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154 results for “Raster”
Land Cover, 2005, for Town of West Newbury, Massachusetts - Raster
This is a seven-category land-cover map of West Newbury, Massachusetts. The seven categories are: bare soil, coniferous trees, decidous trees, grass, impervious surface, water, and wetlands. Note: Complete metadata is available within the downloaded zip file. This metadata can be viewed with ESRI ArcGIS software, and can be exported to FGDC and ISO metadata formats.
Land Cover, 2005, for Town of Wilmington, Massachusetts - Raster
This is a seven-category land-cover map of Wilmington, Massachusetts. The seven categories are: bare soil, coniferous trees, decidous trees, grass, impervious surface, water, and wetlands. Note: Complete metadata is available within the downloaded zip file. This metadata can be viewed with ESRI ArcGIS software, and can be exported to FGDC and ISO metadata formats.
Land Cover, 2005, for Town of Woburn, Massachusetts - Raster
This is a seven-category land-cover map of Woburn, Massachusetts. The seven categories are: bare soil, coniferous trees, decidous trees, grass, impervious surface, water, and wetlands. Note: Complete metadata is available within the downloaded zip file. This metadata can be viewed with ESRI ArcGIS software, and can be exported to FGDC and ISO metadata formats.
PIE LTER 2005 Digital elevation model for the Plum Island Sound estuary, Massachusetts, filtered_grd, last filtered grid - Raster
On April 18 and 19, 2005 LIDAR (Light Detection and Radar) flights occured in the lower portion of the Plum Island Sound, Massachusetts estuary and were timed to correspond to low tides to minimize higher tide influences on pulsed returns. The LIDAR survey was conducted by the National Center for Airborne Laser Mapping (NCALM). This data set consists of a one meter Digital Elevation Model (DEM) in ESRI GRID file format based upon last filtered grid (bare-earth) data from the LIDAR flights.
Raster layers of prioritisation analyses for current and future conditions based on phylogenetic diversity of Neotropical palms
<p><strong>Aim:</strong> Palms are an ecologically and societally important plant group, with high diversity in the Neotropics. Here, we estimated the impacts of future climate change on phylogenetic diversity (PD) of Neotropical palms under varying climatic and dispersal scenarios, assessed the effectiveness of the established network of protected areas (PAs) for conserving palms PD today and in 2070, and identified priority areas for the conservation of palm species and their evolutionary history in the face of climate change.</p> <p><strong>Location:</strong> Neotropics.</p> <p><strong>Methods:</strong> We used ecological niche modelling to estimate the distribution of 367 species in the present and for 2070 based on two greenhouse gas emission and two dispersal scenarios. We calculated Faith's PD within each five arc-minute grid cell to evaluate the effectiveness of PAs relative to null models and used phylogenetic spatial prioritisation analysis to detect priority areas.</p> <p><strong>Results:</strong> We found that even under the most optimistic climatic and dispersal scenarios, the established network of PAs performed poorly in safeguarding palms PD under both current conditions and those projected for 2070. Significant losses in PD inside PAs are expected under future climate conditions, especially if species are unable to disperse to suitable areas. Nevertheless, a modest and strategic increase in the number of PAs could considerably improve the protection of palms PD in the present and 2070.</p> <p><strong>Main conclusions: </strong>The PD of Neotropical palms is poorly represented within the established network of PAs, at both present and in 2070. A higher realised dispersal rates would diminish PD losses inside the network of PAs. The conservation of palm PD can be improved through the expansion of PAs in strategic regions such as the upper portion of the Amazon Basin, Tropical Andes, and Mesoamerica.</p>
Raster-based imagery and terrain variables with wetland/deepwater polygons for select areas in the Great Lakes region
<p>Data was obtained from public sources to produce the aerial imagery, DEM, DEM-derived indices, and other raster variables. Please see that attached "DATA SOURCES & PREP METHODS.pdf" for more information.</p> <p>The shapefiles are comprised of polygons that represent wetland and deep-water classes drawn and attributed by experienced photo-interpreters and are similar to a National Wetlands Inventory (NWI; fws.gov/program/national-wetlands-inventory) product, though these have not been obtained from nor approved by the NWI Program, nor do they exist in the official NWI database.</p> <p>These data can be used for training and validating machine learning and other predictive models for wetland classification.</p>
Raster and R script Dataset
<p>Raster data and R script data used in the study.</p>
Raster layers of prioritisation analyses for current and future conditions based on phylogenetic diversity of Neotropical palms
Open the record for dataset details and reuse information.
BOREAS TE-01 Soils Data over the SSA Tower Sites in Raster Format
This data set was gridded from vector layers of soil maps that were received from Dr. Darwin Anderson TE-01 who did the original soil mapping in the field during 1994. The vector layers were gridded into raster files that cover approximately 1 square kilometer over each of the tower sites in the SSA.
SWOT Level 2 Water Mask Raster Image 100m Data Product, Version C
The SWOT Level 2 Water Mask Raster Image 100m Data Product from the Surface Water Ocean Topography (SWOT) mission provides global surface water elevation and inundation extent derived from high rate (HR) measurements from the Ka-band Radar Interferometer (KaRIn) on SWOT. SWOT launched on December 16, 2022 from Vandenberg Air Force Base in California into a 1-day repeat orbit for the "calibration" or "fast-sampling" phase of the mission, which completed in early July 2023. After the calibration phase, SWOT entered a 21-day repeat orbit in August 2023 to start the "science" phase of the mission, which is expected to continue through 2025.\r\n<br>Water surface elevation, area, water fraction, backscatter, geophysical information are provided in geographically fixed scenes at 100 meter horizontal resolution in Universal Transverse Mercator (UTM) projection. Available in netCDF-4 file format. On-demand processing available to users for different resolutions, sampling grids, scene sizes, and file formats.<br>Please note that this collection contains SWOT Version C science data products.<br><br>This collection is a sub-collection of its parent: https://podaac.jpl.nasa.gov/dataset/SWOT_L2_HR_Raster_2.0
BOREAS Regional DEM in Raster Format and AEAC Projection
This data set is based on the GTOPO30 DEM produced by the USGS EDC. The BOREAS region (1,000km x 1000km) was extracted from the GTOPO30 data and reprojected by BOREAS staff into the AEAC projection. The pixel size of these data is 1 km.
BOREAS Regional Soils Data in Raster Format and AEAC Projection
This data set was gridded by BORIS staff from a vector data set received from Canadian Soil Information System (CanSIS). The original data came in two parts that covered Saskatchewan and Manitoba. The data were gridded and merged into one data set of 84 files covering the BOReal Ecosystem-Atmosphere Study (BOREAS) region. The data were gridded into the Albers Equal-Area Conic (AEAC) projection. Because the mapping of the two provinces was done separately in the original vector data, there may be discontinuities in some of the soil layers because of different interpretations of certain soil properties.
Data over the SSA in Raster Format and AEAC Projection
This data set consists of GIS layers that describe the soils of the BOREAS SSA. The original data were submitted as vector layers that were gridded by BOREAS staff to a 30-meter pixel size in the AEAC projection. These data layers include the soil code (which relates to the soil name), modifier (which also relates to the soil name), and extent (indicating the extent that this soil exists within the polygon). There are three sets of these layers representing the primary, secondary, and tertiary soil characteristics. Thus, there is a total of nine layers in this data set along with supporting files. The data are stored in binary, image format files.
SWOT Simulated Level 2 North America Continent High Rate Raster Product Version 1.0
This dataset contains a simulated rasterized water surface elevation and inundation-extent product to be provided by the Surface Water and Ocean Topography (SWOT) mission. SWOT will provide a global coverage but this simulated subset focuses on the North America continent. This is a derived product through resampling the upstream dataset L2_HR_PIXC_V1 and L2_HR_PIXCVEC_V1 onto a uniform grid over the North America continent. A uniform grid is superimposed onto the pixel cloud from the source products, and all pixel-cloud samples within each grid cell are aggregated to produce a single value per raster cell. The raster data are produced geographically fixed tiles at resolutions of 100 m and 250 m in a Universal Transverse Mercator projection grid. Note that this is a simulated SWOT product and not suited for any scientific exploration.
BOREAS TGB-05 Fire History of Manitoba 1980 to 1991 in Raster Format
This raster format data set covers the province of Manitoba. The data were gridded into the AEAC projection from the original vector data. The original vector data were produced by Forestry Canada from hand-drawn boundaries of fires on photocopies of 1:250,000-scale maps. The locational accuracy of the data is considered fair to poor. When the locations of some fire boundaries were compared to Landsat TM images, they were found to be off by as much as a few kilometers. This problem should be kept in mind when using these data.
BOREAS Forest Cover Data Layers Over the SSA-MSA in Raster Format
This data set was prepared by BORIS staff by processing the original vector data into raster files. The original data were received as ARC/INFO coverages or as export files from SERM. The data include information on forest parameters for the BOREAS SSA MSA. The data are stored in binary, image format files.
BOREAS Follow-On DSP-09 Saskatchewan Raster Forest Fire Chronology, 1945-1996
This data set contains a pair of raster images and a spreadsheet chronicling the most recent fire history of Saskatchewan from 1945 to 1996. This data set was developed from a series of ARC/INFO export files of annual fire data that were compiled and provided by the Saskatchewan Environment and Resource Management (SERM) Wildlife Branch.
LBA-ECO LC-07 Validation Overflight for Amazon Mosaics, Raster, 1999
This data set includes high-resolution geocoded mosaics derived from the Validation Overflight for Amazon Mosaics (VOAM) aerial video surveys as part of the Large-Scale Biosphere-Atmosphere (LBA) Experiment in the Amazon. The VOAM flights were carried out in the wet-season (June) 1999 in the Brazilian Amazon to provide ground verification for mapping of wetland cover in the Amazon Basin conducted by the Global Rain Forest Mapping (GRFM) Project JERS-1 (Japanese Earth Remote Sensing Satellite). Digital camcorder systems were installed in a Bandeirante survey plane operated by Brazil's National Institute for Space Research. The VOAM99 surveys circumscribed the Brazilian Amazon, documenting ground conditions at resolutions on the order of 1-m resolution for wetlands, forests, savannas, and human-impacted areas. Geocoded mosaics were generated by processing the aerial videography into GeoTIFF format, maximizing its usefulness for environmental monitoring applications. Other applications of the VOAM99 videography include acquisition of ground control points for image geolocation, forest biomass estimation, and rapid assessment of fire damage. Geocoded digital videography provides a cost-effective means of compiling a high-resolution validation data set for land cover mapping in remote, cloud-covered regions.
BOREAS Forest Cover Layers of the NSA in Raster Format
This data set was processed by BORIS staff from the original vector data of species, crown closure, cutting class, and site classification/subtype into raster files. The original polygon data were received from Linnet Graphics, the distributor of data for MNR. In the case of the species layer, the percentages of species composition were removed. This reduced the amount of information contained in the species layer of the gridded product, but it was necessary in order to make the gridded product easier to use. The original maps were produced from 1:15,840-scale aerial photography collected in 1988.
BOREAS TE-20 Soils Data over the NSA-MSA and Tower Sites in Raster Format
This data set was gridded from vector layers of soil maps that were received from Dr. Hugo Veldhuis, who did the original mapping in the field during 1994. The vector layers were gridded into raster files that cover the NSA-MSA and tower sites.
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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.