMSE of simulated and observed values of the dry matter accumulation above ground was 412.6 kgDM•hm-2, reflecting the good predictability of the model.

Irrigation of Geraniums with an Automatic Controlled Water Table System

HortScience ◽  
1998 ◽  
Vol 33 (3) ◽  
pp. 522d-522 ◽  
Author(s):  
J.W. Buxton ◽  
D.L. Ingram ◽  
Wenwei Jia
Keyword(s):  
Water Potential ◽  
Leaf Area ◽  
Water Table ◽  
Nutrient Solution ◽  
Irrigation System ◽  
Central Area ◽  
Dry Weight ◽  
Trickle Irrigation ◽  
Run Off ◽  
Optimum Water

Geraniums in 15-cm pots were irrigated automatically for 8 weeks with a Controlled Water Table (CWT) irrigation system. Plants were irrigated with a nutrient solution supplied by a capillary mat with one end of the mat suspended in a trough below the bottom of the pot. The nutrient solution remained at a constant level in the trough. Nutrient solution removed from the trough was immediately replaced from a larger reservoir. The vertical distance from the surface of the nutrient solution and the bottom of the pot determined the water/air ratio and water potential in the growing media. Treatments consisted of placing pots at 0, 2, 4, and 6 cm above the nutrient solution. Control plants were irrigated as needed with a trickle irrigation system. Geraniums grown at 0,2 and 4 CWT were ≈25% larger than the control plants and those grown at 6 CWT as measured by dry weight and leaf area. Roots of plants grown at 0 CWT were concentrated in the central area of the root ball; whereas roots of plants in other treatments were located more near the bottom of the pot. Advantages of the CWT system include: Plant controlled automatic irrigation; no run off; optimum water/air ratio.

scholarly journals UAV Based Estimation of Forest Leaf Area Index (LAI) through Oblique Photogrammetry

2021 ◽  
Vol 13 (4) ◽  
pp. 803
Author(s):  
Lingchen Lin ◽  
Kunyong Yu ◽  
Xiong Yao ◽  
Yangbo Deng ◽  
Zhenbang Hao ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Point Cloud ◽  
Forest Canopy ◽  
Estimation Method ◽  
Vertical Direction ◽  
Estimation Accuracy ◽  
3D Point Cloud ◽  
Area Index ◽  
Better Than

As a key canopy structure parameter, the estimation method of the Leaf Area Index (LAI) has always attracted attention. To explore a potential method to estimate forest LAI from 3D point cloud at low cost, we took photos from different angles of the drone and set five schemes (O (0°), T15 (15°), T30 (30°), OT15 (0° and 15°) and OT30 (0° and 30°)), which were used to reconstruct 3D point cloud of forest canopy based on photogrammetry. Subsequently, the LAI values and the leaf area distribution in the vertical direction derived from five schemes were calculated based on the voxelized model. Our results show that the serious lack of leaf area in the middle and lower layers determines that the LAI estimate of O is inaccurate. For oblique photogrammetry, schemes with 30° photos always provided better LAI estimates than schemes with 15° photos (T30 better than T15, OT30 better than OT15), mainly reflected in the lower part of the canopy, which is particularly obvious in low-LAI areas. The overall structure of the single-tilt angle scheme (T15, T30) was relatively complete, but the rough point cloud details could not reflect the actual situation of LAI well. Multi-angle schemes (OT15, OT30) provided excellent leaf area estimation (OT15: R2 = 0.8225, RMSE = 0.3334 m2/m2; OT30: R2 = 0.9119, RMSE = 0.1790 m2/m2). OT30 provided the best LAI estimation accuracy at a sub-voxel size of 0.09 m and the best checkpoint accuracy (OT30: RMSE [H] = 0.2917 m, RMSE [V] = 0.1797 m). The results highlight that coupling oblique photography and nadiral photography can be an effective solution to estimate forest LAI.

Single leaf area estimation models based on leaf weight of eucalyptus in southern China

2010 ◽  
Vol 21 (1) ◽  
pp. 73-76 ◽  
Author(s):  
Jun Diao ◽  
Xiang-dong Lei ◽  
Ling-xia Hong ◽  
Jian-tao Rong ◽  
Qiang Shi
Keyword(s):  
Leaf Area ◽  
Southern China ◽  
Area Estimation ◽  
Single Leaf ◽  
Leaf Weight ◽  
Estimation Models

Compensatory Responses of Common Cocklebur (Xanthium strumarium) and Velvetleaf (Abutilon theophrasti) to Partial Shading

Weed Science ◽  
1993 ◽  
Vol 41 (4) ◽  
pp. 541-547 ◽  
Author(s):  
Emilie E. Regnier ◽  
S. Kent Harrison
Keyword(s):  
Leaf Area ◽  
Shade Tolerance ◽  
Shoot Growth ◽  
Branch Length ◽  
Dry Weight ◽  
Xanthium Strumarium ◽  
Leaf Angle ◽  
Petiole Length ◽  
Partial Shading ◽  
Total Plant

Lower leaves of greenhouse-grown common cocklebur and velvetleaf were shaded to 5% of full light over a 12-d period while upper leaves remained exposed to full light to determine weed foliar and branching responses to partial shading similar to that encountered in soybean crops. Shading increased lower leaf senescence and specific leaf area, and decreased branch length and number of second-order leaves in both species compared to unshaded controls. Common cocklebur branched more extensively along the lower portion of its stem than velvetleaf under both shaded and unshaded conditions. Upper leaves of partially shaded velvetleaf were held in a more perpendicular position to the light source beginning 3 days after treatment (DAT) compared to upper leaves of unshaded plants. Shading of lower leaves caused an increase in upper (unshaded) leaf area beginning 3 and 6 DAT in velvetleaf and common cocklebur, respectively. Petiole length of upper leaves also increased in response to shading in both species. Total plant dry weight at 12 DAT was unaffected by shading in velvetleaf but was reduced 10% by shading in common cocklebur. While common cocklebur maintained greater lower shoot growth in the presence of shade than velvetleaf, there was a greater change in upper leaf angle by velvetleaf in response to shading than by common cocklebur. These results support previous field observations of apparent greater shade tolerance of common cocklebur compared to velvetleaf and indicate that both species have the ability to compensate for shading of lower leaves by altering upper shoot growth.

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