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781 results for “canopies”

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zenodo48/100

L2C - Canopy height models across the Brazilian Amazon

<p>Canopy height models derived from LiDAR data collected across the Brazilian Amazon. The files are provided in .tiff format in 7 zip folders. A full description of the data set is available here:&nbsp;https://zenodo.org/record/4968706#.YzB693ZKg5s</p> <p>We also provide the summary data used for statistical analysis in the associated publication:&nbsp;</p> <p>Reis and Jackson et al 2022.&nbsp;Forest disturbance and growth processes are reflected in the geographic distribution of large canopy gaps across the Brazilian Amazon. Journal of Ecology.</p> <p>Each transect&nbsp;covered&nbsp;375 ha (12.5 km &times; 300 m) by emitting full-waveform laser pulses from a Trimble Harrier 68i airborne sensor (Trimble; Sunnyvale, CA) aboard a Cessna aircraft (model 206). The average point density was set at four returns per square meters, the field of view was equal to 30&deg;, the flying altitude was 600 m, and transect width on the ground was approximately 494 m. Global Navigation Satellite System (GNSS) data were collected on a dual-frequency receiver (L1/L2). The pulse footprint was set to be below 30 cm, based on a divergence angle between 0.1 and 0.3 milliradians. Horizontal and vertical accuracy were controlled to be under 1 m and under 0.5 m, respectively.</p> <p>The data collection was funded by the Coordena&ccedil;&atilde;o&nbsp;de Aperfei&ccedil;oamento de Pessoal de N&iacute;vel&nbsp;Superior Brasil&nbsp;(CAPES; Finance Code 001); Conselho Nacional de Desenvolvimento Cient&iacute;fico e Tecnol&oacute;gico (Processes 403297/2016-8 and 301661/2019-7); Amazon Fund (grant 14.2.0929.1)</p> <p>The research project was funded by the UK Natural Environment Research Council project number&nbsp;<strong>NE/S010750/1</strong></p>

opencc-by-4.0Sep 2022View details →
zenodo48/100

Data from Phenocam (PHE) measurements of in-canopy vegetation (hartheim2) at Hartheim Forest Research Site (DE-Har) from 2018-11-05 to 2018-12-31 [RAW]

<p>Phenocam images from "hartheim2" at DE-Har separated into near-infrared (NIR) and visible (VIS) for the year 2022.&nbsp;The phenocam "hartheim2" was put into operation on November 5, 2018. There are no phenocam images before that date at this site.</p> <p>Phenocam "hartheim2" shows the view from the main tower at 8.4 m height towards N at the <a href="https://www.meteo.uni-freiburg.de/en/infrastructure/hartheim-forest-research-site?set_language=en">ICOS Associate Ecosyste Site DE-Har, Germany</a> recording the phenology and state of in-canopy vegetation.</p>

opencc-by-4.0Apr 2024View details →
zenodo48/100

Data from Phenocam (PHE) measurements of in-canopy vegetation (hartheim2) at Hartheim Forest Research Site (DE-Har) from 2020-01-01 to 2020-12-31 [RAW]

<p>Phenocam images from "hartheim2" at DE-Har separated into near-infrared (NIR) and visible (VIS) for the year 2020.&nbsp;</p> <p>Phenocam "hartheim2" shows the view from the main tower at 8.4 m height towards N at the <a href="https://www.meteo.uni-freiburg.de/en/infrastructure/hartheim-forest-research-site?set_language=en">ICOS Associate Ecosyste Site DE-Har, Germany</a> recording the phenology and state of in-canopy vegetation.</p>

opencc-by-4.0Apr 2024View details →
zenodo48/100

Data from Phenocam (PHE) measurements of in-canopy vegetation (hartheim2) at Hartheim Forest Research Site (DE-Har) from 2021-01-01 to 2021-12-31 [RAW]

<div> <p>Phenocam images from "hartheim2" at DE-Har separated into near-infrared (NIR) and visible (VIS) for the year 2021.&nbsp;</p> <p>Phenocam "hartheim2" shows the view from the main tower at 7m height towards N at the&nbsp;<a href="https://www.meteo.uni-freiburg.de/en/infrastructure/hartheim-forest-research-site?set_language=en">ICOS Associate Ecosystem Site DE-Har, Germany</a> recording the phenology and state of in-canopy vegetation.</p> </div>

opencc-by-4.0Apr 2024View details →
zenodo48/100

Data from Phenocam (PHE) measurements of in-canopy vegetation (hartheim2) at Hartheim Forest Research Site (DE-Har) from 2022-01-01 to 2022-12-31 [RAW]

<div> <p>Phenocam images from "hartheim2" at DE-Har separated into near-infrared (NIR) and visible (VIS) for the year 2022.&nbsp;</p> <p>Phenocam "hartheim2" shows the view from the main tower at at 8.4 m height towards N at the <a href="https://www.meteo.uni-freiburg.de/en/infrastructure/hartheim-forest-research-site?set_language=en">ICOS Associate Ecosystem Site DE-Har, Germany</a> recording the phenology and state of in-canopy vegetation.</p> <p>&nbsp;</p> </div>

opencc-by-4.0Apr 2024View details →
zenodo48/100

Comparison of high-resolution global canopy height maps and their applicability to biodiversity modelling - dataset

<p>This repository was created to provide datasets related with an article comparing high-resolution global canopy height maps and exploring their applicability to biodiversity modeling in temperate biomes.</p> <p>EBR stands for Entlebuch Biosphere Reserve, MRF stands for Mount Richmond Forest and TAW stands for Trinity Alps Wilderness.</p> <p>The original airborne laser scanning point clouds used&nbsp;for the generation of the canopy height models&nbsp;were sourced from the LINZ Data Service and OpenTopography, and licensed for reuse under the CC BY 4.0 licence (<a href="https://mcas-proxyweb.mcas.ms/certificate-checker?login=false&amp;originalUrl=https%3A%2F%2Fdoi.org.mcas.ms%2F10.5069%2FG97D2SB0%3FMcasTsid%3D20893&amp;McasCSRF=cf3ae9aed6f2016d3ceedda452d422646f4f8e5a5e6270380b370aad4964323a">https://doi.org/10.5069/G97D2SB0</a>);&nbsp;Federal Office of Topography swisstopo&nbsp;(<a href="https://mcas-proxyweb.mcas.ms/certificate-checker?login=false&amp;originalUrl=https%3A%2F%2Fwww.swisstopo.admin.ch.mcas.ms%2Fen%2Fgeodata%2Fheight%2Fsurface3d.html%3FMcasTsid%3D20893&amp;McasCSRF=cf3ae9aed6f2016d3ceedda452d422646f4f8e5a5e6270380b370aad4964323a">https://www.swisstopo.admin.ch/en/geodata/height/surface3d.html</a>); and&nbsp;U.S. Geological Survey&nbsp;(<a href="https://mcas-proxyweb.mcas.ms/certificate-checker?login=false&amp;originalUrl=https%3A%2F%2Fapps.nationalmap.gov.mcas.ms%2Fdownloader%2F%3FMcasTsid%3D20893&amp;McasCSRF=cf3ae9aed6f2016d3ceedda452d422646f4f8e5a5e6270380b370aad4964323a">https://apps.nationalmap.gov/downloader/</a>).</p> <p>The Global Forest Canopy Height Map - GFCH (Potapov et al. 2021; https://glad.umd.edu/dataset/gedi) and the high-resolution canopy height model of the Earth -&nbsp;HRCH&nbsp;(Lang et al. 2022, https://langnico.github.io/globalcanopyheight/) are provided free of charge, without restriction of use under Creative Commons Attribution 4.0 International License. Publications, models, and data products that make use of these datasets must include proper acknowledgement.</p> <p><em>P. Potapov, X. Li, A. Hernandez-Serna, A. Tyukavina, M.C. Hansen, A. Kommareddy, A. Pickens, S. Turubanova, H. Tang, C.E. Silva, J. Armston, R. Dubayah, J. B. Blair, M. Hofton (2021) Mapping and monitoring global forest canopy height through integration of GEDI and Landsat data. Remote Sensing of Environment, 112165.&nbsp;<a href="https://doi.org/10.1016/j.rse.2020.112165">https://doi.org/10.1016/j.rse.2020.112165</a></em></p> <p><em>Lang, N., Jetz, W., Schindler, K., &amp; Wegner, J. D. (2022). A high-resolution canopy height model of the Earth. arXiv preprint arXiv:2204.08322.</em></p> <p>R scripts related with this datasets are available at Github (https://github.com/lukasgabor/Comparison-of-high-resolution-global-canopy-height-maps-and-their-applicability;&nbsp;<a href="https://doi.org/10.5281/zenodo.7332716">DOI: 10.5281/zenodo.7332716</a>)</p> <p>In the previous version (1.0) the average was calculated for the canopy height. In this version (1.1), the maximum height is calculated for the canopy height.</p>

opencc-by-4.0Mar 2023View details →
edi48/100

Native tree growth and reproduction in response to reduction in the coconut palm (Cocos nucifera) canopy at Palmyra Atoll

These data describe competition for light (open solar path) between introduced coconut palm trees (Cocos nucifera) and native tree species between 2004 and 2008 at Palmyra Atoll, Northern Line Islands, Pacific Ocean. Data are contained in one table, including values from the start, end, and intermediate samples. The dataset measures the change in tree growth (DBH and height) and reproductive potential (flower and fruit production) in relation to time and open solar path value. Two treatments are considered: OSP values less than 50% created by C. nucifera removal, and OSP values greater than 50%.

openCC (other)Feb 2022View details →
edi48/100

Tree species, diameter, and canopy class records for 4-paired plots in Black Rock Forest, NY, since 1931.

Black Rock Forest maintains eight long-term forest monitoring plots in Cornwall, NY. Four pairs of plots were established in 1931 to compare thinning treatments to nearby control plots. Four plots are approximately 0.25 acres and the other four are 0.1 acres. Tree species, diameter at breast height, height and canopy class have been measured on all stems greater than 1 inch in diameter since 1931. Plots were revisited every five years until the 1990s and annually after 1994.

openCC (other)Jan 2026View details →
edi48/100

Understory percent cover, plant traits, canopy LAI, PAR, temperature, and soil moisture data at multiple time points for sites in the burn chronosequence and Indian Point forest at the University of Michigan Biological Station, Pellston, MI (2022-2023)

Community ecology has sought to understand the mechanisms by which plant communities are assembled through time and space. One prominent way to address how communities are assembled is by quantifying functional traits. While there is a tremendous body of literature on functional traits, debate persists about how to account for variation in measured traits. For example, intraspecific trait variation (ITV) can be equal to or greater than interspecific trait variation and ITV has also been found to vary greatly across years. Therefore, there is a need to account for variability in functional trait measures among and within species and through time to improve our understanding of community assembly. Chronosequences are a powerful tool to address temporal changes in community dynamics, however, the inclusion of understory plants in forest chronosequence studies is still relatively uncommon. Previous chronosequence studies have been primarily performed in grasslands or in a limited subset of forest types, so further work is needed in understory plant traits across other ecosystems and climates to improve trait-based understanding of understory plant communities through time. Additionally, because plant traits change as ecosystems age, community interactions are likely to change with ecosystem age. Interactions of particular interest are herbivory, arthropod predation, and the influence of plant traits on arthropod diversity.

openCC (other)Nov 2024View details →
edi48/100

UCSB SONGS Mitigation Monitoring: Wetland Performance Standard - Spartina Canopy

These data describe annual estimates of Spartina foliosa canopy architecture (measured as proportion of stems > 3 ft long) from four locations at two coastal wetlands as part of the SONGS San Dieguito Wetland Restoration mitigation monitoring program to track long-term patterns in Spartina size structure. This study began in 2012 in the San Dieguito Wetlands and Tijuana Estuary in San Diego County, CA. Beginning in 2024, Tijuana Estuary was replaced with Mugu Lagoon in Ventura County, CA.

openCC (other)Jun 2025View details →
edi48/100

Advanced Resolution Canopy FLOw (ARCFLO) experiment employing the SUbcanopy Sonic Anemometer Network (SUSAN) in WS01 of the HJ Andrews Experimental Forest, July-September 2012

This dataset was collected during one of the ARCFLO (Advanced Resolution Canopy FLOw) experiment series’ field campaigns. This field campaign was carried out in WS1 of the HJ Andrews Experimental forest during July-September 2012 by the biomicrometeorology group, PI Christoph Thomas. The ARCFLO experiment series spanned a wide range of topographic conditions (flat, sloped, mountainous) and canopy architectures (grassland, orchard, open forest, dense forest) and was carried out between 2011 and 2014. It was funded through the NSF Career Award in Physical and Dynamical Meteorology to PI Christoph Thomas. The main goal of this project was to develop a novel improved framework to describe the airflow and its transport under weak-wind conditions for a continuous variation of overstory density and stratification. The objective is to i) identify forcing mechanisms of submeso motions, ii) evaluate the impact of plant canopies of different overstory density on the wind, temperature, and humidity fields, and iii) improve predictors for mixing in plant canopies that incorporate the important physical mechanisms. Observations were be made with a unique combination of new and standard techniques including optical fiber measurement of temperature structure, acoustic remote sensing, ultrasonic anemometers, and laser-illuminated flow visualizations.

openCC0Jun 2017View details →
edi48/100

Vertical tree air temperature measurements within the canopy of the HJ Andrews Experimental Forest, 2011-2019

Vertical air temperature from 11 trees in the Andrews Forest has been collecting beginning in 2011. The trees are at a variety of elevations and are of various species and ages. The 11 trees were selected form the H.J Andrews phenology study air temperature network (MS045). This study examines air temperatures at multiple heights in each tree. The first sensor is at 1.5 m and subsequent sensors measure every 5 m up the tree. Each sensor includes a light (illumination) sensor, which can be used to assess the value of the data. This is not a measurement of the actual light conditions.

openCC (other)Feb 2020View details →
edi48/100

Anaktuvuk River fire scar canopy reflectance spectra from the 2008-2014 growing seasons, North Slope Alaska.

The Anaktuvuk River Fire occurred in 2007 on the North Slope of Alaska. In 2008, three eddy covariance towers were established at sites represent ing unburned tundra, moderately burned tundra, and severely burned tundra. During the 2008-2014 growing seasons, canopy vegetation within the footprint of each of these towers was scanned with a handheld spectrophotometer several times throughout the growing season. Average reflectance spectra per site and collection day are presented here.

openCC (other)Dec 2015View details →
edi48/100

Vegetation indices calculated from canopy reflectance spectra at four sites along Imnavait Creek, AK during the 2008-2010 growing seasons.

A spectrophotometer was used to scan the canopy vegetation at four sites along Imnavait Creek in the Kuparuk Watershed near Toolik Lake LTER, Alaska. The resulting reflectance spectra were used to calculate average vegetation indices for each site and collection day.

openCC (other)Jan 2020View details →
edi48/100

Soil and canopy temperature data from the Arctic LTER Moist Acidic Tussock Experimental plots (MAT89) from 2012 to 2018, Toolik Field Station, North Slope, Alaska

Soil and canopy temperature data from the Arctic LTER 1989 Moist Acidic Tussock Experimental plots(MAT89). The station was established in 1990 in block 2 of a 4 block random block design. The plots are located on a hillside near Toolik Lake, Alaska (68 38' N, 149 36'W). Treatments include - control (CT), greenhouse (GH), greenhouse plus nitrogen and phosphorus (GHNP) shade (SH), shade plus nitrogen and phosphorus (SHNP) and nitrogen and phosphorus (NP). Profiles include above and within canopy, 10, 20 and 40 centimeter soil depths. Not all treatments have a complete profile. Meteorological data was also collected but are included in a separate data set.

openCC (other)Jan 2020View details →
edi48/100

Residential housing segregation and urban tree canopy in 37 US Cities; data in support of Locke et al 2021 in npj Urban Sustainability

Our goal in this paper is to examine whether there are similar patterns in the distribution of tree canopy by Home Owners’ Loan Corporation (HOLC) graded neighborhoods across 37 cities. A pre-print of the paper can be found here: https://osf.io/preprints/socarxiv/97zcs This data packages contains: 1. City-specific file geodatabases with features classes of the HOLC polygons obtained from the Mapping Inequality Project https://dsl.richmond.edu/panorama/redlining/, and tables summarizing tree canopy, and in some cases other land cover classes. 2. An *.R script that replicates all of the analyses, graphs, and tables in the paper. Other double checks, exploratory, and miscellaneous outputs are created by the script too as a bonus. Everything in the paper can be done with the script; additional work outputs are also created. 3. A *.csv file containing city, the HOLC grade, and the percent tree canopy cover. This can be used to create the main findings of the paper and this flat file is provided as an alternative to running the R script to extract information from the geodatabases, combine, and analyze them. The intention is that this file is more widely accessible; the underlying information is the same. Redlining was a racially discriminatory housing policy established by the federal government’s Home Owners’ Loan Corporation (HOLC) during the 1930s. For decades, redlining limited access to homeownership and wealth creation among racial minorities, contributing to a host of adverse social outcomes, including high unemployment, poverty, and residential vacancy, that persist today. While the multigenerational socioeconomic impacts of redlining are increasingly understood, the impacts on urban environments and ecosystems remains unclear. To begin to address this gap, we investigated how the HOLC policy administered 80 years ago may relate to present-day tree canopy at the neighborhood level. Urban trees provide many ecosystem services, mitigate the urban heat island effect

openCC (other)Dec 2020View details →
edi48/100

Tree survey:Effects of Long Term Fertilization and Oak Canopy Cover on Plant Communities and Ecosystem Processes

In 1996 E142 was established in field D on top of the E004 macroplots. E004 was conducted in fields A, B, C and D by Dave Tilman. The purpose of E004 was to see what effect NH4NO3 addition has on large areas over a longer period of time with exposure to naturally-occurring levels of herbivory. The nutrient addition treatments in E004, E142 plots have been applied annually since 1982. These experiments, along with others at Cedar Creek, examine the community and ecosystem consequences of chronic nutrient loading.

openCC0Aug 2025View details →
edi48/100

Canopy litter biomass:Effects of Long Term Fertilization and Oak Canopy Cover on Plant Communities and Ecosystem Processes

In 1996 E142 was established in field D on top of the E004 macroplots. E004 was conducted in fields A, B, C and D by Dave Tilman. The purpose of E004 was to see what effect NH4NO3 addition has on large areas over a longer period of time with exposure to naturally-occurring levels of herbivory. The nutrient addition treatments in E004, E142 plots have been applied annually since 1982. These experiments, along with others at Cedar Creek, examine the community and ecosystem consequences of chronic nutrient loading.

openCC0Aug 2025View details →
edi48/100

Herbaceous Vegetation Survey:Effects of Long Term Fertilization and Oak Canopy Cover on Plant Communities and Ecosystem Processes

In 1996 E142 was established in field D on top of the E004 macroplots. E004 was conducted in fields A, B, C and D by Dave Tilman. The purpose of E004 was to see what effect NH4NO3 addition has on large areas over a longer period of time with exposure to naturally-occurring levels of herbivory. The nutrient addition treatments in E004, E142 plots have been applied annually since 1982. These experiments, along with others at Cedar Creek, examine the community and ecosystem consequences of chronic nutrient loading.

openCC0Sep 2025View details →
edi48/100

Percent cover, species richness, and canopy height data of seagrass communities in Shark Bay, Western Australia, with accompanying abiotic data, from October 2012 to July 2013

This dataset provides cover, canopy height, and species richness estimates for seagrass communities throughout Shark Bay, as well as ancilliary physical data. These data will be used to determine spatial patterns of seagrass loss and recovery, as well as recovery rates and succisional changes in community composition, if present.

openCC (other)Oct 2019View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record