Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
189
datasets available to search
ShareScore release 0.9.0
Dataset results
189 results for “Vineyards”
Historical and Ecological GIS Data from Manuel F. Correllus State Forest on Martha’s Vineyard 1830-1994
Sand-plain ecosystems are a priority for conservation because they are uncommon, support numerous rare or uncommon plant and animal species, serve as groundwater recharge areas, and are threatened by land development. The 5,200-acre Manuel F. Correllus State Forest, in the central part of Martha’s Vineyard, is part of one of the larger sand-plain ecosystems in New England. This GIS data package was created as part of a study on the history and ecology of Martha’s Vineyard and the state forest as part of an effort to understand sandplain landscapes and make management recommendations for their maintenance.
Land Cover on the Elizabeth Islands, Martha's Vineyard, and Nantucket 1938
The widespread influence of land use and natural disturbance on population, community, and landscape dynamics and the long-term legacy of disturbance on modern ecosystems requires that a historical, broad-scale perspective become an integral part of modern ecological studies and conservation assessment and planning. In previous studies, the Harvard Forest Long Term Ecological Research (LTER) program has developed an integrated approach of paleoecological and historical reconstruction, meteorological modeling, air photo interpretation, GIS analyses, and field studies of vegetation and soils, to address fundamental ecological questions concerning the rates, direction, and causes of vegetation change, to evaluate controls over modern species and community distributions and landscape patterns, and to provide critical background for conservation and restoration planning. In the current study, we extend this approach to investigate the link between landscape history and the abundance, distribution, and dynamics of species, communities and landscapes of the Cape Cod to Long Island coastal region, including the islands of Martha's Vineyard, Nantucket, and Block Island. The study region includes many areas of high conservation priority that are linked geographically, historically, and ecologically. This dataset includes a land cover GIS layer created from aerial photographs from 1938. Janice Stone interpreted the photos onto acetates which were then redrawn onto USGS topographic maps using a zoom transfer scope to reduce edge distortion from the photographs. The landcover polygons were then digitized into a GIS. As 1938 is near the midpoint between the peak of 19th century agricultural land clearance and the modern plant communities of the region, this data provides valuable information on changing landscape characteristics and vegetation successional patterns which shape the modern landscape.
Lake Sediment Pollen and Charcoal from Black Pond on Martha's Vineyard MA from 9926 BP to Present
Aim We analyzed a dataset composed of multiple palaeoclimate and lake-sediment pollen and charcoal records from New England to explore how postglacial changes in forest composition and spatial patterns of vegetation and fire were controlled by regional-scale climate change, a subregional environmental gradient, and landscape-scale variations in soil characteristics. Location The 120,000-km2 study area includes parts of Vermont and New Hampshire in the north, where sites are 150-200 km from the Atlantic Ocean, and spans the coastline from southeastern New York to Cape Cod and the adjacent islands, including Block Island, the Elizabeth Islands, Nantucket, and Martha’s Vineyard. Results Boreal forest featuring Picea and Pinus banksiana was present across the region when conditions were cool and dry 14,000-12,000 calibrated 14C yrs before present (ybp). Pinus strobus became regionally dominant as temperatures increased between 12,000 and 10,000 ybp. The composition of forests in inland and coastal areas diverged in response to further warming after 10,000 ybp, when Quercus and Pinus rigida expanded across southern New England, while conditions remained cool enough in inland areas to maintain Pinus strobus. Fire severity was high during 10,000-8000 ybp. Increasing precipitation allowed Tsuga canadensis, Fagus grandifolia, and Betula to replace Pinus strobus in inland areas during 9000-8000 ybp, and also led to the expansion of Carya across the coastal part of the region beginning at 7000-6000 ybp. Abrupt cooling at 5500-5000 ybp caused sharp declines in Tsuga in inland areas and Quercus at some coastal sites, and the populations of those taxa remained low until they recovered around 3000 ybp in response to rising precipitation. Throughout most of the Holocene, sites underlain by sandy glacial deposits were occupied by Pinus rigida and Quercus. Main conclusions Postglacial changes in the composition and spatial pattern of New England forests were controlled by long-term t
Lake Sediment Pollen and Charcoal from Uncle Seth's Pond on Martha's Vineyard MA from 13389 BP to Present
Aim We analyzed a dataset composed of multiple palaeoclimate and lake-sediment pollen and charcoal records from New England to explore how postglacial changes in forest composition and spatial patterns of vegetation and fire were controlled by regional-scale climate change, a subregional environmental gradient, and landscape-scale variations in soil characteristics. Location The 120,000-km2 study area includes parts of Vermont and New Hampshire in the north, where sites are 150-200 km from the Atlantic Ocean, and spans the coastline from southeastern New York to Cape Cod and the adjacent islands, including Block Island, the Elizabeth Islands, Nantucket, and Martha’s Vineyard. Results Boreal forest featuring Picea and Pinus banksiana was present across the region when conditions were cool and dry 14,000-12,000 calibrated 14C yrs before present (ybp). Pinus strobus became regionally dominant as temperatures increased between 12,000 and 10,000 ybp. The composition of forests in inland and coastal areas diverged in response to further warming after 10,000 ybp, when Quercus and Pinus rigida expanded across southern New England, while conditions remained cool enough in inland areas to maintain Pinus strobus. Fire severity was high during 10,000-8000 ybp. Increasing precipitation allowed Tsuga canadensis, Fagus grandifolia, and Betula to replace Pinus strobus in inland areas during 9000-8000 ybp, and also led to the expansion of Carya across the coastal part of the region beginning at 7000-6000 ybp. Abrupt cooling at 5500-5000 ybp caused sharp declines in Tsuga in inland areas and Quercus at some coastal sites, and the populations of those taxa remained low until they recovered around 3000 ybp in response to rising precipitation. Throughout most of the Holocene, sites underlain by sandy glacial deposits were occupied by Pinus rigida and Quercus. Main conclusions Postglacial changes in the composition and spatial pattern of New England forests were controlled by long-term t
Early-Holocene Forest at Stonewall Beach on Martha’s Vineyard 10700-9800 BP
Coastal erosion at Stonewall Beach on the island of Martha’s Vineyard, Massachusetts, U.S.A., has exposed a thick layer of peaty sediments rich in botanical remains, including well-preserved tree trunks. We identified the species of the tree trunks based on wood anatomy, analyzed pollen and macrofossils in the sediments, and determined the ages of the tree trunks and peat with 14C dating. The tree trunks were identified as Pinus strobus (white pine), and pollen assemblages featured high percentages of P. strobus in sediments associated with the trunks. The tree trunks and peat dated to ~10,700–9800 calibrated 14C years before present. These findings confirm that Martha’s Vineyard, like other parts of southern New England, was dominated by P. strobus forest during the early Holocene. At that time, regional climate was drier than today and Martha’s Vineyard was not yet isolated from the mainland by postglacial sea-level rise.
Abundance of eukaryote picophytoplankton and Synechococcus from a moored submersible flow cytometer at Martha's Vineyard Coastal Observatory, ongoing since 2003 (NES-LTER since 2017)
This is a decadal-scale time series of the abundance of eukaryote picophytoplankton and Synechococcus at 4 meters depth at the Martha's Vineyard Coastal Observatory, about 3 km south of Katama Beach, Edgartown, Massachusetts, USA. Picophytoplankton were sensed in situ by a submersible flow cytometer (FlowCytobot, or FCB). Sampling frequency was continuous at approximately 20-minute intervals binned to hourly resolution with some exceptions (e.g., winter in some years). This time series is ongoing for Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER).
Event logs from Northeast U.S. Shelf Long Term Ecological Research (NES-LTER) cruises to the Martha's Vineyard Coastal Observatory (MVCO) ongoing since 2017
This package provides a table of cruises to the Martha's Vineyard Coastal Observatory for Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER). The majority of events are single day cruises, however, samples missing an MVCO Event Number were collected on multi-day NES-LTER transect cruises aboard larger research vessels. The same sampling protocols for CTD and bongo collection are used on both cruise types. Sampling frequency is approximately monthly, with NES-LTER sampling ongoing since 2017. Cruises involve collection of water column bottle samples, surface bucket samples, and zooplankton net tow samples, as well as ship-provided data. NES-LTER transect cruises will have more extensive underway and acoustic data which can be found by searching by cruise at https://www.rvdata.us/data. The event number for each cruise is provided, along with date, vessel name, cruise identifier where applicable, link to data location (for CTD, ADCP, and other underway data), and checklist of six data types.
Dataset on UAV RGB videos acquired over a vineyard property of Bodegas Terras Gauda at an early stage of Botrytis cinerea infection in 2021
<p>The videos were collected in a vineyard owned by Bodegas Terras Gauda, in June 2021. The videos were collected with a DJI Matrice 210 RTK UAV, which had a DJI Zenmuse X5S sensor onboard. A total of 4 rows were recorded with side videos. The flights were carried out on a sunny day with wind velocity lower than 0.5 m/s. Annotations of the grape clusters in the MOTS style are provided. </p>
Dissolved inorganic nutrients from the Martha's Vineyard Coastal Observatory (MVCO), including 4 macro-nutrients from water column bottle samples, ongoing since 2003 (NES-LTER since 2017)
Dissolved inorganic nutrients including nitrate + nitrite, ammonium, silicate, and phosphate are measured from water column bottle and bucket samples taken on NES-LTER day cruises in the vicinity of the Martha's Vineyard Coastal Observatory (MVCO). Sampling frequency near MVCO is approximately monthly, ongoing since 2003. Samples were filtered, frozen, then processed at the Woods Hole Oceanographic Institution's Nutrient Analytical Facility. These macro-nutrients are analyzed in seawater using a colorimetric assay in which light absorbance is measured versus known standards, and final concentrations are calculated (in micromole per liter). Each sample may have up to 3 replicates.
Size-fractionated chlorophyll from the Martha’s Vineyard Coastal Observatory (MVCO), ongoing since 2003 (NES-LTER since 2017)
Size-fractionated chlorophyll a and phaeopigments are measured from water column bottle and bucket samples taken on Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) day cruises in the vicinity of the Martha's Vineyard Coastal Observatory (MVCO), as a proxy for phytoplankton biomass. Sampling frequency near MVCO is approximately monthly, ongoing since 2003. Size fractions in addition to whole seawater (>0.7 micron) include <10 and <80 microns. Pigments were analyzed using fluorometers in which fluorescence was measured versus a blank and a standard, and final concentrations were calculated in micrograms per liter (or mg per cubic meter).
Data for "Crop Diversification in Viticulture with Aromatic Plants: Effects of Intercropping on Grapevine Productivity in a Steep-Slope Vineyard in the Mosel Area, Germany"
<p>This dataset is corresponding to an open-access article named "Crop Diversification in Viticulture with Aromatic Plants: Effects of Intercropping on Grapevine Productivity in a Steep-Slope Vineyard in the Mosel Area, Germany" published in Agriculture (https://www.mdpi.com/2077-0472/11/2/95; <a href="https://doi.org/10.3390/agriculture11020095">https://doi.org/10.3390/agriculture11020095</a>), funded by the European Commission Horizon 2020 project Diverfarming [grant agreement 728003]. </p>
AgRob V21 - ROS1.0 Bag dataset acquired with AgRobModel E in Vineyard
<p>This ROS bag was acquired using AgRobModel E (from <a href="http://esctec.pt/en/laboratories/laboratory-of-robotics-and-iot-for-smart-precision-agriculture-and-forestry">Laboratory of Robotics and IoT for Smart Precision Agriculture and Forestry</a> from INESC TEC) in a Portuguese Vineyard, and it has data from:</p> <ul> <li>LiVOX MID 70 LIDAR </li> <li>IMU</li> <li>Odometry</li> </ul> <p>Stored on these topics:</p> <ul> <li> <pre>/camera_info 7663 msgs : sensor_msgs/CameraInfo /cmd_vel 6058 msgs : geometry_msgs/Twist /diagnostics 2060 msgs : diagnostic_msgs/DiagnosticArray (3 connections) /gps_mBase/fix 1277 msgs : sensor_msgs/NavSatFix /gps_mBase/fix_velocity 1277 msgs : geometry_msgs/TwistWithCovarianceStamped /gps_mBase/monhw 255 msgs : ublox_msgs/MonHW /gps_mBase/navclock 1277 msgs : ublox_msgs/NavCLOCK /gps_mBase/navheading 1277 msgs : sensor_msgs/Imu /gps_mBase/navposecef 1277 msgs : ublox_msgs/NavPOSECEF /gps_mBase/navpvt 1277 msgs : ublox_msgs/NavPVT /gps_mBase/navrelposned 1277 msgs : ublox_msgs/NavRELPOSNED9 /gps_mBase/navsat 64 msgs : ublox_msgs/NavSAT /gps_mBase/navstatus 1277 msgs : ublox_msgs/NavSTATUS /gps_rover/fix 1037 msgs : sensor_msgs/NavSatFix /gps_rover/fix_velocity 1037 msgs : geometry_msgs/TwistWithCovarianceStamped /gps_rover/monhw 255 msgs : ublox_msgs/MonHW /gps_rover/navclock 1036 msgs : ublox_msgs/NavCLOCK /gps_rover/navheading 1036 msgs : sensor_msgs/Imu /gps_rover/navposecef 1036 msgs : ublox_msgs/NavPOSECEF /gps_rover/navpvt 1037 msgs : ublox_msgs/NavPVT /gps_rover/navrelposned 1036 msgs : ublox_msgs/NavRELPOSNED9 /gps_rover/navsat 51 msgs : ublox_msgs/NavSAT /gps_rover/navstatus 1036 msgs : ublox_msgs/NavSTATUS /gps_rover/rxmrtcm 7169 msgs : ublox_msgs/RxmRTCM /image_raw/compressed 7651 msgs : sensor_msgs/CompressedImage /imu_um7/data 4886 msgs : sensor_msgs/Imu /imu_um7/mag 4886 msgs : geometry_msgs/Vector3Stamped /imu_um7/rpy 4886 msgs : geometry_msgs/Vector3Stamped /imu_um7/temperature 4886 msgs : std_msgs/Float32 /joy 6973 msgs : sensor_msgs/Joy /livox/lidar 2557 msgs : sensor_msgs/PointCloud2 /rosout 8027 msgs : rosgraph_msgs/Log (4 connections) /rosout_agg 8011 msgs : rosgraph_msgs/Log /tf 2556 msgs : tf2_msgs/TFMessage</pre> <p> </p> </li> </ul> <p>This was acquired under SCORPION project. </p>
Precision viticulture dataset for detailed vineyard mapping composed of geotagged smartphone ground images, phytosanitary status, UAV orthomosaics, 3D point clouds, and RTK GNSS data - Northern Spain, July 2022
<p>This dataset offers a rich multimodal collection of data from vineyards, designed to enhance agricultural research with a focus on vineyard management and disease monitoring. It includes geotagged smartphone ground images in ".7z" format for detailed plant-level analysis, a ".csv" file detailing plants' phytosanitary status for health assessment, UAV-derived 3D Point Clouds and orthomosaics in ".las" and ".tiff" formats for aerial landscape views, and RTK GNSS data in ".shp" format for precise plant geolocations.</p> <p>This dataset can be combined with other datasets to enable a comprehensive view of the vineyards and improve its value:</p> <div> <ul> <li>Ariza-Sentís, Mar, Sergio Vélez, and João Valente. ‘Dataset on UAV RGB Videos Acquired over a Vineyard Including Bunch Labels for Object Detection and Tracking’. <em>Data in Brief</em> 46 (February 2023): 108848. <a href="https://doi.org/10.1016/j.dib.2022.108848">https://doi.org/10.1016/j.dib.2022.108848</a>.</li> <li>Vélez, Sergio, Mar Ariza-Sentís, and João Valente. ‘VineLiDAR: High-Resolution UAV-LiDAR Vineyard Dataset Acquired over Two Years in Northern Spain.’ <em>Data in Brief</em>, October 2023, 109686. <a href="https://doi.org/10.1016/j.dib.2023.109686">https://doi.org/10.1016/j.dib.2023.109686</a>.</li> <li> <div> <div>Vélez, Sergio, Mar Ariza-Sentís, and João Valente. ‘Dataset on Unmanned Aerial Vehicle Multispectral Images Acquired over a Vineyard Affected by Botrytis Cinerea in Northern Spain’. <em>Data in Brief</em> 46 (February 2023): 108876. <a href="https://doi.org/10.1016/j.dib.2022.108876">https://doi.org/10.1016/j.dib.2022.108876</a>.</div> <div> </div> </div> </li> </ul> </div>
UAV-based monocular SLAM video datasets in vineyards with RTK ground truth
<p>The dataset provides a UAV-based monocular visual SLAM data, designed to evaluate the potential of using monocular visual SLAM in vineyards. It includes videos in ".mp4" format collected by UAV, and "xlsx" tables which include latitude, longitude, height, speed in x, y and z, comjpass, pitch, roll. The ".xlsx" tables were measured by RTK and can be used as ground truth of UAV trajectory and pose.</p> <p>This dataset can be combined with other datasets to enable a comprehensive view of the vineyards:</p> <p>Vélez S, Ariza-Sentís M, Valente J. EscaYard: Precision viticulture multimodal dataset of vineyards affected by Esca disease consisting of geotagged smartphone images, phytosanitary status, UAV 3D point clouds and Orthomosaics. Data in Brief. 2024 Jun 1;54:110497. <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.dib.2024.110497" target="_blank" rel="noreferrer noopener"><span>https://doi.org/10.1016/j.dib.2024.110497</span></a></p> <p><span>Ariza-Sentís M, Wang K, Cao Z, Vélez S, Valente J. GrapeMOTS: UAV vineyard dataset with MOTS grape bunch annotations recorded from multiple perspectives for enhanced object detection and tracking. Data in Brief. 2024 Jun 1;54:110432. <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.dib.2024.110432" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.dib.2024.110432</a></span></p> <p> </p> <p> </p>
Semantic Segmentation Vineyard Rows
<p>Test dataset for semantic segmentation.<br> The datasets includes 500 RGB - images with the relative single-channel binary masks.</p> <p>Images are taken from the vineyards in Grugliasco - Turin - Piedmont Region -Italy</p> <p> </p> <p><strong>For more info please check out our work <a href="https://arxiv.org/abs/2107.00700">here</a></strong></p>
AgRob V14 Dataset - Vineyards
<p>DS_AG_01</p> <p>Data acquired by Agrob V14 @INESCTEC<br> (NoIR camera without blue filter)<br> - IMU<br> - Monocular Camera<br> - Laser Scan<br> - Raw Data Sensors<br> - Power State</p> <p>48Mb / ROSBag</p> <p>DS_AG_02</p> <p>Data acquired by Agrob V14 @INESCTEC<br> (NoIR camera without blue filter)<br> - IMU<br> - Monocular Camera<br> - Laser Scan<br> - Raw Data Sensors<br> - Power State</p> <p>64Mb / ROSBag</p> <p> </p> <p>DS_AG_03</p> <p>Data acquired by Agrob V15 @UTAD (Morning)<br> (NoIR camera with and without blue filter)<br> - IMU<br> - Monocular Camera<br> - Raw Data Sensors<br> - Power State</p> <p>114Mb / ROSBag</p> <p> </p> <p>DS_AG_04</p> <p> </p> <p>Data acquired by Agrob V15 @UTAD (Morning)<br> (NoIR camera with blue filter)<br> - IMU<br> - Monocular Camera<br> - Raw Data Sensors<br> - Power State</p> <p>1Mb / ROSBag</p> <p>DS_AG_05</p> <p>Data acquired by Agrob V15 @UTAD (Morning)<br> (NoIR camera without blue filter)<br> - IMU<br> - Monocular Camera<br> - Raw Data Sensors<br> - Power State</p> <p>53Mb / ROSBag</p> <p> </p> <p>DS_AG_06</p> <p>Data acquired by Agrob V15 @UTAD (Afternoon)<br> (RGB camera)<br> - IMU<br> - Monocular Camera<br> - Raw Data Sensors<br> - Power State</p> <p>68Mb / ROSBag</p> <p> </p> <p>DS_AG_07</p> <p>Data acquired by Agrob V15 @UTAD (Afternoon)<br> (NoIR camera with blue filter)<br> - IMU<br> - Monocular Camera<br> - Raw Data Sensors<br> - Power State<a href="http://vcriis01.inesctec.pt/datasets/DataSet/AGROB/05_noir_com_filtro_tarde_utad.bag">0</a></p> <p>62Mb / ROSBag</p> <p> </p> <p>DS_AG_08</p> <p>Data acquired by Agrob V15 @UTAD (Afternoon)<br> (NoIR camera without blue filter)<br> - IMU<br> - Monocular Camera<br> - Raw Data Sensors<br> - Power State<a href="http://vcriis01.inesctec.pt/datasets/DataSet/AGROB/06_noir_sem_filtro_tarde_utad.bag">0</a></p> <p>58Mb / ROSBag</p> <p> </p> <p>DS_AG_09</p> <p>Data acquired by Agrob V14 @Quinta das Bateiras (Pinhão)<br> (NoIR camera without blue filter)<br> - IMU<br> - Monocular Camera<br> - Laser Scan<br> - Raw Data Sensors<br> - Power State<br> - CmdVel</p> <p>229Mb / ROSBag</p> <p> </p> <p>DS_AG_10</p> <p>Data acquired by Agrob V14 @Quinta das Bateiras (Pinhão)<br> (NoIR camera without blue filter)<br> - IMU<br> - Monocular Camera<br> - Laser Scan<br> - Raw Data Sensors<br> - Power State<br> - CmdVel<a href="http://vcriis01.inesctec.pt/datasets/DataSet/AGROB/1segunda.bag">1segunda.bag</a>191Mb / ROSBag</p> <p> </p> <p>DS_AG_11</p> <p>Data acquired by Agrob V14 @Quinta das Bateiras (Pinhão)<br> (NoIR camera without blue filter)<br> - IMU<br> - Monocular Camera<br> - Laser Scan (Partial)<br> - Raw Data Sensors<br> - Power State<br> - CmdVel</p> <p>1.4Gb / ROSBag</p> <p> </p> <p>DS_AG_12</p> <p>Data acquired by Agrob V14 @Quinta das Bateiras (Pinhão)<br> (NoIR camera without blue filter)<br> - IMU<br> - Monocular Camera<br> - Laser Scan<br> - Raw Data Sensors<br> - Power State<br> - CmdVel</p> <p>196Mb / ROSBag</p>
UAV multispectral imagery dataset over a vineyard affected by Botrytis in 'Tomiño', Pontevedra, Spain. It includes GPS location of vine trunks, diseases and GCP points.
<p>This dataset contains a set of ground data and four flights captured on grape harvest over a vineyard affected by Botrytis cinerea. UAV flights took place on 16 September 2021, at 30 m height and using different angles (0, 30, 45 degrees). Pictures were taking using a Micasense RedEdge 3 sensor and were calibrated using the provided Micasense reflectance panel. The flight path was programmed to fly in autonomously, following manufacturer’s instructions (DJI). The dataset includes a shapefile with the GPS location of vine trunks, bunches affected by Botrytis and GCP points.</p>
Italian vineyards database
<p>The database contains geo-spatial (block shape, block length/width ratio, mean and max slope) and management (training system, row spacing and headland size) information of 3686 sample vineyards throughout Italian territory.</p>
A dataset of three vine water status indicators, weather records and soil water capacity components collected from a rain-fed Mediterranean vineyard
<p>This dataset contains three key indicators of vine water status: vine shoot growth index (iG-Apex), predawn leaf water potential (Ψpd), and carbon isotope ratio (δ13C). Additionally, it includes weather data and soil measurements. Spatial data files of studied fields, plots, and some vines’ locations are also provided. The data were collected from a rain-fed vineyard in Southern France, 4 km north of the Mediterranean Sea. Measurements were made at the plot level, with each plot consisting of 10 adjacent grapevines (Vitis Vinifera). The iG-Apex was recorded weekly from June 10 to August 22, 2022, across 70 vine plots. Ψpd was measured weekly between 3 a.m. and 5 a.m. in 12 of these plots using a pressure chamber. On August 23, 2022, 100 berries were sampled from each plot, and 1.5 mL of grape juice was extracted for δ13C analysis using a carbon analyzer and mass spectrometer. The dataset contains 761 iG-Apex measurements (70 time series), 720 Ψpd measurements (60 time series), and 70 single-date δ13C measurements. Weather data were recorded daily in 2022 from a weather station located at the vineyard's center, providing five parameters: cumulative rainfall, relative humidity, and three air temperatures (mean, minimum, and maximum). Soil available water capacity components (horizon thickness, field capacity, permanent wilting point, bulk density, and rock fragment content) were measured in 5 of the 70 plots after prior soil profile wall analyses. Monitoring vine water status is essential for optimizing grape yield and wine quality. While Ψpd and δ13C are considered reference methods, they are expensive and prone to logistical constrains. In contrast, iG-Apex can be collected with minimal time and financial investment. This dataset enables not only the exploration of statistical relationships between the plant-based and soil-based indicators, but also the modeling of Ψpd and/or δ13C using iG-Apex, while accounting for weather and soil influences. All data were georeferenced, allowing future integration of ancillary spatial data sources, like multi-spectral remote sensing images or yield data.</p>
Text-fig. 1. Photograph of the studied outcrop with wide bedding planes on the Loděnice – vinice above the topmost step of the vineyard. in Early Complex Tiering Pattern: Upper Ordovician, Barrandian Area, The Czech Republic
Text-fig. 1. Photograph of the studied outcrop with wide bedding planes on the Loděnice – vinice above the topmost step of the vineyard.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.