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1,838 results for “location”
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.
Nutrient Limitation of Algal Biomass in Boreal Streams located near the Bonanza Creek LTER in Fairbanks, Alaska - Summer 2022
This dataset contains estimates of chlorophyll-a accumulated on nutrient-diffusing substrata during ~21 d incubation in each of nine streams located in the interior of Alaska near Fairbanks.
Seasonal and annual summary statistics of urbanization, vegetation, land surface temperature, and bioclimatic variables derived from remotely-sensed imagery in areas surrounding long-term bird monitoring locations in the greater Phoenix, Arizona, USA metropolitan area (1997-2023)
This data package consists of 26 years (1998-2023) of environmental data and 22 years (2000-2022) years of bioclimatic data associated with CAP-LTER long-term point-count bird censusing sites (https://doi.org/10.6073/pasta/4777d7f0a899f506d6d4f9b5d535ba09), temporally aggregated by year and by four meteorological seasons (Winter, Spring, Summer, Fall). The environmental variables include land surface temperature (LST), three spectral indices of vegetation and water – the normalized difference vegetation index (NDVI), the soil adjusted vegetation index (SAVI), and modified normalized difference water index (MNDWI) – and four spectral indices of impervious surface/urbanization. Impervious surface indices include the normalized difference built-up index (NDBI), the normalized difference impervious surface index (NDISI), the enhanced normalized differences impervious surface index (ENDISI), and the normalized impervious surface index (NISI). LST and all spectral indices were derived from annual and seasonal composites of 30-m resolution Landsat 5-9 Level-2 Surface Reflectance imagery. The seven bioclimatic variables (e.g., air temperature, precipitation) were sourced from 1-km resolution gridded estimates of daily climatic data from NASA Daymet V4. We created temporally-aggregated Daymet raster images by calculating mean pixel-values for each season and year, as well as seasonally and annually summed precipitation. We summarized the values of each environmental variable by generating variously-sized (100-m, 500-m, 1000-m) buffers around each bird point count location and extracting weighted mean values of each environmental variable, with each pixel's values weighted by the proportion of its area falling within the buffer. All imagery retrieval and data processing were completed with Google Earth Engine (Gorelick et al. 2017) and program R. A complete description of data processing methods, including the aggregation of imagery by year and season and the calculation of s
Thalassia leaf morphology and productivity measurements from arbitrary plots located in a Thalassia seagrass meadow in Rabbit Key Basin, Florida Bay (FCE) from March 2000 to April 2001
Thalassia leaf morphology and productivity were measured from six arbitrary 200 cm2 plots within a Thalassia seagrass meadow in Rabbit Key Basin, Florida Bay.
Lizard pitfall trap data from 11 NPP study locations at the Jornada Basin LTER site, 1989-2006
This data package contains data on lizards sampled by pitfall traps located at 11 consumer plots at Jornada Basin LTER site from 1989-2006. The objective of this study is to observe how shifts in vegetation resulting from desertification processes in the Chihuahaun desert have changed the spatial and temporal availability of resources for consumers. Desertification changes in the Jornada Basin include changes from grass to shrub dominated communities and major soil changes. If grassland systems respond to rainfall without significant lags, but shrub systems do not, then consumer species should reflect these differences. In addition, shifts from grassland to shrubland results in greater structural heterogeneity of the habitats. We hypothesized that consumer populations, diversity, and densities of some consumers will be higher in grasslands than in shrublands and will be related to the NPP of the sites. Lizards were captured in pitfall traps at the 11 LTER II/III consumer plots (a subset of NPP plots) quarterly for 2 weeks per quarter. Variables measured include species, sex, recapture status, snout-vent length, total length, weight, and whether tail is broken or whole. This study is complete.
Aeolian dust weights sampled by BSNE collectors in 18 locations at the Jornada Basin LTER site, 1998-ongoing
This data package contains aeolian dust weights from BSNE collectors at 18 locations at the Jornada Basin LTER. Collections are obtained at the 15 NPP study locations, the Geomet location, Scrape study location (now known as GROWES study), and Pasture 13 Burn study location. The collectors are turned into the wind with wind vanes. The amount of material collected corresponds to the horizontal flux at the height of the collector and the opening area of the collector and the duration of the sampling time. The five heights of the BSNE collectors above the soil surface are 5, 10, 20, 50, and 100 centimeters for every location where samples are taken. The vertical flux of the particles smaller than 10 micrometers is assumed to be a constant ratio of the horizontal sand flux. The objectives of the study are to find patterns of sand flux rates as related to soil and vegetation. Site info: The NPP sites were established to estimate patterns of aboveground primary production. The Geomet site is within a mesquite-dune area that has had long-term protection from cattle grazing. The scrape site (now known as the GROWES site) was originally designed to measure the abrasion of surface crust. The Pasture 13 Burn site is located in a pasture that was originally burned in 1998. Contact the data manager for additional information and site locations. This data collection is ongoing with new data added quarterly.
Precipitation data from four locations within the Tromble Weir experimental watershed, located at the Jornada Basin LTER site, 2010-ongoing
This data package contains one-minute resolution precipitation data from tipping bucket rain gauges (Texas Electronics) at four locations in the Tromble Weir watershed area of the Jornada Basin in southern New Mexico, USA. These rain gauges are used to help quantify the water balance across the small experimental watershed. Values have been used to investigate groundwater recharge, soil infiltration rates, and as forcings for hydrologic models. This is an ongoing dataset that will be updated annually.
Soil volumetric water content data from fifteen locations, 3 depths at each location, within the Tromble Weir experimental watershed at the Jornada Basin LTER site, 2010-ongoing
This data package contains 30-minute soil volumetric water content (VWC) data collected at fifteen locations along 3 transects (5 locations per transect) in the Tromble Weir Watershed area of the Jornada Basin in southern New Mexico, USA. At each location, soil sensors measure VWC at three depths, 5, 15 and 30 cm, in units of cubic meters of water per cubic meter of soil. These measurements are used to help quantify the water balance across the small experimental watershed. Values have been used to investigate groundwater recharge, soil infiltration rates, and to evaluate the performance of hydrologic models. This is an ongoing dataset that will be updated annually.
GPS point locations of plots, subplots, itex subplots, transects and soil sensor in the black sand extended growing season experiment, 2018 - 2023.
As a result of climate change, the Rocky Mountain Front Range is experiencing warmer summers and earlier snowmelt. Due to the importance of snow for regulating soil temperature, growing season length, and available moisture in alpine ecosystems, even small shifts in the snow-free period could have large impacts. The focus of the Black Sand Extended Growing Season Length Experiment is to examine how terrain-related differences in climate exposure influence the way alpine habitats respond to climate change via earlier snowmelt. To simulate how climate exposure may affect plant communities, NWT LTER researchers established 5 experimental sites each containing a pair 10 x 40m rectangular plots. These sites include north and south facing aspects, subalpine and alpine tundra meadows in a range of hydrological conditions (e.g. dry meadows, moist meadows, wet meadows). We accelerated snowmelt in one plot of each block by adding chemically inert black sand, while keeping the second plot as an unmanipulated control; black sand was added to these plots after snow had naturally melted. This dataset includes geolocations of individual subplots and sensors within the experiment, measured in summer 2023.
PIE LTER, Wind sensor data, 15 minute intervals, from the Ipswich Bay Yacht Club pier located in Ipswich, MA, year 2022.
Wind sensor measurements (wind speed and wind direction) for 2022 at the Ipswich Bay Yacht Club, Ipswich, MA, 15 minute average measurements.
PIE LTER, meteorological data, 15 minute intervals, from the Marshview Farm weather station located in Newbury, MA, year 2021
Meteorological measurements for 2021 at MBL Marshview Farm, Newbury, MA. Sensors conduct measurements every 5 seconds and measurements are reported as averages or totals for 15 minute intervals. 15 minute averages are reported for air temperature, humidity, solar radiation, PAR, wind speed and direction and barometric pressure. 15 minute totals are reported for precipitation.
PIE LTER 15-minute meteorological data from the Marshview Farm weather station located in Newbury, MA, year 2022
Meteorological measurements for 2022 at MBL Marshview Farm, Newbury, MA. Sensors conduct measurements every 5 seconds and measurements are reported as averages or totals for 15 minute intervals. 15 minute averages are reported for air temperature, humidity, solar radiation, PAR, wind speed and direction and barometric pressure. 15 minute totals are reported for precipitation.
PIE LTER 15-minute meteorological data from the Marshview Farm weather station located in Newbury, MA, year 2023
Meteorological measurements for 2023 at MBL Marshview Farm, Newbury, MA. Sensors conduct measurements every 5 seconds and measurements are reported as averages or totals for 15 minute intervals. 15 minute averages are reported for air temperature, humidity, solar radiation, PAR, wind speed and direction and barometric pressure. 15 minute totals are reported for precipitation.
SBC LTER: Ocean: Ocean hourly temperature at nearshore locations along the Northern Channel Islands in the Santa Barbara Channel, ongoing since 2000
Ocean in-situ temperature data were collected at nearshore sites along the Northern Channel Islands in the Santa Barbara Channel. The earliest temperature records started in April 2000. The temporal coverage varies at each site. At the start of the temperature data collection, the tidbit or hobo sensors were deployed on a mooring line at approximate 3 m, 9m, and 14 m nominal depths, and the sampling interval is 2 minutes. In 2013, the 3 m and 9 m temperature sensors were terminated and only 14 m sensors continued. In addition, the sampling interval changed to 15 minutes. This data package presents hourly average in-situ temperature data. The original raw data (2-min interval) between 2000-2010 were published on DataOne https://search.dataone.org/portals/PISCO. Data can be viewed and accessed by zooming in the Northern Channel Islands in the Santa Barbara Channel region and searching the keyword "physical oceanography moored temperature data". These datasets were funded and managed by The Partnership for Interdisciplinary Studies of Coastal Oceans (PISCO). In 2013, the maintenance of the sensor deployment was transferred to NOAA National Marine Sanctuaries, and Santa Barbara Coastal LTER has been responsible for data download and processing.
Mask at 300 m of water-body locations more than 5, 15 and 20 km distant from land
<p>Locations of water-body locations remote from land: This dataset is a latitude-longitude grid indicating the locations of water-body locations more distant from land than 5, 15 and 20 km. It is derived from Carrea et al., 2016, which in turn was derived from the ESA Climate Change Initiative for Land Cover Water Bodies product released in October 2014. 3 = distance greater than 20 km; >=2 = distance greater than 15 km; >=1 = distance greater than 5 km. Paper describing underlying distance-to-land dataset: Carrea, L., Embury, O., Merchant, C.J. (2016) Datasets related to inland water for limnology and remote sensing applications: distance-to-land, distance-to-water, water-body identifier and lake-centre co-ordinates. Geoscience Data Journal, 2(2). pp. 83-97. doi: https://doi.org/10.1002/gdj3.32. This work done within the project: ESA Climate Change Initiative Lakes, by University of Reading, UK. </p> <p> 'geospatial_lat_min': -90.0,\<br> 'geospatial_lat_max': 90.0,\<br> 'geospatial_lon_min': -180.0,\<br> 'geospatial_lon_max': 180.0,\<br> 'geospatial_lat_units': 'degrees_north',\<br> 'geospatial_lat_resolution': 0.0027777778,\<br> 'geospatial_lon_units': 'degrees_east',\<br> 'geospatial_lon_resolution': 0.0027777778,\<br> 'spatial_resolution': '300m'</p>
Data to "Predicting precision grip grasp locations on three-dimensional objects"
<p>This record contains experimental and analysis scripts (written in Matlab) as well as raw and processed data to reproduce the results shown in:</p> <p>Klein, L. K. ^, Maiello, G. ^, Paulun, V. C., & Fleming, R. W. (in press). <br> Predicting precision grip grasp locations on three-dimensional objects. PLOS Computational Biology<br> ^co-first authors </p> <p>A preprint version of the manuscript is currently available at: https://doi.org/10.1101/476176</p>
A 2-minute rainfall (12 locations) and discharge time series at the Vallon de Nant catchment, Switzerland, for 2018 summer seasons
<p>The data set contains rainfall time series within the experimental 13.4 km² Vallon de Nant catchment, Switzerland (Michelon et al., 2020), from June 30th to September 23rd 2018 at 12 locations. A network of <em>Pluvimate</em> drop-counting raingauges (www.driptych.com) measured continuously the rainfall intensity at a 2-minute resolution. Operation and characteristics of the raingauges are detailed in Benoit et al. (2018) and Michelon et al. (2020), and the rating curve is described by Ceperley et al. (2018).</p> <p>Description of the files:</p> <ul> <li><em><strong>data.csv</strong></em> contain the rainfall intensities for the observation period, along with the main river discharge measured at the <a href="https://map.geo.admin.ch/?lang=fr&topic=ech&bgLayer=ch.swisstopo.pixelkarte-farbe&layers=ch.swisstopo.zeitreihen,ch.bfs.gebaeude_wohnungs_register,ch.bav.haltestellen-oev,ch.swisstopo.swisstlm3d-wanderwege,KML%7C%7Chttps:%2F%2Fpublic.geo.admin.ch%2FaLKDanGXRPGMpB_D51f2Tg&layers_visibility=false,false,false,false,true&layers_timestamp=18641231,,,,&E=2574619.27&N=1122462.26&zoom=8">outlet</a> over the same 2-minutes time step as the rainfall intensity. We also provide areal rainfall intensity aggregated over the whole catchment:<br> Columns: <ul> <li>year [-]</li> <li>month [-]</li> <li>day [-]</li> <li>hour [-]</li> <li>minute [-]</li> <li>specific discharge 95% inf. [mm/day]: inferior values of the specific discharge (with 95% of confidence interval) over 2 minutes</li> <li>specific discharge 95% sup. [mm/day]: superior values of the specific discharge (with 95% of confidence interval) over 2 minutes</li> <li>specific discharge mean [mm/day]: mean value of the specific discharge over 2 minutes</li> <li>specific discharge median [mm/day]: median value of the specific discharge over 2 minutes</li> <li>P St. #X [mm]: rainfall amount measured at the station X over 2 minutes</li> <li>P stochastic mean [mm/h]: rainfall amount interpolated over the whole catchment over 2 minutes</li> <li>P stochastic std [mm/h]: standard deviation of the stochastic rainfall interpolation, over 2 minutes</li> </ul> </li> <li><strong><em>stations.csv</em></strong> describes the raingauge locations.<br> Columns: <ul> <li>Station ID [-]</li> <li>lon [WGS84]: decimal longitude of the station into WGS84</li> <li>lat [WGS84]: decimal latitude of the station into WGS84</li> <li>E [CH1903]: east coordinate into Swiss Coordinate System</li> <li>N [CH1903]: north coordinate into Swiss Coordinate System</li> <li>elevation [m asl]: altitude of the station in meters above the sea level</li> <li>data in 2017 [-]: flag if the station was working over the 2017 observation period</li> <li>data in 2018 [-]: flag if the station was working over the 2018 observation period</li> </ul> </li> <li><em><strong>rainfall_viewer.m</strong></em> is a <em>MatLab</em> script (created with <em>MatLab 2017b</em>) which allows the joint visualization of the rainfall intensities and river discharge. It produces a composite figure with the following plots: <ul> <li>On top the general hydrograph over the whole observation period [mm/day]. The red dashed lines mark out period that the other plots are focus on. The shaded orange areas correspond to when the river stage data was not available.</li> <li>Below, the zoomed hydrogram show a detailed view of the river discharge (and uncertainty). In case a river reaction is associated, the discharge event is marked out by red dashed lines. Between these vertical lines is drawn a line joining the initial and final baseflow, separating the discharge amount fed by the baseflow (under the line) to the fast runoff (over the line). The red square shows the center of mass of the fast runoff part.</li> <li>In the middle a zoomed magnification of the hydrograph that shows a detailed view of the discharge in the river [mm/day]. When a river response is associated, the discharge event is marked with dashed red lines. Between these vertical lines a line joining the initial and final baseflow is drawn, separating the discharge amount fed by the baseflow (under the line) to the fast runoff (over the line). The red square shows the center of mass of the fast runoff.</li> <li>At the bottom are shown the rainfall recorded by each of the 12 rain gauges (the y-axis scale between 2 stations is about 20 mm/h). The rainfall event is marked out by green dashed lines.</li> <li>Above is shown the rainfall amount (and uncertainty) interpolated over the catchment using the stochastic method. The rainfall event is marked out by green dashed lines.</li> <li>On the left, a map with the 12 raingauge locations show the total amount of rainfall recorded by each station during the event (a red cross shows missing data).<br> <br> It is possible to zoom in the plots by clicking with the left and right mouse buttons to define respectively the starting and ending of the visualization window. The middle button defines a third time reference used to identify rainfall intensity peaks or discharge peaks. Statistics concerning the visualization period are displayed on the MatLab console.<br> Pressing [enter] will save the figure into a PNG file named with the starting and ending dates of the visualization window.</li> </ul> </li> <li><strong><em>Q_stats.m </em></strong>is a MatLab function used by the main code rainfall_viewer.m</li> <li><strong><em>print_figure.m </em></strong>is a MatLab function used by the main code rainfall_viewer.m</li> <li><strong>data.mat</strong> is a MatLab data file with all data required by the main code rainfall_viewer.m</li> </ul>
Pythia Generated Jet Images with Alternative Rotation Scheme for Location Aware Generative Adversarial Network Training
<p>Dataset containing 300k jet images that can be used to train Location Aware Generative Adversarial Networks (LAGAN) for High Energy Physics, such as the one in [arXiv:1701.05927].</p> <p><strong>Format</strong>:</p> <p>HDF5 file with the following fields:</p> <ul> <li>'image' : array of dim (300000, 25, 25), contains the pixel intensities of each 25x25 image</li> <li>'signal' : binary array to identify signal (1, i.e. W boson) vs background (0, i.e. QCD)</li> <li>'jet_eta': eta coordinate per jet</li> <li>'jet_phi': phi coordinate per jet</li> <li>'jet_mass': mass per jet</li> <li>'jet_pt': transverse momentum per jet</li> <li>'jet_delta_R': distance between leading and subleading subjets if 2 subjets present, else 0</li> <li>'tau_1', 'tau_2', 'tau_3': substructure variables per jet (a.k.a. n-subjettiness, where n=1, 2, 3)</li> <li>'tau_21': tau<sub>2</sub>/tau<sub>1</sub> per jet</li> <li>'tau_32': tau<sub>3</sub>/tau<sub>2</sub> per jet</li> </ul> <p><strong>Details</strong>:</p> <ul> <li>Simulated using Pythia 8.219 at √ s = 14 TeV</li> <li>Image pre-processing using method from in L. de Oliveira et al., <em>Jet-Images -- Deep Learning Edition </em>[arXiv:1511.05190]</li> <li>scikit-image==0.10.0 implementation of cubic spline rotation with fewer low energy artifacts than scikit-image>=0.12.0</li> <li>Finite calorimeter granularity simulated with 0.1×0.1 grid in η and φ, with η × φ ∈ [−1.25, 1.25] × [−1.25, 1.25]</li> <li>Jet clustering with anti-k<sub>t</sub> algorithm with a radius R = 1.0 using FastJet 3.2.1; constituent re-clustering into R = 0.3 k<sub>t</sub> subjets</li> <li>Intensity of pixel = p<sub>T</sub> of cell</li> <li>60 GeV < m<sup>jet</sup> < 100 GeV</li> <li>250 GeV < p<sub>T</sub><sup>jet</sup> < 300 GeV</li> <li>Sparse images (~10% NNZ)</li> </ul> <p>Full dataset description in [arXiv:1701.05927].</p>
Multi-faceted analyses of Poland's Bronze and Early Iron Age hoards: Fig.1. Location of hoards mentioned in the text: white dots represent locations of hoards examined in the Biography of Hoards project; black dots represent locations of hoards examined in other multi-faceted projects
<p>The set contains a figure, with data, on the location of the hoards included (described in the related paper).<br><br>The paper and data were prepared as part of a project funded by the National Science Centre, Poland: <em>A Biography of Late Bronze and Early Iron Ages Hoards. A Multi-Faceted Analysis of Metal Objects Related to Monumental Constructions in Poland</em> (UMO-2021/41/B/HS3/00038)</p>
Plant Atlas 2020 — British and Irish vascular plant and charophyte 2 x 2 km grid square locations up to 2019
<p><span>This resource provides the data behind the 2 × 2 km grid square (tetrad) British and Irish distribution maps, for 3,431 taxa, presented in both the Plant Atlas 2020 book and website (</span><a href="http://www.plantatlas2020.org"><span><span>www.plantatlas2020.org</span></span></a><span><span>), up to 2019. These are presence-only data, indicating where a taxon was reported from a tetrad</span></span><span>. These 2 km square presences are based on over 30 million records, collected mainly by volunteer recorders of the Botanical Society of Britain and Ireland (BSBI) between 2000 and 2019, as well as previous nationwide surveys undertaken in the 1950s and 1990s.</span></p>
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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.