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70 results for “Forest Environment”

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zenodo28/100

Fig. 7 in Red wood Ants (Formica rufa-group) prefer mature pine forests in Variscan granite environments (Hymenoptera: Formicidae)

Fig. 7 – Density plots of RWA nests in a, MG, b, FB study area and c, tectonic stress directions in the study areas (yellow; © World Stress Map 2016; Heidbach et al. 2016).

opencc-by-4.0May 2022View details →
dryad28/100

Data from: Roles of pathogens on replacement of tree seedlings in heterogeneous light environments in a temperate forest: a reciprocal seed sowing experiment

Open the record for dataset details and reuse information.

publicMar 2016View details →
dryad28/100

Data from: The role of transcriptomes linked with responses to light environment on seedling mortality in a subtropical forest, China

Open the record for dataset details and reuse information.

publicMay 2017View details →
dryad28/100

Data from: Fire evolution in the radioactive forests of Ukraine and Belarus: future risks for the population and the environment

Open the record for dataset details and reuse information.

publicOct 2014View details →
dryad28/100

Data from: Roles of pathogens on replacement of tree seedlings in heterogeneous light environments in a temperate forest: a reciprocal seed sowing experiment

Open the record for dataset details and reuse information.

publicFeb 2017View details →
dryad28/100

Data from: Genotype-environment mismatch of kelp forests under climate change

Open the record for dataset details and reuse information.

publicMay 2021View details →
zenodo24/100

Multimodal Sensor Dataset from a Forest Environment in Adões using a Unitree Go1 Platform equipped with a Robosense BPearl LiDAR

<p><strong>Dataset Description:</strong></p> <p>This dataset was collected using a Unitree Go1 robot equipped with multiple sensors:</p> <ul> <li><strong>LiDAR Data:</strong> Acquired from a Robosense Bpearl.</li> <li><strong>IMU Data:</strong> Available through the <code>/high_state</code> topic published by the Unitree Go1.</li> <li><strong>RGB Images:</strong> Captured using a Realsense D435i camera.</li> </ul> <p>To process this dataset, you will need the <code>Unitree_transformer.py</code> Python script, available at the provided <a href="https://github.com/pedrotomas27/python_executables/tree/252ecf0feb9c3e8652daa2e6def7f4c94667207e">URL</a>, along with the necessary <a href="https://github.com/unitreerobotics/unitree_legged_sdk">Unitree package</a>.</p> <p><strong>Note:</strong> The transform for the LiDAR sensor is not included in the rosbag. To include it, manually add the following static transform to your ROS setup:<br>&lt;node pkg="tf" type="static_transform_publisher" name="rslidar_broadcaster" args="0.15 0 0.13 0 0.309017 0 base rslidar 0.1" /&gt;<br><br><strong>Important:</strong> There was a camera malfunction midway through the dataset collection.</p>

opencc-by-4.0Sep 2024View details →
zenodo24/100

Multimodal Sensor Dataset from a Forest Environment in Adões using a Unitree Go1 Platform equipped with a Velarray M1600 LiDAR

<p><strong>Dataset Description:</strong></p> <p>This dataset was collected using a Unitree Go1 robot equipped with various sensors:</p> <ul> <li><strong>LiDAR Data:</strong> Captured with a Velodyne Velarray M1600.</li> <li><strong>IMU Data:</strong> Available via the <code>/high_state</code> topic published by the Unitree Go1.</li> <li><strong>RGB Images:</strong> Streamed from a Realsense D435i camera.</li> </ul> <p>To process this dataset, you will need the <code>Unitree_transformer.py</code> Python script, which can be found at the provided <a href="https://github.com/pedrotomas27/python_executables/tree/252ecf0feb9c3e8652daa2e6def7f4c94667207e">URL</a>. Ensure that the <a href="https://github.com/unitreerobotics/unitree_legged_sdk">Unitree package</a> is also installed.</p> <p><strong>Note:</strong> The LiDAR transform is not included in the rosbag file. To incorporate this transform, manually add the following static transform to your ROS setup:<br><br>&lt;node pkg="tf" type="static_transform_publisher" name="lidar_0_broadcaster" args="0.15 0 0.13 0 0 0 base lidar_0 0.1" /&gt;<br><br></p>

opencc-by-4.0Sep 2024View details →
zenodo24/100

Dataset for "Fluorescence of solvent-extractable organics in sub-micrometer forest aerosols in Hokkaido, Japan, Atmos. Environ."

<p>This dataset is for &ldquo;Fluorescence of solvent-extractable organics in sub-micrometer forest aerosols in Hokkaido, Japan&rdquo; by Afsana et al. in Atmospheric Environment. &nbsp;The contents are described in the sheet &ldquo;readme&rdquo; of the Excel file named &ldquo;Dataset_sonia2023323.xlsx&rdquo;. The excitation&ndash;emission matrix (EEM) spectra of OA extracts in solutions were measured using a fluorescence spectrophotometer (FP-6600, JASCO) using a 1-cm path length quartz cell. The ranges of the excitation and emission wavelengths were 220&ndash;500 nm and 250&ndash;650 nm, respectively. drEEM toolbox (version 0.2.0) for MATLAB (http://www.models.life.ku.dk/dreem) was used to preprocess the EEMs and to perform parallel factor (PARAFAC) analysis. The details of the analysis of the mass concentrations and the ion groups of OA extracts were reported in Afsana et al. (2022). The details of the analysis of the mass concentrations of biogenic molecular tracers were reported in M&uuml;ller et al. (2017). The dataset was obtained under the support by JSPS KAKENHI Grant Numbers JP19H04253 and JP25281002.</p> <p>Afsana, S., Zhou, R., Miyazaki, Y., Tachibana, E., Deshmukh, D. K., Kawamura, K., and Mochida, M.: Fluorescence of solvent-extractable organics in sub-micrometer forest aerosols in Hokkaido, Japan, Atmos. Environ.</p> <p>Afsana, S., Zhou, R., Miyazaki, Y., Tachibana, E., Deshmukh, D. K., Kawamura, K., and Mochida, M.: Abundance, chemical structure, and light absorption properties of humic-like substances (HULIS) and other organic fractions of forest aerosols in Hokkaido, Sci. Rep., 12, 14379, 2022.</p> <p>M&uuml;ller, A., Miyazaki, Y., Tachibana, E., Kawamura. K., and Hiura, T.: Evidence of a reduction in cloud condensation nuclei activity of water-soluble aerosols caused by biogenic emissions in a cool-temperate forest, Sci. Rep., 7, 1&minus;9, 2017.</p>

opencc-by-4.0Mar 2023View details →
geo16/100

Ecophysiological and molecular basis of drought responses in forest trees: the modulating role of canopy structure and light environment

GEO Series GSE208073. Abies pinsapo. 12 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenJul 2022View 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