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Dataset Description:
Example Analysis:
The complete code for calculating the centroids and web scraping for the data is shared on GitHub.
The purpose of this project was to map population density center for each state.
You can also read about the complete project here: https://medium.com/@sumit.arora/plotting-weighted-mean-population-centroids-on-a-country-map-22da408c1397
Output Screenshots:
Indian districts mapped as polygons
https://i.imgur.com/UK1DCGW.png" alt="Indian districts mapped as polygons">
Mapping centroids for each district
https://i.imgur.com/KCAh7Jj.png" alt="Mapping centroids for each district">
Mean centers of population by state, 2001 vs. 2011
https://i.imgur.com/TLHPHjB.png" alt="Mean centers of population by state, 2001 vs. 2011">
National center of population
https://i.imgur.com/yYxE4Hc.png" alt="National center of population">
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TwitterThe files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. GRBA’s spatial database and map layer was produced from high-resolution 2007 Digital Map, Inc. imagery provided to CTI by the NPS. By comparing the signatures on the imagery to field and ground data, 64 map units (48 vegetated, four barren geology and snow, and 12 land-use / land-cover) were developed and the vegetation map units were directly cross-walked or matched to their corresponding rUSNVC plant associations. The interpreted and remotely sensed data were converted to Geographic Information System (GIS) spatial geodatabases and maps were printed, field tested, reviewed, and revised.
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License information was derived automatically
The graph shows the changes in the g-index of ^ and the corresponding percentile for the sake of comparison with the entire literature. g-index is a scientometric index similar to g-index but put a more weight on the sum of citations. The g-index of a journal is g if the journal has published at least g papers with total citations of g2.
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This dataset provide information about population density all over the world.
Data have been compiled from Kontur as a GeoPackage (gpkg) file format [1], 22km global hexagon population grid. Values represent number of people in cell.
GeoPackage format have been converted to Comma Separated Values format (GPKG to CSV) using by Geopandas Python library.
It contains 3 columns; H3 code, population and geometry.
- H3 is a hierarchical geospatial index that refers to cells within a spatial hierarchy..
- Population refers a group of organisms of the same species who inhabit the same particular geographical area and are capable of interbreeding [2].
- Geometry column contains polygons that store their geographic representation.
The dataset is of interest to GIS researchers, social surveyors, and geospatial data enthusiasts.
All the best!
[1] This format was published in 2014; defined by the OGC (Open Geospatial Consortium). Various governments, commercial, and open source organizations widely support the GeoPackage.
[2] "Definition of population (biology)". Oxford Dictionaries. Oxford University Press.
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TwitterThe files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the Agate Fossil Beds National Monument. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. The approach also used for Agate Fossil Beds National Monument involved mapping of association/community, height, density, and pattern.
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TwitterSpatial 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.
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This data release supports U.S. Geological Survey Scientific Investigations Report 2023-5106, Groundwater Discharge by Evapotranspiration from the Amargosa Wild and Scenic River and Contributing Areas, Inyo and San Bernardino Counties, California. Geospatial datasets presented are two polygon shapefiles representing the groundwater discharge areas and evapotranspiration units for the Amargosa Wild and Scenic River and contributing areas, and a raster dataset representing the vegetation index corresponding to the vegetated evapotranspiration unit.
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TwitterThis dataset is used to produce the CNCS state profile map for use on our website.
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TwitterThe California State Places Boundary data.
This dataset offers high-resolution boundary definitions, which allow users to analyze and visualize California’s state limits within mapping and spatial analysis projects.
The shapefile is part of a ZIP archive containing multiple related files that together define and support the boundary data. These files include:
.shp (Shape): This is the core file containing the vector data for California’s Places boundaries, representing the geographic location and geometry of the state outline.
.shx (Shape Index): A companion index file for the .shp file, allowing for quick spatial queries and efficient data access.
.dbf (Attribute Table): A database file that stores attribute data linked to the geographic features in the .shp file, such as area identifiers or classification codes, in a tabular format compatible with database applications.
.prj (Projection): This file contains projection information, specifying the coordinate system and map projection used for the data, essential for aligning it accurately on maps.
.cpg (Code Page): This optional file indicates the character encoding for the attribute data in the .dbf file, which is useful for ensuring accurate text representation in various software.
.sbn and .sbx (Spatial Index): These files serve as a spatial index for the shapefile, allowing for faster processing of spatial queries, especially for larger datasets.
.xml (Metadata): A metadata file in XML format, often following FGDC or ISO standards, detailing the dataset’s origin, structure, and usage guidelines, providing essential information about data provenance and quality.
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The graph shows the changes in the h-index of ^ and its corresponding percentile for the sake of comparison with the entire literature. H-index is a common scientometric index, which is equal to h if the journal has published at least h papers having at least h citations.
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TwitterThe Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Vegetation Indices 16-Day (MOD13C1) Version 6.1 product provides a Vegetation Index (VI) value at a per pixel basis. There are two primary vegetation layers. The first is the Normalized Difference Vegetation Index (NDVI) which is referred to as the continuity index to the existing National Oceanic and Atmospheric Administration-Advanced Very High Resolution Radiometer (NOAA-AVHRR) derived NDVI. The second vegetation layer is the Enhanced Vegetation Index (EVI), which has improved sensitivity over high biomass regions.
The Climate Modeling Grid (CMG) consists 3,600 rows and 7,200 columns of 5,600 meter (m) pixels. Global MOD13C1 data are cloud-free spatial composites of the gridded 16-day 1 kilometer MOD13A2 data, and are provided as a Level 3 product projected on a 0.05 degree (5,600 m) geographic CMG. The MOD13C1 has data fields for NDVI, EVI, VI QA, reflectance data, angular information, and spatial statistics such as mean, standard deviation, and number of used input pixels at the 0.05 degree CMG resolution.
Known Issues * For complete information about known issues please refer to the MODIS/VIIRS Land Quality Assessment website.
Improvements/Changes from Previous Versions * The Version 6.1 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: changes to the response-versus-scan angle (RVS) approach that affects reflectance bands for Aqua and Terra MODIS, corrections to adjust for the optical crosstalk in Terra MODIS infrared (IR) bands, and corrections to the Terra MODIS forward look-up table (LUT) update for the period 2012 - 2017. * A polarization correction has been applied to the L1B Reflective Solar Bands (RSB).
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This U.S. Geological Survey (USGS) data release record consists of topographic data themes that cover the Hawaiian Geospatial Fabric (HIGF) domain. The 30-meter (m) raster data sets included under Topographic Derivatives are: digital elevation (dem.tif) , topographic wetness index (TWI, twi.tif), slope (rise over run, slope.tif), aspect (asp.tif), flow accumulation (fac.tif), and flow direction (fdr.tif). All file formats are in GeoTIFF (Geographic Tagged Imaged Format).
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TwitterThe Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Vegetation Indices 16-Day (MYD13C1) Version 6.1 product provides a Vegetation Index (VI) value at a per pixel basis. There are two primary vegetation layers. The first is the Normalized Difference Vegetation Index (NDVI) which is referred to as the continuity index to the existing National Oceanic and Atmospheric Administration-Advanced Very High Resolution Radiometer (NOAA-AVHRR) derived NDVI. The second vegetation layer is the Enhanced Vegetation Index (EVI), which has improved sensitivity over high biomass regions.
The Climate Modeling Grid (CMG) consists 3,600 rows and 7,200 columns of 5,600 meter (m) pixels. Global MYD13C1 data are cloud-free spatial composites of the gridded 16-day 1 kilometer MYD13A2 data, and are provided as a Level 3 product projected on a 0.05 degree (5,600 m) geographic CMG. The MYD13C1 has data fields for NDVI, EVI, VI QA, reflectance data, angular information, and spatial statistics such as mean, standard deviation, and number of used input pixels at the 0.05 degree CMG resolution.
Known Issues * For complete information about known issues please refer to the MODIS/VIIRS Land Quality Assessment website.
Improvments/Changes from Previous Version * The Version 6.1 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: changes to the response-versus-scan angle (RVS) approach that affects reflectance bands for Aqua and Terra MODIS, corrections to adjust for the optical crosstalk in Terra MODIS infrared (IR) bands, and corrections to the Terra MODIS forward look-up table (LUT) update for the period 2012 - 2017. * A polarization correction has been applied to the L1B Reflective Solar Bands (RSB).
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TwitterThe Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Vegetation Indices Monthly (MYD13C2) Version 6.1 product provides a Vegetation Index (VI) value at a per pixel basis. There are two primary vegetation layers. The first is the Normalized Difference Vegetation Index (NDVI) which is referred to as the continuity index to the existing National Oceanic and Atmospheric Administration-Advanced Very High Resolution Radiometer (NOAA-AVHRR) derived NDVI. The second vegetation layer is the Enhanced Vegetation Index (EVI), which has improved sensitivity over high biomass regions.
The Climate Modeling Grid (CMG) consists of 3,600 rows and 7,200 columns of 5,600 meter (m) pixels. In generating this monthly product, the algorithm ingests all the MYD13A2 products that overlap the month and employs a weighted temporal average. Global MYD13C1 data are cloud-free spatial composites and are provided as a Level 3 product projected on a 0.05 degree (5,600 m) geographic CMG. The MYD13C2 has data fields for the NDVI, EVI, VI QA, reflectance data, angular information, and spatial statistics such as mean, standard deviation, and number of used input pixels at the 0.05 degree CMG resolution.
Known Issues * For complete information about known issues please refer to the MODIS/VIIRS Land Quality Assessment website.
Improvments/Changes from Previous Version * The Version 6.1 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: changes to the response-versus-scan angle (RVS) approach that affects reflectance bands for Aqua and Terra MODIS, corrections to adjust for the optical crosstalk in Terra MODIS infrared (IR) bands, and corrections to the Terra MODIS forward look-up table (LUT) update for the period 2012 - 2017. * A polarization correction has been applied to the L1B Reflective Solar Bands (RSB).
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License information was derived automatically
The graph shows the changes in the g-index of ^ and the corresponding percentile for the sake of comparison with the entire literature. g-index is a scientometric index similar to g-index but put a more weight on the sum of citations. The g-index of a journal is g if the journal has published at least g papers with total citations of g2.
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TwitterThe Barrow Area Information Database (BAID) data collection is comprised of geospatial data for the research hubs of Barrow, Atqasuk and Ivotuk on Alaska's North Slope. Over 9600 research plots and instrument locations are included in the BAID research sites database. Updates to the project tracking database are ongoing through field mapping of new research locations and extant sampling sites dating back to the 1940s. Many ancillary data layers are also compiled to facilitate research activities and science communication. These geospatial data sets have been compiled through BAID and related NSF efforts. Geospatial data unique to this project are currently browseable via the BAID archive and include shapefiles of research information (sampling sites and instrumentation, the NOAA-CMDL clean air sector), administrative units (Barrow Environmental Observatory Science Research District plus adjacent federal lands, village districts, zoning, tax parcels, and the Ukpeagvik Inupiat Corporation boundary), infrastructure (power poles, snow fences, roads), erosion data for Elson Lagoon and imagery (declassified military imagery, air photo mosaics, IKONOS, Landsat, Quickbird, SAR and flight line indexes). Related data sets can be browsed via BAID’s web mapping tools and downloaded via the “Related links” section below. In addition, the BAID Internet Map Server (BAID-IMS) provides browse access to a number of additional layers which are available for download through catalog pages at the National Snow and Ice Data Center (NSIDC), the Alaska Geospatial Data Clearinghouse at USGS and the Alaska State Geo-Spatial Data Clearinghouse. Some layers are proprietary and are only available for browse access in BAID-IMS through special agreement. BAID provides a suite of user interfaces (Internet Map Server, Google Earth and Adobe Flex) and Open Geospatial Consortium web services for accessing the research plots and instrument locations. For more information on...
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TwitterThe files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. The mapping component of the GOSP project used a combination of methods to interpret and delineate vegetation polygons. The initial set of polygons was drawn and annotated in the field on a 1:3500-scale print of the base true-color orthoimagery. The lines were transferred to a digital environment in an ArcMap personal geodatabase using on-screen digitizing methods. Each polygon was assigned a map class number, alpha code and name, Anderson land use class, and vegetation density, pattern, and height attributes. In order to improve the utility of the map and related data, the spatial database was moved into a geodatabase format, the general structure of which is illustrated in Figure 13. This format allows text and image information to be incorporated and linked to spatial coordinates. Detailed documentation of the geodatabase is provided in Appendix C. All geospatial products associated with this project are in the UTM projection, NAD83, Zone 12.
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The Southwestern Region is 20.6 million acres. There are six national forests in Arizona, five national forests and a national grassland in New Mexico, and one national grassland each in Oklahoma and the Texas panhandle.The region ranges in elevation from 1,600 feet above sea level and an annual rain fall of 8 inches in Arizona's lower Sonoran Desert to 13,171-foot high Wheeler Peak and over 35 inches of precipitation a year in northern New Mexico. Geographic Information Systems or GIS are computer systems, software and data used to analyze and display spatial or locational data about surface features. One of the strengths of GIS is the capability to overlay or compare multiple feature layers. A user can then analyze the relationship between the layers. Data, reports and maps produced through GIS are used by managers and resource specialists to make decisions about land management activities on National Forests. The National Forests of the Southwestern Region maintain and utilize GIS data for various features on the ground. Some of these datasets are made available for download through this page. Resources in this dataset:Resource Title: GIS Datasets. File Name: Web Page, url: https://www.fs.usda.gov/detail/r3/landmanagement/gis/?cid=STELPRDB5202474 Selected GIS datasets for the Southwestern Region are available for download from this page.Resource Software Recommended: ArcExplorer,url: http://www.esri.com/software/arcexplorer/index.html
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TwitterSpatial coverage index compiled by East View Geospatial of set "Colombia 1:100,000 Scale Topographic Maps (DMA E671)". Source data from DMA (publisher). Type: Topographic. Scale: 1:100,000. Region: South America.
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The Geospatial Data Gateway (GDG) provides access to a map library of over 100 high resolution vector and raster layers in the Geospatial Data Warehouse. It is the one stop source for environmental and natural resource data, available anytime, from anywhere. It allows a user to choose an area of interest, browse and select data, customize the format, then download or have it shipped on media. The map layers include data on: Public Land Survey System (PLSS), Census data, demographic statistics, precipitation, temperature, disaster events, conservation easements, elevation, geographic names, geology, government units, hydrography, hydrologic units, land use and land cover, map indexes, ortho imagery, soils, topographic images, and streets and roads. This service is made available through a close partnership between the three Service Center Agencies (SCA): Natural Resources Conservation Service (NRCS), Farm Service Agency (FSA), and Rural Development (RD). Resources in this dataset:Resource Title: Geospatial Data Gateway. File Name: Web Page, url: https://gdg.sc.egov.usda.gov This is the main page for the GDG that includes several links to view, download, or order various datasets. Find additional status maps that indicate the location of data available for each map layer in the Geospatial Data Gateway at https://gdg.sc.egov.usda.gov/GDGHome_StatusMaps.aspx
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Dataset Description:
Example Analysis:
The complete code for calculating the centroids and web scraping for the data is shared on GitHub.
The purpose of this project was to map population density center for each state.
You can also read about the complete project here: https://medium.com/@sumit.arora/plotting-weighted-mean-population-centroids-on-a-country-map-22da408c1397
Output Screenshots:
Indian districts mapped as polygons
https://i.imgur.com/UK1DCGW.png" alt="Indian districts mapped as polygons">
Mapping centroids for each district
https://i.imgur.com/KCAh7Jj.png" alt="Mapping centroids for each district">
Mean centers of population by state, 2001 vs. 2011
https://i.imgur.com/TLHPHjB.png" alt="Mean centers of population by state, 2001 vs. 2011">
National center of population
https://i.imgur.com/yYxE4Hc.png" alt="National center of population">