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13 results for “tree health”
Tree Health Conditions (mortality, damage, disease, bark beetles) in Fuel Reduction Treatments Located Near Communities in Interior Alaska and the Cook Inlet Region of Alaska - Observations from July-August 2023
This dataset contains tree-, transect-, and site-level observations of forest stands at sites that received a fuel reduction treatment. Tree-level observations include species, diameter, living status, damage, disease, and bark beetle presence. Transect-level observations include level of coarse woody debris and bark beetle presence. Sites are categorized by region (recent/ongoing spruce beetle oubreak or endemic spruce beetle population levels) and treatment type (hand-thinned or mechanincally felled and masticated). These observations are from July-August 2023. Sites are located near communities in Interior Alaska and the Cook Inlet Region.
Data for estimating spruce tree health using drone-based RGB and multispectral imagery
<p>The dataset contains multispectral and RGB orthomosaics (.tif), and photogrammetric point clouds (.laz) of four study areas (about 25 ha each), where bark beetle-related decline of Norway spruce has been observed in Helsinki, Finland. The filenames refer to Area 1 (Männikkötie), Area 2 (Maunulanmaja), Area 3 (Hakuninmaa), and Area 4 (Paloheinä), described in detail in Junttila et al. 2022. Multispectral Imagery Provides Benefits for Mapping Spruce Tree Decline Due to Bark Beetle Infestation When Acquired Late in the Season, Remote Sensing 14(4), 909: <a href="https://doi.org/10.3390/rs14040909">https://doi.org/10.3390/rs14040909</a> </p> <p>The image data was acquired between 11th and 14th September 2020.</p> <p>RE = Red-Edge M multispectral data<br>RGB = RGB data (Phantom 4 Pro)<br>Altum = Altum multispectral data</p> <p>The ground sampling distances (GSD) were approximately 3 cm, 5 cm, and 8 cm for RGB, Altum, and RedEdge, respectively.</p> <p>The field reference data file contains 556 geolocated trees assessed in the field (between 11.9. and 17.9.2020), of which 203 were dead and 353 were alive. The data is in polygon format, representing the crown delineation done during the data processing. The file includes tree heights estimated from airborne laser scanning data, dbh (for a subset of trees), discoloration, defoliation, resin flow, bark structural damage, and canopy size estimates. More details are in the journal article mentioned above.</p> <p>Key for Field Reference:</p> <p>Z = tree height<br>dbh = diameter-at-breast-height (cm)<br>vari = Discoloration (score 0-5)<br>harsu = Defoliation (score 0-4)<br>pihka = Resin flows (score 0-2)<br>runko = Stem/bark structural damage (score 0-2)<br>latvus = Significantly decreased canopy size (score 0-1)</p>
Tree species identity, diameter and qualitative canopy health measurements (full, partial or dead) from 2005 to 2023 on 12 experimental oak loss plots in Black Rock Forest, NY.
Black Rock Forest established a series of 12, 0.56 ha plots in 2005 to assess impacts of the loss of tree in the genus Quercus on the forest ecosystem (entitled the Future of Oak Forests experiment). Three trunk girdling treatments, with control plots were instituted in 2008. Each plot also contained an ~10m by ~15m deer exclosure to assess the impact of herbivory post-disturbance. Trees were measured twice per year from 2008 to 2013 (except 2009 when trees were measured once) and once per year from 2014 to 2023. Data include tree species identity, diameter at breast height (DBH), canopy health (a qualitative assessment of approximate cover as full, partial or dead), presence/absence of sprouts, and location within the plot. All live trees equal to or larger than 2.5 cm DBH are included in the dataset.
A dataset of 5 million city trees from 63 US cities: species, location, nativity status, health, and more.
<p>Sustainable cities depend on urban forests. City trees -- a pillar of urban forests -- improve our health, clean the air, store CO2, and cool local temperatures. Comparatively less is known about urban forests as ecosystems, particularly their spatial composition, nativity statuses, biodiversity, and tree health. Here, we assembled and standardized a new dataset of N=<span>5,660,237</span> trees from 63 of the largest US cities. The data comes from tree inventories conducted at the level of cities and/or neighborhoods. Each data sheet includes detailed information on tree location, species, nativity status (whether a tree species is naturally occurring or introduced), health, size, whether it is in a park or urban area, and more (comprising 28 standardized columns per datasheet). This dataset could be analyzed in combination with citizen-science datasets on bird, insect, or plant biodiversity; social and demographic data; or data on the physical environment. Urban forests offer a rare opportunity to intentionally design biodiverse, heterogenous, rich ecosystems.</p>
A dataset of 5 million city trees from 63 US cities: species, location, nativity status, health, and more.
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Data from: Current inequality and future potential of US urban tree cover for reducing heat-related health impacts
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Long-term effects of intercropping on multi-trophic structure and bio-thermodynamic health of mixed Eucalyptus-native tree plantations
<p><span>1. </span><span>The intercropping approach of <em>Eucalyptus</em> and native trees has been widely recommended, as an ideal replacement for monoculture <em>Eucalyptus</em> plantations (EUs), to ameliorate global biodiversity loss and mitigate environmental change. However, both suitable native tree species and the best intercropping ratio between <em>Eucalyptus</em> and native trees have not been determined. </span></p> <p><span>2. </span><span>To fill this gap, a four-level intercropping gradient of <em>Eucalyptus urophylla</em> planted with eight native tree species was set up (i.e., 20%NS, 30%NS, 40%NS, 50%NS), monitored and compared to a monoculture <em>E. urophylla</em> plantation (EU) and a randomly mixed plantation of nine native tree species (NS) in southern China. </span></p> <p><span>3. </span><span>The results showed that the intercropping ratio of <em>Eucalyptus</em> and native trees had a long-term effect on tree layer structure and health status and a cascading effect on the thermodynamic health state of soil microbes. Shade-tolerant woody species are more suitable for intercropping with <em>Eucalyptus</em>. Intercropping plantations with not less than 30% native trees were more favorable for long-term survival and growth of both planted <em>Eucalyptus</em> and native trees and provided much more favorable conditions for the natural immigration of other native trees, which leads to a healthy plant community with significantly higher eco-exergy compared to EU. The initial mixing ratio between <em>Eucalyptus</em> and high diversity native trees affected soil fertility through its long-term effects on the biodiversity and bio-thermodynamic state of trees and soil microbes.</span></p> <p><span>4. </span><span><em>Synthesis and applications</em>.</span><span> Our results highlight the long-term positive effect of the intercropping ratio of <em>Eucalyptus</em> and high diversity native trees on multi-trophic biodiversity conservation, bio-thermodynamic health development, and soil fertility conservation. In the conversion of monoculture <em>Eucalyptus</em> plantations (EU) to multi-species plantations, it is recommended to mix more than 30% native tree species that have different ecological niches with <em>Eucalyptus</em>.</span></p>
Data and code from: A spectral three-dimensional color space model of tree crown health
<p>Protecting the future of forests in the United States and other countries depends in part on our ability to monitor and map forest health conditions in a timely fashion to facilitate management of emerging threats and disturbances over a multitude of spatial scales. Remote sensing data and technologies have contributed to our ability to meet these needs, but existing methods relying on supervised classification are often limited to specific areas by the availability of imagery or training data, as well as model transferability. Scaling up and operationalizing these methods for general broadscale monitoring and mapping may be promoted by using simple models that are easily trained and projected across space and time with widely available imagery. Here, we describe a new model that classifies high resolution (~1 m<sup>2</sup>) 3-band red, green, blue (RGB) imagery from a single point in time into one of four color classes corresponding to tree crown condition or health: green healthy crowns, red damaged or dying crowns, gray damaged or dead crowns, and shadowed crowns where the condition status is unknown. These Tree Crown Health (TCH) models trained on data from the United States (US) Department of Agriculture, National Agriculture Imagery Program (NAIP), for all 48 States in the contiguous US and spanning years 2012 to 2019, exhibited high measures of model performance and transferability when evaluated using randomly withheld testing data (<em>n</em> = 122 NAIP state x year combinations; median overall accuracy 0.89-0.90; median Kappa 0.85-0.86). We present examples of how TCH models can detect and map individual tree mortality resulting from a variety of nationally significant native and invasive forest insects and diseases in the US. We conclude with discussion of opportunities and challenges for extending and implementing TCH models in support of broadscale monitoring and mapping of forest health.</p>
Long-term effects of intercropping on multi-trophic structure and bio-thermodynamic health of mixed Eucalyptus-native tree plantations
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Data and code from: A spectral three-dimensional color space model of tree crown health
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Tree health analysis in the Phoenix Metropolitan Area
Urban trees contribute significantly to human health and environmental quality but assessments of their health are rare. This project involved developing an urban tree health monitoring protocol for use in the Southwestern US and using it to conduct field assessments of urban tree health in the Phoenix urban ecosystem during the winter/spring of 2006. Field manuals prepared by the USDA Forest Service for use in monitoring urban forest health (Cumming et al. 2001) were adapted to reflect the unique stresses and diseases that occur in urban areas in the southwestern US. Tree health was then assessed using a subset of field plots that have been established as part of the Survey 200 project and NPP intensive monitoring project as a foci. Ten to fifteen trees were assessed at each site for general tree health including canopy condition, canopy dieback and disease and pest problems. Abiotic problems were also assessed including stress problems, nutrient deficiency symptoms, improper pruning practices, trunk damage and girdling.
A Clinical Evaluation of Pine Trees Health Test System Including the Pine Trees Health Reader and COVID-19 Test for Point-of-Care
ClinicalTrials.gov study NCT05107258. IPD Sharing: NO. Countries: 1. Publications: 0.
Data and Script for: Olive Trees Health and Yield Prediction through EO data and Machine Learning (OLEA-PRED) / EO AFRICA – Research and Development Facility
<p>This database was collected under the "Olive Trees Health and Yield Prediction through EO data and Machine Learning" project, funded by the European Space Agency in the framework of the "EO AFRICA R&D Facility".</p> <p>- Shapefiles.rar contains shp files for Orchads boundaries and tree locations.</p> <p>- Field_data contains data collected in the field (Chllorophyl, Yield and Soil ).</p> <p>- SCRIPTS.rar contains all scripts and extracted data used for prediction for Settat orchad.</p> <p>- FBS images.rar contains UAV and M6 images for Fkih Ben Saleh orchad.</p>
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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.