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26 results for “grid cells”
Geografisches hexagonales Gitter mit 1 Quadratkilometer Zellengröße für Deutschland - Geographical hexagonal grid with one square kilometer cell size for Germany
<p>Ein räumliches Gitter stellt eine abstrakte Definition von einheitlich großen Bezugszellen für statistische Auswertungen dar. Dieses macht Auswertungen und Vergleiche gegenüber räumlichen Abgrenzungen auf der Basis von administrativen Grenzen wie Kreisen oder Gemeinden unterschiedlicher Größen einfacher. Geografische Gitterdefinitionen werden eingesetzt, um eine vordefinierte Raumbezugsstruktur zu haben mit einer einheitlicheren Verteilung von Zellen in der Fläche.</p> <p><br> Ein Gitter mit sechseckigen, eben hexagonalen Zellen bietet eine Alternative zu rechteckigen statistischen Gittern wie das GeoGitter vom Bundesamt für Kartographie und Geodäsie (BKG, 2020). Ein Hexagon-Gitter bietet neben der Eigenschaft homogene Einheiten für statistische Analysen zu bilden (Schindler et al. 2008) mit sechs unmittelbaren Nachbarzellen vorteilhaftere Voraussetzungen für Nachbarschaftsanalysen im Vergleich zu quadratischen Zellen mit vier Kantennachbarn (White et al. 1992). Als Beispiel werden im Bild 1 mittels Hexagonen-Gitter Volumenunterschiede der aufragenden Vegetation pro Zelle dargestellt.</p>
Fig. 2. – Species prediction for a grid cell. A in Geographical patterns of woody plants' functional traits in Burkina Faso
Fig. 2. – Species prediction for a grid cell. A. Average of maximal plant size; B. Percentage of spinescent species; C. Percentage of species containing latex; D. Percentage of species with compound leaves.
Fig. 2. Forty-one grid cells randomly set within a 10 in Factors limiting the current distribution of the introduced Java sparrow (Lonchura oryzivora) in Bangkok, Thailand
Fig. 2. Forty-one grid cells randomly set within a 10-km radius around Don Muang airport, Bangkok, Thailand, used for surveying Java sparrows. Don Muang was the site where Java sparrows were first recorded in Thailand in 1924. The study area includes three provinces; Bangkok, Pathum Thani, and Nonthaburi. The primary land use was urban, while paddyfields were mostly located on the eastern side of the study area. Different symbols (circles, squares and triangles) represent the number of occasions (out of 5 possible visits to a location) on which the sparrow was detected. Size of symbols of Java sparrow detection points was related to the number of birds detected; smallest size indicated only 1 bird was detected, medium size indicated 2–10 birds were detected, and largest size indicated a group of more than 40 birds was detected.
During hippocampal inactivation, grid cells maintain synchrony, even when the grid pattern is lost
<p>The grid cell network in the medial entorhinal cortex (MEC) has been subject to thorough testing and analysis, and many theories for their formation have been suggested. To test some of these theories, we re-analyzed data from Bonnevie et al., 2013, in which the hippocampus was inactivated and grid cells were recorded in the rat MEC. We investigated whether the firing associations of grid cells depend on hippocampal inputs. Specifically, we examined temporal and spatial correlations in the firing times of simultaneously recorded grid cells before and during hippocampal inactivation. Our analysis revealed evidence of network coherence in grid cells even in the absence of hippocampal input to the MEC, both in regular grid cells and in those that became head-direction cells after hippocampal inactivation. This favors models, which suggest that phase relations between grid cells in the MEC are dependent on intrinsic connectivity within the MEC.</p>
Cell thicknesses calculated for the tripolar grid used by the GREP reanalyses
<p>Cell thicknesses were calculated for the tripolar NEMO0.25 grid used by the GREP reanalyses (ORAS5, CGLORS, GLORYS2V4, FOAM).</p>
2014 EPA National Emissions Inventory allocated to the grid cells of InMAP Source-Receptor Matrix
<p>This dataset is the 2014 EPA National Emissions Inventory (NEI) v1 allocated to the individual grid cells of InMAP Source-Receptor Matrix (<a href="https://zenodo.org/record/2589760#.Yds79GjMI2w">ISRM</a>). The source types is classified by EPA Source Classification Codes (SCCs). The dataset includes emissions of both primary and secondary PM<sub>2.5</sub>. Secondary PM<sub>2.5</sub> includes four precursors: NO<sub>x</sub>, SO<sub>x</sub>, NH3, and VOC. The detailed description of emission processing is in <a href="https://doi.org/10.1073/pnas.1818859116">Tessum et al. (2019</a>).</p> <p>Each shapefile in the dataset is in the format of input file of <a href="http://spatialmodel.com/inmap/">InMAP</a>/ISRM, which includes the emission amounts of five pollutants (Primary PM<sub>2.5</sub>, NO<sub>x</sub>, SO<sub>x</sub>, NH3, and VOC), stack information (height, diameter, temperature, and velocity), and SCCs. The unit of emissions is <span class="math-tex">\(\mu g/s\)</span>. (If these emissions are used directly with the ISRM, the resulting outputs will be concentrations, in units of <span class="math-tex">\(\mu g/m^3\)</span>.)</p>
Wind and solar capacity factor time series by year and grid cell over the contiguous U.S.
<p>This data set contains hourly capacity factor time series of wind and solar resources over the contiguous U.S.</p> <p> </p> <p>The included time series cover four individual years and 2,586 grid cells. The years range from 2016 to 2019. The grid cells correspond to the grid cells of the NASA's MERRA-2 reanalysis data set into which the contiguous U.S. is subdivided. The grid cells have a spatial resolution of 0.5° latitude x 0.625° longitude with dimensions ranging from about 55 km x 45 km to 55 km x 62 km.</p> <p> </p> <p>This data set is used to generate the results of the following journal article:</p> <p>Enrico G. A. Antonini, Tyler H. Ruggles, David J. Farnham, Ken Caldeira, "The quantity-quality transition in the value of expanding wind and solar power generation", iScience 25 (4), 104140, 2022.</p> <p> </p> <p>Code and instructions required to reproduce the results reported in the above paper are available in the GitHub repositories at <a href="https://github.com/eantonini/Distributed_wind_and_solar_generation">https://github.com/eantonini/Distributed_wind_and_solar_generation</a> and <a href="https://github.com/carnegie/MEM_public/tree/Antonini_et_al_2022">https://github.com/carnegie/MEM_public/tree/Antonini_et_al_2022</a>.</p>
Data from: During hippocampal inactivation, grid cells maintain synchrony, even when the grid pattern is lost
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Grid cells accurately track movement during path integration-based navigation despite switching reference frames
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Estimated Distance from the Ocean for River Grid Cells - Parker and Ipswich Watersheds - ASCII Raster File
This datalayer is a gridded data set of the estimated distance (km) to ocean from each point in the gridded river network. The resolution is 120 m x 120 m. Based on the flow direction in: WAT-RGIS-120m-FlowDirection.asc Provide the distance to ocean for each grid cell.
Statistics for each 15 km X 15 km grid cell, for all California native vascular plants, as studied by Baldwin et al. (2017 Amer. J. Bot.), including randomization results.
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Net ecosystem production (NEP) raw data for the coupled and uncoupled simulation for all North American black spruce grid cells (n=1758)
Output from TEM modeling in North American black spruce grid cells Data from the following manuscript Clein, J.S., A.D. McGuire, X. Zhang, D.W. Kicklighter, J.M. Melillo, S.C. Wofsy, P.G. Jarvis, and J. M. Massheder. 2002. Historical and projected carbon balance of mature black spruce ecosystems across North America: The role of carbon-nitrogen interactions. Plant and Soil 242:15-32.
Data from: Visual landmarks sharpen grid cell metric and confer context specificity to neurons of the medial entorhinal cortex
Neurons of the medial entorhinal cortex (MEC) provide spatial representations critical for navigation. In this network, the periodic firing fields of grid cells act as a metric element for position. The location of the grid firing fields depends on interactions between self-motion information, geometrical properties of the environment and nonmetric contextual cues. Here, we test whether visual information, including nonmetric contextual cues, also regulates the firing rate of MEC neurons. Removal of visual landmarks caused a profound impairment in grid cell periodicity. Moreover, the speed code of MEC neurons changed in darkness and the activity of border cells became less confined to environmental boundaries. Half of the MEC neurons changed their firing rate in darkness. Manipulations of nonmetric visual cues that left the boundaries of a 1D environment in place caused rate changes in grid cells. These findings reveal context specificity in the rate code of MEC neurons.
Socio-economic dataset at 1 km grid cell for fire prediction in 1980s and 2000s Madrid (Spain)
<p><span>This data gathers socioeconomic drivers at 1km2 grid cell spatial resolution to predict forest fires in a region in Spain (Madrid) for two periods of time (1980 and 2000s. The response variable was exact located fires by grid cell. <span>The resulting work was published at </span></span>Vilar, L., Gómez, I., Martínez-Vega, J., Echavarría, P., Riaño, D., & Martín, M. P. (2016). Multitemporal modelling of socio-economic wildfire drivers in central Spain between the 1980s and the 2000s: comparing generalized linear models to machine learning algorithms. <em>PLoS One</em>, <em>11</em>(8), e0161344.</p> <p><span>.-Description of the data and file structure</span></p> <p><span>The data set is an excel file with columns for these variables:</span></p> <table> <tbody> <tr> <td>VARIABLES</td> <td>DESCRIPTION</td> </tr> <tr> <td>CellCode</td> <td>ID of the 1*1km cell</td> </tr> <tr> <td>X</td> <td>X cell coordinate</td> </tr> <tr> <td>Y</td> <td>Y cell coordinate</td> </tr> <tr> <td>POP</td> <td>population density</td> </tr> <tr> <td>AGRI</td> <td>agriculture workforce density</td> </tr> <tr> <td>SERV</td> <td>services workforce density</td> </tr> <tr> <td>FAI</td> <td>200 m Forest Agriculture Interface buffer<span> </span></td> </tr> <tr> <td>WUI</td> <td>12.5m Wildland Urban Interface buffer<span> </span></td> </tr> <tr> <td>FGI</td> <td>200 m Forest Grassland Interface buffer<span> </span></td> </tr> <tr> <td>RAILWAYS</td> <td>70 and 100 m railway buffers<span> </span></td> </tr> <tr> <td>ROADS</td> <td>15, 25 and 50 m road buffers<span> </span></td> </tr> <tr> <td>TRACKS</td> <td>300 m tracks buffer<span> </span></td> </tr> <tr> <td>NPA</td> <td>Natural Protected Area</td> </tr> <tr> <td>FIRE_PRESENCE</td> <td>Response variable. Fire presence/absence</td> </tr> </tbody> </table>
Ithomiini grid-cell records for distribution modeling
<p> </p> <p>This repository contains georeferenced <strong>occurrence data</strong> for ithomiine butterflies (tribe Ithomiini) needed to reproduce the analyses presented in the research paper <strong>"Doré et al., 2021 - Anthropogenic pressures coincide with Neotropical biodiversity hotspots in a flagship butterfly group"</strong>: <a href="https://doi.org/10.1111/ddi.13455">https://doi.org/10.1111/ddi.13455</a>.</p> <p> </p> <p><strong>Distribution maps</strong> generated from distribution models runned on these occurrences data are available in an other associated archive: <a href="http://doi.org/10.5281/zenodo.4673446">https://doi.org/10.5281/zenodo.4673446</a>.</p> <p><strong>Mimicry classification</strong> used for theses analyses is available in this associated archive: <a href="https://doi.org/10.5281/zenodo.5497876">https://doi.org/10.5281/zenodo.5497876</a>.</p> <p><strong>Scripts</strong> to reproduce these maps are available on Github at <a href="http://github.com/MaelDore/ithomiini_diversity">https://github.com/MaelDore/ithomiini_diversity</a>.</p> <p> </p> <p>This repository contains an Excel file with the occurrence records and associated metadata in separated tabs. </p> <p> </p>
Fig. 3. – Species prediction for a grid cell. A in Geographical patterns of woody plants' functional traits in Burkina Faso
Fig. 3. – Species prediction for a grid cell. A. Percentage of species flowering in rainy season; B. Percentage of species having dry fruits; C. Percentage of species having dehiscent fruits; D. Average of minimal fruit length.
Data from: Visual landmarks sharpen grid cell metric and confer context specificity to neurons of the medial entorhinal cortex
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The long noncoding RNA Malat1 regulates CD8+ T cell differentiation by mediating epigenetic repression (GRID-Seq)
GEO Series GSE203089. Mus musculus. 2 samples. Type: Other.
Arizona Building Aggregated Parameters: Model America v1.0 Data for 146,557 1kmx1km Grid Cells
<p>Oak Ridge National Laboratory (ORNL) has developed the Automatic Building Energy Modeling (AutoBEM) software suite to process multiple types of data, extract building-specific descriptors, generate building energy models, and simulate them on High Performance Computing (HPC) resources. For more information, see AutoBEM-related publications (<a href="https://bit.ly/AutoBEM">bit.ly/AutoBEM</a>).</p> <ul> <li>Building height</li> <li>Building footprint area</li> <li>Building total floor area</li> <li>Height-to-width ratio (height / [longest polygon vertex pair distance]) </li> <li>Number of buildings (ratio of each building type)</li> <li> Street orientation (longest polygon vertex pair's degree)</li> <li>Rooftop area density (total roof area / total cell area)</li> <li>Rooftop area density (total roof area / total cell area)</li> <li>Lambda_p (roof area / total cell area)</li> <li>Lambda_b (surface area of buildings (roof + vertical walls) / total cell area)</li> </ul> <p>Please note that certain parameters include the mean, median, mode, standard deviation, maximum, and minimum values.</p> <p>Three sets of data are provided for 2,555,153 buildings located within the boundary of Arizona in the United States:</p> <ol> <li><strong>Data (3.6MB *.csv) - Arizona 146,557 Grid Cell Locations.</strong></li> <li><strong>Data (15MB *.csv) - Arizona Building Aggregated Parameters Data developed for the Grid Cells.</strong></li> <li><strong>Data (2.5MB *.csv) - Arizona Building Aggregated Parameters Data developed for the Grid Cells (Selected Parameters).</strong></li> </ol> <p>This data is made free and openly available in hopes of stimulating any simulation-informed use case. Data is provided as-is with no warranties, express or implied, regarding fitness for a particular purpose. We wish to thank our sponsors which include Oak Ridge National Laboratory (ORNL), U.S. Dept. of Energy’s (DOE) Building Technologies Office (BTO), Office of Electricity (OE), and Biological and Environmental Research (BER).</p>
Grid Radiation Therapy for the Treatment of Stage IV Non-Small Cell Lung Cancer
ClinicalTrials.gov study NCT06660407. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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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.