Researchdata.se
Not a member yet
    6142 research outputs found

    Vascular plants and bryophytes in heathlands in the Bale mountains, Ethiopia

    No full text
    This dataset consists of records of vascular plants and bryophytes from 48 plots of 5 x 5 m in heathland vegetation. The plots were laid out in sites with different time since fire and were inventoried in autumn 2015. The vascular plants are recorded as rare or common in each plot. Bryophyte data just consist of presence data. Voucher specimens of the bryophytes are deposited at the National Herbarium in Addis Ababa

    Atmospheric CO2 product from Hyltemossa (70.0 m)

    No full text
    Atmospheric CO2 concentrations, both ICOS and non-/pre-ICOS data, delivered by the Atmospheric Thematic Center Heliasz, M., Biermann, T. (2025). Atmospheric CO2 product from Hyltemossa (70.0 m), 2016-12-13–2025-03-31, European ObsPack, https://hdl.handle.net/11676/-5xpgaVhhAUQxSQCwh2DcHQ

    Atmospheric CH4 product from Svartberget (35.0 m)

    No full text
    Atmospheric CH4 concentrations, both ICOS and non-/pre-ICOS data, delivered by the Atmospheric Thematic Center Larmanou, E., Marklund, P., Ottosson-Löfvenius, M., Smith, P. (2025). Atmospheric CH4 product from Svartberget (35.0 m), 2017-05-31–2025-03-31, European ObsPack, https://hdl.handle.net/11676/gjzz26yYrGltcwiQlB0WcM0

    Atmospheric CO2 product from Hyltemossa (150.0 m)

    No full text
    Atmospheric CO2 concentrations, both ICOS and non-/pre-ICOS data, delivered by the Atmospheric Thematic Center Heliasz, M., Biermann, T. (2025). Atmospheric CO2 product from Hyltemossa (150.0 m), 2016-12-13–2025-03-31, European ObsPack, https://hdl.handle.net/11676/OFyzNFFL7xH3EUeV5mtKoyQ

    Atmospheric CO2 product from Svartberget (150.0 m)

    No full text
    Atmospheric CO2 concentrations, both ICOS and non-/pre-ICOS data, delivered by the Atmospheric Thematic Center Larmanou, E., Marklund, P., Ottosson-Löfvenius, M., Smith, P. (2025). Atmospheric CO2 product from Svartberget (150.0 m), 2017-05-31–2025-03-31, European ObsPack, https://hdl.handle.net/11676/uQQQloydm5Mf275OIIxs_16

    Phenocam - Region Of Interest (ROI) Time Series from Grimsö Research Area

    No full text
    Daily aggregated time series containing solar-weighted mean vegetation indices and RGB channel values per Region of Interest, temporal data, solar metrics, and processing statistics for each daily composite. Grimsö Wildlife Research Station (2025). Phenocam - Region Of Interest (ROI) Time Series from Grimsö Research Area, 2020-03-03–2024-11-02 [Data set]. Swedish Infrastructure for Ecosystem Science (SITES). https://hdl.handle.net/11676.1/Aq-j5f9Bp_fGhjp6vcXpE32

    Phenocam - Region Of Interest (ROI) Time Series from Svartberget Experimental Forest, Mast 70m Phenocam 01

    No full text
    Daily aggregated time series containing solar-weighted mean vegetation indices and RGB channel values per Region of Interest, temporal data, solar metrics, and processing statistics for each daily composite. Svartberget Research Station (2025). Phenocam - Region Of Interest (ROI) Time Series from Svartberget Experimental Forest, Mast 70m Phenocam 01, 2019-05-06–2025-05-29 [Data set]. Swedish Infrastructure for Ecosystem Science (SITES). https://hdl.handle.net/11676.1/GDUSsXTyp9CjdyhIfaJANAd

    Phenocam - Region Of Interest (ROI) Time Series from Röbäcksdalen Research Area, Mast 4m Phenocam 02

    No full text
    Daily aggregated time series containing solar-weighted mean vegetation indices and RGB channel values per Region of Interest, temporal data, solar metrics, and processing statistics for each daily composite. Röbäcksdalen Field Research Station (2025). Phenocam - Region Of Interest (ROI) Time Series from Röbäcksdalen Research Area, Mast 4m Phenocam 02, 2022-06-13–2025-05-05 [Data set]. Swedish Infrastructure for Ecosystem Science (SITES). https://hdl.handle.net/11676.1/PAdGRZeVbfb8_EvQv6e0xD4

    CT scan images of internal resinwood in Scots pine

    No full text
    Resinwood in Scots pine timber resulting from Cronartium pini infection represents an important quality defect, substantially reducing sawn yield and economic value in sawmilling. This dataset generated from X-ray computed tomography (CT) for non-destructive resinwood detection across wood moisture states. Scots pine specimens exhibiting external cankers were harvested and scanned using an industrial MicroTec CT scanner in both green and dry states, included full logs and 3-cm-thick discs. Comparative density analysis identified regions of interest based on elevated density patterns. The scanner produced data using a cone beam and two angled flat detectors on a helical scanning trajectory. The spatial resolution and resulting voxel dimensions were uniform at 0.3 × 0.3 × 0.3 mm³. The resulting 3D images comprised 16-bit greyscale values representing density in kg/m³ at each location, and helical 1PI Katsevich was used for image reconstruction. Related materials:- Identifier 10.1080/17480272.2025.2536725 - Title X-ray computed tomography-based qualitative analysis of internal resinwood in Scots pine - Identifier Peer Review Journal Article - Relation type Dataset that used for producing the research articl

    Chemical variables - lake from Tarfalasjön, water sample

    No full text
    Manual grab samples for chemical analysis are taken from the lake on a biweekly basis during ice-free conditions, and on a monthly basis during ice cover conditions. At the central lake sampling location water samples are collected from both epi- and hypolimnion during periods of stratification. Tarfala Research Station (2025). Chemical variables - lake from Tarfalasjön, water sample, 2021-08-05–2021-09-13 [Data set]. Swedish Infrastructure for Ecosystem Science (SITES). https://hdl.handle.net/11676.1/rdAVjltd58mYscOhJanKAKg

    0

    full texts

    6,142

    metadata records
    Updated in last 30 days.
    Researchdata.se
    Access Repository Dashboard
    Do you manage Open Research Online? Become a CORE Member to access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard! 👇