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23 results for “forest canopy structure”
R scripts for analyzing LiDAR data to assess forest canopy structure and perform Principal Component Analysis (PCA) on derived metrics
<p>This repository contains R scripts for analyzing LiDAR data to assess forest canopy structure and perform Principal Component Analysis (PCA) on spectral and LiDAR-derived metrics. The scripts cover LiDAR data processing, canopy height model (CHM) generation, calculation of forest canopy metrics, and PCA analysis.</p>
Robust retrieval of forest canopy structural attributes using multi-platform airborne LiDAR
<p><strong>Data and R code to replicate the analyses presented in</strong>:<br>Zhang et al. (2024) Robust retrieval of forest canopy structural attributes using multi-platform airborne LiDAR. Remote Sensing in Ecology and Conservation, <a href="https://doi.org/10.1002/rse2.398">https://doi.org/10.1002/rse2.398</a></p> <p>If using these data and/or R code in your work please cite the original publication listed above, as well as this repository using the corresponding DOI.</p>
UAS-SfM data from Unoccupied aerial system (UAS) Structure-from-Motion canopy fuel parameters: Multisite area-based modelling across forests in California, USA
<p>Data for:</p> <p>Unoccupied aerial system (UAS) Structure-from-Motion canopy fuel parameters: Multisite area-based modelling across forests in California, USA<br>Sean Reilly 1, Matthew L. Clark 2, Lika Loechler 2, Jack Spillane 2, Melina Kozanitas 3, Paris Krause 4, David Ackerly 3, Lisa Patrick Bentley 4, and Imma Oliveras Menor 1,5</p> <p>1 Environmental Change Institute, University of Oxford, Oxford OX1 3QY, UK<br>2 Center for Interdisciplinary Geospatial Analysis, Department of Geography, Environment, and Planning, Sonoma State University, Rohnert Park, CA 94928, USA<br>3 Departments of Integrative Biology and Environmental Science, Policy, and Management, University of California, Berkeley, CA 94720, USA<br>4 Department of Biology, Sonoma State University, Rohnert Park, CA 94928, USA<br>5 AMAP (Botanique et Modélisation de l’Architecture des Plantes et des Végétations), CIRAD, CNRS, INRA, IRD, Université de Montpellier, Montpellier, France</p> <p>Study abstract:</p> <p>There is a pressing need for well-informed management to reduce wildfire hazard and restore fire’s beneficial ecological role in the Mediterranean- and temperate-climate forests of California, USA. These efforts rely upon the accessibility of high spatial and temporal resolution data on biomass and canopy fuel parameters such as canopy base height (CBH), mean canopy height, canopy bulk density (CBD), canopy cover, and leaf area index (LAI). Remote sensing using unoccupied aerial system Structure-from-Motion (UAS-SfM) presents a promising technology for this application due to its accessibility, relatively low cost, and possibility for high temporal cadence. However, to date, this method has not been studied in the complex mosaic of forest types found across California. In this study we examined the capacity of structural and multispectral information obtained from UAS-SfM, in conjunction with machine learning methods, to model aboveground biomass and forest canopy fuel structural parameters using an area-based approach across multiple sites representing a diversity of forest types in California.</p> <p>Based on correlations with field measurements, fuel parameters separated into vertical (biomass, CBH, and mean height) and horizontal (LAI, CBD, canopy cover) groups. UAS-SfM random forest models performed well for modelling the vertical structure canopy fuels parameters (R2 0.69 – 0.75). These models exhibited strong performance in comparison to ALS, as well as when transferred to a novel site. Vertical structure predictors were prominent in these models, and did not improve with the addition of spectral predictors. UAS-SfM random forest models of horizontal structure parameters mainly used raster-based spectral indices (primarily NDVI) and had relatively low performance (R2 0.49 – 0.59). In addition, these models underperformed ALS and had poor performance when applied to a novel site. When applied to a region with widespread UAS-SfM coverage, models from both groups successfully produced contiguous maps that could be used for modelling fire behavior or in management decision making and monitoring.</p> <p>These findings indicate that UAS-SfM, without the need for multispectral sensors, is well suited for mapping area-based vertical-structure canopy parameters across diverse landscapes supporting a wide range of forest types. In contrast, the identification of spectral mean variables for modelling horizontal structure canopy fuels suggests the potential of multi- or hyperspectral sensors or high-resolution satellite imagery for meeting management information needs. </p> <p>Published in Remote Sensing of Environment</p> <p><br>Contents:</p> <p>This repository contains multispectral UAS-SfM data from four sites around California, USA:<br>jcksn: Jackson Demonstration State Forest<br>ltr: LaTour Demonstration State Forest<br>ppwd: Pepperwood Preserve<br>sdlmtn: Saddle Mountain Open Space Preserve</p> <p>Data were collected during a series of campaigns:<br>c1: Pepperwood, 2019-09-01 to 2019-10-15<br>c3: Jackson, 2020-06-15 to 2020-07-02<br>c4: LaTour, 2020-07-07 to 2020-07-17<br>c6: Saddle Mountain, 2020-08-04 to 2020-08-09<br>c9: Jackson, 2021-07-08 to 2021-07-12</p> <p>Data are included in three formats:<br>raw: Raw outputs from Pix4D (spectral and las)<br>reg_grnd, reg_cnpy: Las files with merged multispectral data and classified ground, registered to ALS using either ground points (grnd) or, in cases with insufficient ground points for registration, to the canopy (cnpy)<br>hnrm: Height normalized las files, normalization performed using ALS terrain model</p> <p>File naming structure:<br>site_campaign_flightzone_uas_processedstate</p> <p>See accompanying paper for methods on data collection and processing</p> <p>Data are grouped into zipped folder by product type</p> <p>Funding:</p> <p>Funding for this research was supported by CAL FIRE Forest Health and Forest Legacy (8GG18806) and California State University, Agricultural Research Institute (20-01-106) awards to L.P.B and M.L.C. S.R. was funded by the Rhodes Trust and through the University of Oxford Environmental Change Institute Small Grant Scheme. Pepperwood ground data collection was supported by funding from the Gordon and Betty Moore Foundation and National Science Foundation grants 1754475 and 1835086.</p> <p>Citation:</p> <div> <div>Reilly, S., Clark, M.L., Loechler, L., Spillane, J., Kozanitas, M., Krause, P., Ackerly, D., Bentley, L.P., Menor, I.O., 2024. Unoccupied aerial system (UAS) Structure-from-Motion canopy fuel parameters: Multisite area-based modelling across forests in California, USA. Remote Sensing of Environment 312, 114310. <a href="https://doi.org/10.1016/j.rse.2024.114310">https://doi.org/10.1016/j.rse.2024.114310</a></div> </div> <p> </p> <p> </p>
Fig. 4 in Canopy crane survey of the hemipteran assemblage structure in a Bornean forest
Fig. 4. NMDS ordination plots for (a) all species based on the Sørensen similarity index and (b) abundant species based on the Bray–Curtis dissimilarity index. White circle indicates the GF period and black circle indicates the non-GF period.
Fig. 3 in Canopy crane survey of the hemipteran assemblage structure in a Bornean forest
Fig. 3. Log-transformed numbers of (a) adult species, (b) adult individuals and (c) nymphs during each sampling period. Different letters indicate significant differences in abundance (Kruskal–Wallis with post hoc tests, p <0.01). Box plots indicate the range of the data within the ends of the whiskers; the middle two quartiles are within the box; and the median value is indicated by the bold line. The end of the whisker indicates Q3 + 1.5×(Q3 – Q1) and the outliner is above it.
Fig. 2 in Canopy crane survey of the hemipteran assemblage structure in a Bornean forest
Fig. 2. Species accumulation curves (Sobs, Mao Tau) for adult hemipteran species during each sampling period. The curves are the result 50 randomisations.
Fig. 1 in Canopy crane survey of the hemipteran assemblage structure in a Bornean forest
Fig. 1. Proportions of target canopy tree individuals with mature leaves, immature leaves, buds, flowers or seeds (see text for definitions). Numbers above bars represent the number of target trees during each sampling period.
Snow pit dataset from "Comparison of snowpack structure in gaps and under the canopy in a humid boreal forest"
<p>This original dataset contains snow pit measurements collected at Montmorency Forest (47.29°N, 71.17°W) from 22 November, 2018 to 6 June, 2019. The study site is a balsam fir – whit birch stand on a 12° slope of north-east aspect. The dataset is described in the publication “<strong><em>Comparison of snowpack structure in gaps and under the canopy in a humid boreal forest</em></strong>” from Bouchard et al., 2022. In this dataset you can find:</p> <p> </p> <ul> <li>inside forest gaps: <ul> <li>26 snow height measurements (26 data points)</li> <li>26 snowpack stratigraphy (380 data points)</li> <li>26 snow temperature profiles (427 data points)</li> <li>26 snow density profiles (803 data points)</li> <li>2 snow specific surface area (SSA) profiles (97 data points)</li> </ul> </li> </ul> <p> </p> <ul> <li>under the canopy: <ul> <li>26 snow height measurements (26 data points)</li> <li>26 snowpack stratigraphy (227 data points)</li> <li>26 snow temperature profiles (325 data points)</li> <li>26 snow density profiles (623 data points)</li> <li>2 snow SSA profiles (89 data points)</li> </ul> </li> </ul> <p> </p> <p>For density measurements, the height value corresponds to the center of the 3-cm thick box cutter. For the SSA, the value is measured optically at the top of the sample. This value is representative of the top 1 cm of the snow sample, as this is the typical e-folding depth of 1310 nm radiation in snow. Grain type codes for the snowpack stratigraphy corresponds to the <em>International Classification for Seasonal Snow </em>(Fierz et al., 2009):</p> <p> </p> <ul> <li>PP: Precipitation particle</li> <li>DF: Decomposed and Fragmented precipitation particles</li> <li>RG: Rounded Grains</li> <li>FC: Faceted Crystals</li> <li>DH: Depth Hoar</li> <li>MFpc: Melt Forms – rounded polycrystals</li> <li>MFcl: Melt Forms – clustered rounded grains</li> <li>MFcr: Melt Forms – melt-freeze crusts</li> <li>IF: Ice Formations</li> </ul>
Datasets used for the publication: UAV-Lidar reveals that canopy structure mediates the influence of edge effects on forest diversity, function and microclimate
<p>Datasets used for the publication: UAV-Lidar reveals that canopy structure mediates the influence of edge effects on forest diversity, function and microclimate.</p> <p>The file "Blanchard_et_al_JoE_2023_data_plot_trees.csv" contains individual tree indentification data for the 46 plots used in the study.</p> <p>The file "Blanchard_et_al_JoE_2023_data_plot_aggregated.csv" contains plot-level aggregated metrics used for the analyses:</p> <p>- distance to the forest edge</p> <p>- diversity indices : the 20-sp rarefied species richness "rar_sp_richness_20" and the 20-sp rarefied Beta diversity "Beta_div" which corresponds to the plos coordinates on the PCoA first axis.</p> <p>- functional indices: the community weighted mean trait values for the four traits used in this study : ,"WD","SLA","LA","LDMC"; the fonctional divergence index "FD_trans.FDiv"; and the synthetic community weigthed mean trait wich corresponds to the postion on plots on the principal component analysis of species trait values "Functional_composition_trans". Note that the SLA and LA values were log-transformed before computing "FD_trans.FDiv" and "Functional_composition_trans".</p> <p>- UAV-LiDAR-dervived metrics: canopy height, gap fraction ("gap_fraction2"), slope, curvature</p> <p>- The estimated plot above graound biomass "agb_plot", and the mean value of the vapor pressure deficit during the drisest month "max_monthly_VPD".</p> <p>- coordinates of the plots in UTM 58S (Coordinate reference system)</p> <p>Please read the material and method section of the article for more informations on this dataset.</p>
Supporting dataset for "Surface energy dynamics and canopy structural properties in intact and disturbed forests in the Southern Amazon"
<p>Supporting dataset for the manuscript “Surface energy dynamics and canopy structural properties in intact and disturbed forests in the Southern Amazon", currently under review in the Journal of Geophysical Research: Biogeosciences.</p>
Canopy structure and forest understory conditions in a wet Amazonian forest – no change over the last 20 years
<p><span><span><span><span><span><span><span><span><span><span><span>Climate change is altering forest dynamics in the tropics, with large potential impacts on forest structure and understory conditions. However, we found that canopy height distribution and openness remained stable over two decades in the western Amazon, and that gap creation rates would need to increase 300% before affecting equilibrium.</span></span></span></span></span></span></span></span></span></span></span></p>
Data from: LiDAR-derived canopy structure supports the more-individuals hypothesis for arthropod diversity in temperate forests
Despite considerable progress in the ability to measure the complex 3-D structure of forests with the improvement of remote-sensing techniques, our mechanistic understanding of how biodiversity is linked to canopy structure is still limited. Here we tested whether the increase in arthropod abundance and richness in beech forest canopies with increasing canopy complexity supports the more-individuals hypothesis or the habitat-heterogeneity hypothesis. We used fogging to collect arthropod samples from 80 standardized plots from canopies of single- to multi-layered mature montane European beech stands. Tree height and an independent measure of vertical heterogeneity — the vertical distribution ratio — on each arthropod sampling plot were derived from high-resolution full-waveform airborne laser scanning data. Mixed-model path analysis based on almost 20,000 specimens of 762 species from 11 orders provided support for the more-individuals hypothesis, with higher arthropod abundance but not higher species richness in stands with a more equal vertical distribution of plant biomass. By contrast, we found no support for the habitat-heterogeneity hypothesis. The increase in the number of individuals with increasing vertical distribution of biomass might be caused either by increasing leaf area, as indicated by higher space filling and productivity in multi-layered stands, or by higher persistence of arthropod populations owing to better shelter, reduced competition and more refuges under harsh conditions, or by both. High-resolution airborne laser scanning, with its ability to penetrate dense canopies under leaf-on conditions, has proved suitable for measuring vertical structures as a predictor for canopy diversity. Expanding combinations of remote-sensing and canopy-biodiversity data opens many avenues for improving our understanding of the link between diversity and forest structures.
Data for: The long-term impacts of deer herbivory in determining temperate forest stand and canopy structural complexity
<p>1. Ungulates place immense consumptive pressure on forest vegetation globally, leaving legacies of reduced biodiversity and simplified vegetative structure. However, what remains unresolved is whether browse-induced changes occurring early in succession ultimately manifest themselves in the developed forest canopy. Understanding the development and persistence of these legacies is critical as canopy structure is an important determinant of forest ecosystem functions like carbon sequestration and wildlife habitat.</p> <p>2. We measured how white-tailed deer (Odocoileus virginianus) browse during stand initiation affected canopy structure, tree species richness, diversity, stem density, and basal area on Pennsylvania's Allegheny Plateau using a portable canopy LiDAR system. We capitalized on an historic deer enclosure experiment where forests were subjected to four deer densities (4, 8, 15, and 25 deer/km2) for ten years following stand initiation.</p> <p>3. Deer browsing impacts on the forest canopy are apparent nearly four decades since stand initiation. The highest deer density treatment experienced a significant reduction in tree species diversity, density, and basal area with stands becoming dominated by black cherry (Prunus serotina). Reductions in overstory diversity and tree density resulted in a more open canopy with low leaf area and high horizontal leaf variability. Canopies were tallest at the lowest and highest deer densities.</p> <p><i>4. Synthesis and Applications</i>: Using a portable canopy LiDAR system and a former deer enclosure experiment, we show that high deer browsing pressure during stand initiation can have a decades-long impact on stand and canopy structure. High deer densities led to stands with lower species diversity and tree density, which resulted in canopies that were taller and less dense. Managers should consider the lasting legacy of ungulate herbivory on canopy structure, as canopy structure influences several important management goals, such as forest carbon sequestration, maintenance of diverse understory communities, and creation of wildlife habitat.</p>
Data from: Connectivity explains local ant community structure in a Neotropical forest canopy: a large-scale experimental approach
Understanding how habitat structure and resource availability affect local species distributions is a key goal of community ecology. Where habitats occur as a mosaic, variation in connectivity among patches influences both local species richness and composition, and connectivity is a key conservation concern in fragmented landscapes. Similarly, availability of limiting resources frequently determines species co-existence or exclusion. For primarily cursorial arthropods like ants, gaps between neighboring trees are a significant barrier to movement through the forest canopy. Competition for limited resources such as nest sites also promotes antagonistic interactions. Lianas (woody vines) connect normally isolated neighboring tree crowns and often have hollow stems inhabited by ants. We used two large-scale liana removal experiments to determine how connectivity and nest site availability provided by lianas affect arboreal ant species richness, species composition, and β-diversity in a lowland tropical forest in Panama. Removing lianas from a tree crown reduced ant species richness up to 35%, and disproportionately affected species that require large foraging areas. Adding artificial connectivity to trees mitigated the effects of liana removal. Ant colonization of artificial nests was higher (73% occupied) in trees without lianas vs. trees with lianas (28% occupied). However, artificial nests typically were colonized by existing polydomous, resident ant species. As a result, nest addition did not affect ant community structure. Collectively, these results indicate that lianas are important to the maintenance of arboreal ant diversity specifically by providing connectivity among neighboring tree crowns. Anticipated increases in liana abundance in this forest could increase the local (tree-level) species richness of arboreal ants, with a compositional bias toward elevating the density of broad-ranging specialist predators.
Short-Term Effects of Moderate Severity Disturbances on Forest Canopy Structure- Derived Data
<p>NEON plot-level derived tables used in this study. All the derived data were openly available from The National Science Foundation's National Ecological Observatory Network (NEON).</p> <ul> <li>01: R codes for 01) LiDAR-derived canopy metrics calculation; 02) Modelling</li> <li>02: Input ground survey data with removed duplicate rows (tree_rm_duplicates.csv); CSV files - NEON vegestructure data (disturbance_structural_diversity_data_2022_1109_den4.csv)</li> </ul> <p>All NEON’s Discrete return LiDAR point cloud (DP1.30003.001) (NEON 2021a) and Vegetation structure (DP1.10098.001) (NEON 2022) data are available on NEON data portal as follows: <a href="https://data.neonscience.org/data-products/DP1.30003.001">https://data.neonscience.org/data-products/DP1.30003.001</a> (<a href="https://doi.org/10.48443/6E8K-3343">https://doi.org/10.48443/6E8K-3343</a>), and <a href="https://data.neonscience.org/data-products/DP1.10098.001/RELEASE-2022">https://data.neonscience.org/data-products/DP1.10098.001/RELEASE-2022</a> (<a href="https://doi.org/10.48443/RE8N-TN87">https://doi.org/10.48443/RE8N-TN87</a>), respectively.</p> <p>R scripts for calculating canopy metrics (Hardiman et al. 2021) are available on Environmental Data Initiative (EDI): <a href="https://doi.org/10.6073/pasta/97f8092c10aecbc62aec12557ecb52bd">https://doi.org/10.6073/pasta/97f8092c10aecbc62aec12557ecb52bd</a></p> <p> </p> <p>Reference</p> <ul> <li>Hardiman, B.S., E.A. LaRue, J.R. Foster, R. Fahey, and J. Hatala Matthes. 2021. Forest structural diversity at NEON sites in the continuous USA that experienced recent moderate disturbance ver 1. Environmental Data Initiative. https://doi.org/10.6073/pasta/97f8092c10aecbc62aec12557ecb52bd (Accessed 2023-05-24).</li> <li>NEON. 2021a. Discrete return LiDAR point cloud (DP1.30003.001). National Ecological Observatory Network (NEON). doi: <a href="https://doi.org/10.48443/6E8K-3343">https://doi.org/10.48443/6E8K-3343</a>.</li> <li>NEON. 2022. Vegetation structure (DP1.10098.001). National Ecological Observatory Network (NEON). doi: <a href="https://doi.org/10.48443/RE8N-TN87">https://doi.org/10.48443/RE8N-TN87</a>.</li> </ul>
Data from: Connectivity explains local ant community structure in a Neotropical forest canopy: a large-scale experimental approach
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Canopy structure and forest understory conditions in a wet Amazonian forest – no change over the last 20 years
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Data for: The long-term impacts of deer herbivory in determining temperate forest stand and canopy structural complexity
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Data from: LiDAR-derived canopy structure supports the more-individuals hypothesis for arthropod diversity in temperate forests
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Pasture trees contribute to structural heterogeneity and plant distributions in post-agricultural forests decades after canopy closure
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.