Layers of geospatial data include contours, boundaries, land cover, hydrography, roads, transportation, geographic names, structures, and other selected map features.

Vector Data Llc Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

The computation of change vector statistics for use with the Tasselled Cap indices.

Der Datensatz " Statistische Vektoreinheiten" wird im INSPIRE-Datenmodell bereitgestellt

INSPIRE dataset for Statistical Units theme represents information about the current Statistical grid ETRS89 of the Republic of Lithuania and current area of statistical administrative units. This statistical grid has three different cell sizes: 1x1 km, 10x10 km and 100x100km. Statistical grid cells have unique codes. These codes allow the creation of links between INSPIRE data themes, such as Population Distribution – Demography and Statistical Unit themes. This dataset represents the current area of statistical administrative units: 1) NUTS1 (boundaries and area of Lithuania), 2) NUTS2 (boundaries and area of Capital region and Central and Western Lithuania region), 3) NUTS3 (boundaries and areas of counties), 4) LAU (boundaries and areas of districts). Statistical administrative units have unique codes.

The SWOT Level 2 River Single-Pass Vector Data Product (SWOT_L2_HR_RiverSP_D) provides hydrologic measurements for predefined river reaches and nodes, derived from high-resolution radar observations collected by the Ka-band Radar Interferometer (KaRIn) aboard the SWOT satellite. This product reports water surface elevation, slope, width, area, and discharge estimates for each reach, along with corresponding node-level details. All features are defined by the Prior River Database (PRD), which encodes river geometry and topology across global basins.

Each granule covers a single satellite pass over one or more continents and includes two ESRI shapefiles: one for river reaches (as polylines) and one for nodes (as points). Shapefile attributes include both SWOT-derived measurements and metadata from the PRD. Water surface elevations are referenced to the WGS84 ellipsoid and are corrected for geoid height and solid Earth, load, and pole tides. Measurements are aggregated from lower-level pixel detections (PIXC product) assigned to hydrologic features via the auxiliary PIXCVec product. The product also includes consensus and algorithm-specific river discharge estimates, both unconstrained and constrained by historical gauge data.

The RiverSP product provides reach-scale hydrologic variables suitable for analyzing inland water dynamics, estimating discharge, and monitoring river changes over time. It enables direct integration with the PRD-defined river network and supports applications in large-scale hydrologic modeling, basin monitoring, and water resource management. Data are distributed in shapefile format with metadata and attribute definitions aligned to GIS and hydrologic standards.
This dataset is the parent collection to the following sub-collections:
https://podaac.jpl.nasa.gov/dataset/SWOT_L2_HR_RiverSP_node_D
https://podaac.jpl.nasa.gov/dataset/SWOT_L2_HR_RiverSP_reach_D

Spatial coverage index compiled by East View Geospatial of set "Japan 1:25,000 Vector Data". Source data from GSI (publisher). Type: Topographic. Scale: 1:25,000. Region: Asia.

Spatial coverage index compiled by East View Geospatial of set "Netherlands 1:50,000 Scale Vector Data". Source data from TDK (publisher). Type: Topographic. Scale: 1:50,000. Region: Europe.

INSPIRE dataset for Population Distribution – Demography theme represents the main demographic characteristics for the Lithuanian population and socio-demographic variables grouped by the relevant territorial statistical in Lithuania. Also, certain variables were calculated for different gender and/or age groups, certain economic demographic variables – for different economic activities (by NACE classification). Layers of the theme are shown at a scale of 1: 1 500 000, except for PD.StatisticalDistribution.GRID layer, which is shown at a scale of 1: 25 000.

Spatial coverage index compiled by East View Geospatial of set "Czech Republic 1:250,000 Scale Vector Data". Source data from CUZK (publisher). Type: Topographic. Scale: 1:250,000. Region: Europe.

QUT Research Data Respository Dataset and Resources

Cadaster data from PDOK used to illustrate the use of geopandas and shapely, geospatial python packages for manipulating vector data. The brpgewaspercelen_definitief_2020.gpkg file has been subsetted in order to make the download manageable for workshops. Other datasets are copies of those available from PDOK.

Natural Earth is a public domain map dataset available at 1:10m, 1:50m, and 1:110 million scales. Featuring tightly integrated vector and raster data, with Natural Earth you can make a variety of visually pleasing, well-crafted maps with cartography or GIS software.

Natural Earth was built through a collaboration of many volunteers and is supported by NACIS (North American Cartographic Information Society).

Natural Earth Vector comes in ESRI shapefile format, the de facto standard for vector geodata. Character encoding is Windows-1252.

Natural Earth Vector includes features corresponding to the following:

Cultural Vector Data Thremes:

• Countries: matched boundary lines and polygons with names attributes for countries and sovereign states. Includes dependencies (French Polynesia), map units (U.S. Pacific Island Territories) and sub-national map subunits (Corsica versus mainland Metropolitan France).
• Disputed areas and breakaway regions - From Kashmir to the Elemi Triangle, Northern Cyprus to Western Sahara.
• First order admin (provinces, departments, states, etc.): internal boundaries and polygons for all but a few tiny island nations. Includes names attributes and some statistical groupings of the same for smaller countries.
• Populated places: point symbols with name attributes. Includes capitals, major cities and towns, plus significant smaller towns in sparsely inhabited regions. We favor regional significance over population census in determining rankings.
• Urban polygons: derived from 2002-2003 MODIS satellite data.
• Parks and protected areas: US National Park Service units.
• Pacific nation groupings: boxes for keeping these far-flung islands tidy.
• Water boundary indicators: partial selection of key 200-mile nautical limits, plus some disputed, treaty, and median lines.

Physical Vector Data Themes:

• Coastline: ocean coastline, including major islands. Coastline is matched to land and water polygons.
• Land: Land polygons including major islands
• Ocean: Ocean polygon split into contiguous pieces.
• Minor Islands: additional small ocean islands ranked to two levels of relative importance.
• Reefs: major coral reefs from WDB2.
• Physical region features: polygon and point labels of major physical features.
• Rivers and Lake Centerlines: ranked by relative importance. Includes name and line width attributes. Don’t want minor lakes? Turn on their centerlines to avoid unseemly data gaps.
• Lakes: ranked by relative importance, coordinating with river ranking. Includes name attributes.
• Glaciated areas: polygons derived from DCW, except for Antarctica derived from MOA. Includes name attributes for major polar glaciers.
• Antarctic ice shelves: derived from 2003-2004 MOA. Reflects recent ice shelf collapses.
• Bathymetry: nested polygons at 0, -200, -1,000, -2,000, -3,000, -4,000, -5,000, -6,000, -7,000, -8,000, -9,000,and -10,000 meters. Created from SRTM Plus.
• Geographic lines: Polar circles, tropical circles, equator, and International Date Line.
• Graticules: 1-, 5-, 10-, 15-, 20-, and 30-degree increments. Includes WGS84 bounding box.

This data set contains the Magellan Global Vector Data Record (GVDR), a sorted collection of scattering and emission measurements from the Magellan Mission. The sorting is into a grid of equal area 'pixels' distributed regularly about the planet. For data acquired from the same pixel but in different observing geometries, there is a second level of sorting to accommodate the different geometrical conditions. The 'pixel' dimension is 18.225 km. The GVDR is presented in Sinusoidal Equal Area (equatorial), Mercator (equatorial), and Polar Stereographic (polar) projections.

The SWOT Level 2 Lake Single-Pass Vector Data Product from the Surface Water Ocean Topography (SWOT) mission provides water surface elevation, area, storage change derived from the high rate (HR) data stream from the Ka-band Radar Interferometer (KaRIn). 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. Water surface elevation, area, and storage change are provided in three feature datasets covering the full swath for each continent-pass: 1) an observation-oriented feature dataset of lakes identified in the prior lake database (PLD), 2) a PLD-oriented feature dataset of lakes identified in the PLD, and 3) a feature dataset containing unassigned features (i.e., not identified in PLD nor prior river database (PRD)). These data are generally produced for inland and coastal hydrology surfaces, as controlled by the reloadable KaRIn HR mask. The dataset is distributed in ESRI Shapefile format. This dataset is the parent collection to the following sub-collections: https://podaac.jpl.nasa.gov/dataset/SWOT_L2_HR_LakeSP_obs_2.0 https://podaac.jpl.nasa.gov/dataset/SWOT_L2_HR_LakeSP_prior_2.0 https://podaac.jpl.nasa.gov/dataset/SWOT_L2_HR_LakeSP_unassigned_2.0

Spatial coverage index compiled by East View Geospatial of set "VMAP0 1:1,000,000 Scale Vector Data". Source data from NIMA (publisher). Type: Topographic. Scale: 1:1,000,000. Region: World.

Spatial coverage index compiled by East View Geospatial of set "Iran 1:100,000 Scale Geological GIS Vector Data". Source data from GSI (publisher). Type: Geoscientific - Geology. Scale: 1:100,000. Region: Middle East.

This data set contains the Atmospheric Motion Vector (AMV) data for the duration of the 2015 hurricanes Joaquin (Atlantic basin) and Patricia (Eastern Pacific basin). Data are included for the Geostationary Operational Environmental Satellites (GOES) GOES-13 (for both storms) and GOES-15 (for Patricia only). The data for Joaquin are available from 2315 UTC on 27 September to 2215 UTC 8 October 2015. The data for Patricia are available from 1200 UTC 20 October to 2215 UTC 24 October 2015. These data were provided by The Cooperative Institute for Meteorological Satellite Studies (CIMSS) at the University of Wisconsin-Madison and are in a columnar ASCII format.

the dataset includes geospatial vector point and linestring data

Benchmark data for paper "Deep Learning for Classification Tasks on Geospatial Vector Polygons". Core of the data is in the six numpy zip files. Each numpy zip contains the original WKT geometries as zlib compressed blobs, variable and fixed length geometry vectors, fourier descriptors, and a class dictionary. The zlib compressed wkt strings can be decompressed with import numpy as np import zlib loaded = np.load('archaeology_train_v8.npz') wkts_zipped = loaded['wkts_zlib_compressed'] for wkt_zipped in wkts_zipped: wkt = str.decode(zlib.decompress(wkt_zipped))