scholarly journals Terrestrial Lidar Raw Dataset for: Stemflow Dynamics in Relation to Individual Tree Canopy Structure, Neighborhood Conditions, and Meteorological Factors

2018 ◽  
Author(s):  
Sandra Yankine ◽  
John Van Stan ◽  
Jean-Francois Cote ◽  
Anke Hildebrandt ◽  
Dylan Mesta ◽  
...  
Keyword(s):  
Meteorological Factors ◽  
Canopy Structure ◽  
Tree Canopy ◽  
Individual Tree ◽  
Neighborhood Conditions ◽  
Terrestrial Lidar

scholarly journals Individual Tree Extraction from Terrestrial LiDAR Point Clouds Based on Transfer Learning and Gaussian Mixture Model Separation

2021 ◽  
Vol 13 (2) ◽  
pp. 223
Author(s):  
Zhenyang Hui ◽  
Shuanggen Jin ◽  
Dajun Li ◽  
Yao Yevenyo Ziggah ◽  
Bo Liu
Keyword(s):  
Transfer Learning ◽  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Principal Component ◽  
Point Clouds ◽  
Gaussian Mixture ◽  
Individual Tree ◽  
Terrestrial Lidar ◽  
Initial Segmentation ◽  
Tree Extraction

Individual tree extraction is an important process for forest resource surveying and monitoring. To obtain more accurate individual tree extraction results, this paper proposed an individual tree extraction method based on transfer learning and Gaussian mixture model separation. In this study, transfer learning is first adopted in classifying trunk points, which can be used as clustering centers for tree initial segmentation. Subsequently, principal component analysis (PCA) transformation and kernel density estimation are proposed to determine the number of mixed components in the initial segmentation. Based on the number of mixed components, the Gaussian mixture model separation is proposed to separate canopies for each individual tree. Finally, the trunk stems corresponding to each canopy are extracted based on the vertical continuity principle. Six tree plots with different forest environments were used to test the performance of the proposed method. Experimental results show that the proposed method can achieve 87.68% average correctness, which is much higher than that of other two classical methods. In terms of completeness and mean accuracy, the proposed method also outperforms the other two methods.

scholarly journals EFEKTIFITAS JALUR HIJAU DALAM MENGURANGI POLUSI UDARA OLEH KENDARAAN BERMOTOR

NALARs ◽  
2017 ◽  
Vol 16 (1) ◽  
pp. 91
Author(s):  
Lukmanul Hakim ◽  
Priambudi Trie Putra ◽  
Azka Lathifa Zahratu
Keyword(s):  
Canopy Structure ◽  
Tree Canopy ◽  
Toxic Substances ◽  
Main Function ◽  
Cross Sectional ◽  
Green Belt ◽  
Healthy Environment ◽  
Lead Dust ◽  
The Many ◽  
Selection Of

ABSTRAK. Ameliorasi iklim adalah salah satu manfaat yang diberikan alam khususnya tumbuhan terhadap lingkungan hidup, dengan cara meningkatkan kualitas lingkungan untuk menjamin tersedianya lingkungan yang sehat. Salah satunya adalah dengan menyediakan oksigen (O2) untuk kebutuhan pernafasan dan meminimalisir gas buang kendaraan bermotor yang beracun seperti gas carbon monooksida (CO) dan debu timbal (Pb). Kedua zat beracun ini sangat berbahaya bagi kesehatan manusia, khususnya yng berada disekitar jalan raya dan sekitar kawasan industri.Green belt adalah salah satu desain penghijauan yang fungsi utamanya adalah untuk mengurangi debu pencemaran ini. Yang diuji dalam penelitian ini adalah efektifitas desain green belt di sisi jalan raya dalam menangkap atau menjerap partikel (debu) polusi yang ditimbulkan oleh kendaraan bermotor. Fakta dalam percobaan yang dilkukan menunjukkan, bahwa bentuk struktur tajuk dan luas penampang daun sangat menentukan efektifitas dari penyerapan debu polusi. Daun yang mempunyai permukaan yang lebih luas dan mempunyai permukaan yang kasar, mempunyai nilai efektifitas yang tinggi. Begitu juga dengan pohon yang bertajuk rapat dan lebat akan sangat efektif dalam menjerap debu polusi atau polutan. Dalam hal ini, untuk desain green belt, diperlukan beberapa pertimbangan untuk efektifitas dalam mengurangi polusi udara. Yaitu pemilihan jenis vegetasi yang mempunyai daun yang lebar dan kasar serta pemilihan jenis struktur tajuk pohon yang disesuaikan dengan lokasi green belt tetapi dipilih yang rimbun dan lebat.Kata kunci: Ameliorasi iklim, vegetasi, penyerapan dan polusiABSTRACT. Climate amelioration is one of the many benefit from that nature, particularly plant that, provides to the environment, by enhancing quality of environment and guaranting the provision of healthy environment. For example is by providing oxygen (O2) for respiration and minimalizing toxic gas such as carbon monoxide (CO) and lead dust (Pb) emitted by vehicle. Both mentioned are toxic substances which highly dangerous for human health, especially for those residing around streets and industrial areas.Green belt is a greening design having main function to reduce pollution dust. This research tested the effectiveness of green belt on side roads in catching or absorbing pollution dust or particles emitted by vehicles. Facts from this research showed that the shape of canopy structure and leaves’ cross sectional area highly determine the effectiveness of pollution dust absorpsion. Leaves with wider surface area and rough texture have high effectiveness. Trees having dense canopy and bushy are very effective in absorpsion of pollution dust. In this case, to design a green belt will required a few considerations that are affecting effectiveness in reducing air polution. Namely, selection of vegetation that has wide and rough leaves and type selection of tree canopy structure that is dense and bushy and suitable to green belt location.Keywords : climate amelioration, vegetation, absorpsion and pollution

Obscuration measurements of tree canopy structure using a 3D imaging ladar system

2004 ◽  
Author(s):  
Richard W. Cannata ◽  
William Clifton ◽  
Steven Blask ◽  
Richard M. Marino
Keyword(s):  
3D Imaging ◽  
Canopy Structure ◽  
Tree Canopy

scholarly journals Kinetic Energy of Throughfall in Subtropical Forests of SE China – Effects of Tree Canopy Structure, Functional Traits, and Biodiversity

PLoS ONE ◽  
2013 ◽  
Vol 8 (2) ◽  
pp. e49618 ◽  
Author(s):  
Christian Geißler ◽  
Karin Nadrowski ◽  
Peter Kühn ◽  
Martin Baruffol ◽  
Helge Bruelheide ◽  
...  
Keyword(s):  
Kinetic Energy ◽  
Functional Traits ◽  
Canopy Structure ◽  
Tree Canopy ◽  
Subtropical Forests ◽  
Se China

scholarly journals Multidimensional Structural Characterization is Required to Detect and Differentiate Among Moderate Disturbance Agents

2019 ◽  
Author(s):  
Jeff W. Atkins ◽  
Ben Bond-Lamberty ◽  
Robert T. Fahey ◽  
Brady S. Hardiman ◽  
Lisa Haber ◽  
...  
Keyword(s):  
Structural Changes ◽  
Canopy Structure ◽  
Detection Methods ◽  
Ice Storm ◽  
Storm Damage ◽  
Ecological Disturbance ◽  
Moderate Severity ◽  
Terrestrial Lidar ◽  
Ice Storms ◽  
Age Related

The study of vegetation community and structural change has been central to ecology for over a century, yet how disturbances reshape the physical structure of forest canopies remains relatively unknown. Moderate severity disturbance including fire, ice storms, insect and pathogen outbreaks, affects different canopy strata and plant species, which may give rise to variable structural outcomes and ecological consequences. Terrestrial lidar (light detection and ranging) offers an unprecedented view of the interior arrangement and distribution of canopy elements, permitting the derivation of multidimensional measures of canopy structure that describe several canopy structural traits with known linkages to ecosystem functioning. We used lidar-derived canopy structural measured within a machine learning framework to detect and differentiate among various disturbance agents, including moderate severity fire, ice storm damage, age-related senescence, hemlock woolly adelgid, beech bark disease, and chronic acidification. We found that disturbance agents such as fire and ice storms primarily affected the amount and position of vegetation within canopies, while acidification, pathogen and insect infestation, and senescence altered canopy arrangement and complexity. Only two of the six disturbance agents significantly reduced leaf area, indicating that this commonly quantified canopy feature is insufficient to characterize many moderate severity disturbances. Rather, measures of canopy structure, including those that describe multidimensional change, are needed to characterize disturbance at moderate severities because structural changes from these events are spatially and quantitatively variable. Our findings suggest that standard disturbance detection methods, such as optical based remote sensing platforms, may currently be limited in their ability to detect, differentiate, and characterize disturbance. Further, we conclude that a more broadly inclusive definition of ecological disturbance that incorporates multiple aspects of canopy structure change will improve the modeling, detection, and prediction of functional implications of moderate severity disturbance.

scholarly journals Tree phyllosphere bacterial communities: exploring the magnitude of intra- and inter-individual variation among host species

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e2367 ◽  
Author(s):  
Isabelle Laforest-Lapointe ◽  
Christian Messier ◽  
Steven W. Kembel
Keyword(s):  
Community Structure ◽  
Bacterial Community ◽  
Individual Variation ◽  
Host Species ◽  
Bacterial Communities ◽  
Bacterial Community Structure ◽  
Temperate Forest ◽  
Abies Balsamea ◽  
Tree Canopy ◽  
Individual Tree

BackgroundThe diversity and composition of the microbial community of tree leaves (the phyllosphere) varies among trees and host species and along spatial, temporal, and environmental gradients. Phyllosphere community variation within the canopy of an individual tree exists but the importance of this variation relative to among-tree and among-species variation is poorly understood. Sampling techniques employed for phyllosphere studies include picking leaves from one canopy location to mixing randomly selected leaves from throughout the canopy. In this context, our goal was to characterize the relative importance of intra-individual variation in phyllosphere communities across multiple species, and compare this variation to inter-individual and interspecific variation of phyllosphere epiphytic bacterial communities in a natural temperate forest in Quebec, Canada.MethodsWe targeted five dominant temperate forest tree species including angiosperms and gymnosperms:Acer saccharum,Acer rubrum,Betula papyrifera,Abies balsameaandPicea glauca. For one randomly selected tree of each species, we sampled microbial communities at six distinct canopy locations: bottom-canopy (1–2 m height), the four cardinal points of mid-canopy (2–4 m height), and the top-canopy (4–6 m height). We also collected bottom-canopy leaves from five additional trees from each species.ResultsBased on an analysis of bacterial community structure measured via Illumina sequencing of the bacterial 16S gene, we demonstrate that 65% of the intra-individual variation in leaf bacterial community structure could be attributed to the effect of inter-individual and inter-specific differences while the effect of canopy location was not significant. In comparison, host species identity explains 47% of inter-individual and inter-specific variation in leaf bacterial community structure followed by individual identity (32%) and canopy location (6%).DiscussionOur results suggest that individual samples from consistent positions within the tree canopy from multiple individuals per species can be used to accurately quantify variation in phyllosphere bacterial community structure. However, the considerable amount of intra-individual variation within a tree canopy ask for a better understanding of how changes in leaf characteristics and local abiotic conditions drive spatial variation in the phyllosphere microbiome.

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