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ShareScore release 0.7.1
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45 results for “geographic area”
Gridded Population of the World, Version 3 (GPWv3): Land and Geographic Unit Area Grids
The Gridded Population of the World, Version 3 (GPWv3): Land and Geographic Unit Area Grids measure land areas in square kilometers and the mean Unit size (population-weighted) in square kilometers. The land area grid permits the summation of areas (net of permanent ice and water) at the same resolution as the population density, count, and urban-rural grids. The mean Unit size grids provides a quantitative surface that indicates the size of the input Unit(s) from which population count and density grids are derived..GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT).
Global Rural-Urban Mapping Project, Version 1 (GRUMPv1): Land and Geographic Unit Area Grids
The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1): Land and Geographic Unit Area Grids measure land areas in square kilometers and the mean Unit size (population-weighted) in square kilometers. The land area grid permits the summation of areas (net of permanent ice and water) at the same resolution as the population density, count, and urban-rural grids. The mean Unit size grids provide a quantitative surface that indicates the size of the input Unit(s) from which population count and density grids are derived. Additional global grids are created from the 30 arc-second grid at 1/4, 1/2, and 1 degree resolutions. This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT).
Last of the Wild Project, Version 1, 2002 (LWP-1): Top One Percent Wild Areas Dataset (Geographic)
The Top One Percent Wild Areas Dataset of the Last of the Wild Project, Version 1, 2002 (LWP-1) is derived from the LWP-1 Human Footprint Dataset. The gridded data are classified according to their raster value (wild = 0-1; not wild >1). The top 1% of the wild areas within each biome by realm are selected and identified. The dataset in Clarke 1866 Geographic Coordinate System is produced by the Wildlife Conservation Society (WCS) and the Columbia University Center for International Earth Science Information Network (CIESIN).
Geographically Weighted Regression Modeling of a Nighttime Urban Heat Island in Dar es Salaam Metropolitan Areas
<p>Urban Heat Islands (UHI) is the urban microclimate with higher air temperature than surrounding areas. It is caused by both man-made and natural factors which vary geographically based on weather periods. To have a sustainable future in the environment, there is a need to regulate influence levels of various causative factors that generate UHI. Geographically Weighted Regression (GWR) model is among the spatial regression models that define the non-stationarity of variables. It generates a new equation on each sampled data unlikely global models like Ordinary Least Square (OLS). The study used GWR model to determine the influencing levels of three independent factors named Indexed-based Built-up Index (IBI), albedo and wind speed. Datasets were retrieved from MODIS satellite during the dry period of July from 2000 to 2019. IBI and Albedo were observed to have a strong negative influence with the maximum value of -0.045 and -0.053 respectively although, we expected to observe a positive influence on IBI since buildings emit absorbed energy during the night. Wind speed has a positive influence with the maximum value of 0.028 leading to the shift of heatwaves hence being termed as the secondary driving factor while IBI and Albedo as the primary driving factors. Wind speed is the highest driving factor that shifts emitted energies to other areas. We encourage an innovation in technology that produce higher albedo construction materials. We should improve environmental policies by introducing green cities through horizontal and vertical forests which might decrease the emitted energy into the atmosphere.</p>
Geographically Weighted Regression Modeling of a Daytime Urban Heat Island in Dar es Salaam Metropolitan Areas.
<p>Urban heat island is the phenomenon of having higher temperatures in urban areas compared to surrounding areas. It is caused by the replacement of natural vegetation with construction materials. Geographically Weighted Regression Model (GWR) determines non-stationarity among variables by generating a new equation for each sample size. Moderate Resolution Imaging Spectroradiometer (MODIS) products such as MOD11A1, MCD43A1, MOD09A1 and MOD13A1 are used to acquire Land Surface Temperature (LST), Albedo, Indexed-Based Built-Up Index (IBI) and Enhanced Vegetation Index (EVI) respectively. The highest and lowest coverage of Urban Heat Island of 69% and 43% were observed in 2000 and 2005 respectively. IBI is the leading causative factor by having an influence of 0.023 followed by Albedo, wind speed and EVI with an average of 0.019, 0.016 and -0.015 respectively. We recommend innovation in producing higher albedo construction materials and introducing green city policies.</p>
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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.