Shapefiles information containing the basic information about the spatial structure of the STIB-MIVB network: route of the lines and position of the stops of the "commercial" network, that is the basic itineraries "to" and "from".

Context

When I started exploring how to create interactive maps (using the leaflet() package in R) I come across this free data set (shapefile format) that contains the geographical coordinates (polygons) for all the countries in the world. I thought it would be nice to share this with the Kaggle community.

Content

The .zip folder contains all the necessary files needed for the shapefile data to work properly on your computer. If you are new to using the shapefile format, please see the information provided below:

https://en.wikipedia.org/wiki/Shapefile "The shapefile format stores the data as primitive geometric shapes like points, lines, and polygons. These shapes, together with data attributes that are linked to each shape, create the representation of the geographic data. The term "shapefile" is quite common, but the format consists of a collection of files with a common filename prefix, stored in the same directory. The three mandatory files have filename extensions .shp, .shx, and .dbf. The actual shapefile relates specifically to the .shp file, but alone is incomplete for distribution as the other supporting files are required. "

Acknowledgements

Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com.

Data from various sources, including 2018 and 2019 multibeam bathymetry data collected by the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Geological Survey (USGS) were combined to create a composite 30-m resolution multibeam bathymetry surface of central Cascadia Margin offshore Oregon. These metadata describe the polygon shapefile that outlines and identifies each publicly available bathymetric dataset. The data are available as a polygon shapefile.

The Residential Schools Locations Dataset in shapefile format contains the locations (latitude and longitude) of Residential Schools and student hostels operated by the federal government in Canada. All the residential schools and hostels that are listed in the Indian Residential School Settlement Agreement are included in this data set, as well as several Industrial schools and residential schools that were not part of the IRRSA. This version of the dataset doesn’t include the five schools under the Newfoundland and Labrador Residential Schools Settlement Agreement. The original school location data was created by the Truth and Reconciliation Commission, and was provided to the researcher (Rosa Orlandini) by the National Centre for Truth and Reconciliation in April 2017. The data set was created by Rosa Orlandini, and builds upon and enhances the previous work of the Truth and Reconcilation Commission, Morgan Hite (creator of the Atlas of Indian Residential Schools in Canada that was produced for the Tk'emlups First Nation and Justice for Day Scholar's Initiative, and Stephanie Pyne (project lead for the Residential Schools Interactive Map). Each individual school location in this dataset is attributed either to RSIM, Morgan Hite, NCTR or Rosa Orlandini. Many schools/hostels had several locations throughout the history of the institution. If the school/hostel moved from its’ original location to another property, then the school is considered to have two unique locations in this data set,the original location and the new location. For example, Lejac Indian Residential School had two locations while it was operating, Stuart Lake and Fraser Lake. If a new school building was constructed on the same property as the original school building, it isn't considered to be a new location, as is the case of Girouard Indian Residential School. When the precise location is known, the coordinates of the main building are provided, and when the precise location of the building isn’t known, an approximate location is provided. For each residential school institution location, the following information is provided: official names, alternative name, dates of operation, religious affiliation, latitude and longitude coordinates, community location, Indigenous community name, contributor (of the location coordinates), school/institution photo (when available), location point precision, type of school (hostel or residential school) and list of references used to determine the location of the main buildings or sites. The geographic coordinate system for this dataset is WGS 1984. The data in shapefile format [IRS_locations.zip] can be viewed and mapped in a Geographic Information System software. Detailed metadata in xml format is available as part of the data in shapefile format. In addition, the field name descriptions (IRS_locfields.csv) and the detailed locations descriptions (IRS_locdescription.csv) should be used alongside the data in shapefile format.

Abstract

The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.

These shapefiles are used to create the maps in NAM2.6.2. They are mostly derived from the input files for the groundwater model. The shape files infclude:

ag_extraction: These are points that represent the location of groundwater bores used for agricultural extraction.

boundaries: These are line shape files used for defining the location and extent of lateral boundary conditions of different stratigraphic layers of the groundwater model

coal extraction: These are polygon shape files providing the areal extent of the baseline and ACRD coal mines in the Namoi subregion that are including in the groundwater model.

grid: Polygon shape file representing the mesh of the groundwater model. It also include points that represent the midpoints of each model cell and the suset that represents the model nodes that outcrop.

obs: Shape file of observation bores, the data from which is used for constraining the groundwater model.

River: Set of shape files containing the AWRA catchments, AWRA-R nodes, network of rivers and creeks classified into important reaches and non important reaches based on the distance form the CRDP areas, extent of flood and irrigation recharge

Purpose

The purpose of this dataset is to create pretty pictures. The actual model inputs files are archived separately.

These shapefiles are used along with the software ALGOMESH to generate inputs for the models including model initial and boundary conditions.

Thease are also used to generate maps in the product 2.6.2

Dataset History

Some of the components of this dataset are source data. These include the locations of groundwater and observation bores, river and creek network.

Other components are derived:

The groundwater model mesh and model cell centres are generated in the ALGOMESH software and exported as shape file.

The coal mine extents are derived from digitized mine footprints.

Dataset Citation

Bioregional Assessment Programme (2016) Namoi groundwater model input shapefiles. Bioregional Assessment Derived Dataset. Viewed 11 December 2018, http://data.bioregionalassessments.gov.au/dataset/fb22671f-8b47-48e2-9fcd-232543fb8ad6.

Dataset Ancestors

• Derived From Murray-Darling Basin floodplain inundation 1 in 100 year extent

• Derived From Bioregional_Assessment_Programme_Catchment-scale Land Use Management (CLUM)

• Derived From NSW Office of Water - National Groundwater Information System 20141101v02

• Derived From Namoi groundwater observation bores

• Derived From GEODATA TOPO 250K Series 3, File Geodatabase format (.gdb)

• Derived From GEODATA TOPO 250K Series 3

• Derived From Hydstra Groundwater Measurement Update - NSW Office of Water, Nov2013

Abstract This dataset was created within the Bioregional Assessment Programme for cartographic purposes. Data has not been derived from any source datasets. Metadata has been compiled by the Bioregional Assessment Programme. The dataset was created by the Bioregional Assessment Programme for use in cartographic outputs in Gippsland Basin bioregion product 1.1.4. The processes undertaken to produce this dataset are described in the History field in this metadata statement. Purpose Cartographic …Show full descriptionAbstract This dataset was created within the Bioregional Assessment Programme for cartographic purposes. Data has not been derived from any source datasets. Metadata has been compiled by the Bioregional Assessment Programme. The dataset was created by the Bioregional Assessment Programme for use in cartographic outputs in Gippsland Basin bioregion product 1.1.4. The processes undertaken to produce this dataset are described in the History field in this metadata statement. Purpose Cartographic masks for map products GIP 114, used for clear annotation and masking unwanted features from report maps. Dataset History A shapefile was created for the use of masking data to highlight text. Method: * A new polygon shapefile was created with no content * The shapefile was then populated in an ArcMap editing session by digitizing polygons which surround text. * ArcMAP's Advanced Drawing Option was then used to mask data behind text. Dataset Citation Bioregional Assessment Programme (2015) Cartographic masks for map products GIP 114. Bioregional Assessment Source Dataset. Viewed 29 September 2017, http://data.bioregionalassessments.gov.au/dataset/cf55e8a5-5543-4284-8ef8-121059ea59b2.

Abstract This dataset was created within the Bioregional Assessment Programme for cartographic purposes. Data has not been derived from any source datasets. Metadata has been compiled by the Bioregional Assessment Programme. Cartographic masks for map products GAL group 2 products, used for clear annotation and masking unwanted features from report maps. ## Dataset History A shapefile was created for the use of masking data to highlight text. Method: * A new polygon shapefile was created with no content * The shapefile was then populated in an ArcMap editing session by digitizing polygons which surround text. * ArcMAP's Advanced Drawing Option was then used to mask data behind text. ## Dataset Citation Bioregional Assessment Programme (2015) Cartographic masks for water level trend map products GAL213. Bioregional Assessment Source Dataset. Viewed 07 December 2018, http://data.bioregionalassessments.gov.au/dataset/c714da92-0434-423d-85d0-f48242825fb9.

Abstract This dataset was created within the Bioregional Assessment Programme for cartographic purposes. Data has not been derived from any source datasets. Metadata has been compiled by the Bioregional Assessment Programme. This dataset contains shapefiles used mask features and layers in maps which are unwanted, or behind annotation layers, for clearer map presentation. This dataset is used for the report maps in the Bioregional Assessment Galilee Product 1.1 - Chapter 3. ## Purpose Cartographic masking to enhance label and feature legibility for maps in chapter 3 of the Bioregional Assessment Galilee subregion Product 1.1 ## Dataset History A shapefile was created for the use of masking data to highlight text. Method: * A new polygon shapefile was created with no content * The shapefile was then populated in an ArcMap editing session by digitizing polygons which surround text. * ArcMAP's Advanced Drawing Option was then used to mask data behind text. ## Dataset Citation Bioregional Assessment Programme (2014) Cartographic masks for map products GAL113. Bioregional Assessment Source Dataset. Viewed 10 December 2018, http://data.bioregionalassessments.gov.au/dataset/4b07aa28-d1a3-4311-9396-c30e8e00c9ce.

Dataset

This dataset was created by Gaurav Srivastav

Contents

Abstract

This dataset was created within the Bioregional Assessment Programme for cartographic purposes. Data has not been derived from any source datasets. Metadata has been compiled by the Bioregional Assessment Programme.

Cartographic masks for map products GAL_120, used for clear annotation and masking unwanted features from report maps.

Dataset History

A shapefile was created for the use of masking data to highlight text.

Method:

* A new polygon shapefile was created with no content

* The shapefile was then populated in an ArcMap editing session by digitizing polygons which surround text.

* ArcMAP's Advanced Drawing Option was then used to mask data behind text.

Dataset Citation

Bioregional Assessment Programme (2014) Cartographic masks for map products GAL120. Bioregional Assessment Source Dataset. Viewed 12 December 2018, http://data.bioregionalassessments.gov.au/dataset/77b92796-9501-4829-9b41-598dd455ca93.

Abstract

The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.

This shapefile shows the extent of the Grafton-Piora bedrock in the CLM bioregion.

Dataset History

The shapefile is based on the digital 1:250000 surface geological map (see lineage) obtained from the Clarence-Moreton SEEBASE project in NSW. This polygon shapefile has been created from a preliminary dataset provided by the NSW Geological Survey. The original shapefile consisted of multiple polygons that have been separated for example where alluvia overlie this bedrock unit. The polygons have been dissolved to create a single shapefile that shows the extent of the unit at the surface and in the subsurface.

Dataset Citation

Bioregional Assessment Programme (2014) CLM - Grafton-Piora bedrock. Bioregional Assessment Derived Dataset. Viewed 28 September 2017, http://data.bioregionalassessments.gov.au/dataset/59addbea-b8a5-4409-9c36-da260efe81f1.

Dataset Ancestors

• Derived From Qld 100K mapsheets - Allora

• Derived From CLM - Geology NSW & Qld combined v02

• Derived From Qld 100k mapsheets - Warwick

• Derived From CLM - Qld Surface Geology Mapsheets

• Derived From Qld 100k mapsheets - Beenleigh

• Derived From Qld 100K mapsheets - Caboolture

• Derived From Qld 100K mapsheets - Ipswich

• Derived From Qld 100K mapsheets - Mount Lindsay

• Derived From Qld 100K mapsheets - Esk

• Derived From Qld 100K mapsheets - Toowoomba

• Derived From Clarence-Moreton SEEBASE & Structural GIS Project data.

• Derived From Qld 100K mapsheets - Helidon

• Derived From CLM - NSW Surface Geology Mapsheets in the Clarence-Moreton bioregion

• Derived From Qld 100K mapsheets - Jandowae

• Derived From NSW Geological Survey - geological units DRAFT line work.

• Derived From Qld 100K mapsheets - Inglewood

• Derived From Qld 100K mapsheets - Oakey

• Derived From Qld 100k mapsheets - Murwillumbah

• Derived From Qld 100k mapsheets - Kingaroy

The CalFish Abundance Database contains a comprehensive collection of anadromous fisheries abundance information. Beginning in 1998, the Pacific States Marine Fisheries Commission, the California Department of Fish and Game, and the National Marine Fisheries Service, began a cooperative project aimed at collecting, archiving, and entering into standardized electronic formats, the wealth of information generated by fisheries resource management agencies and tribes throughout California.Extensive data are currently available for chinook, coho, and steelhead. Major data categories include adult abundance population estimates, actual fish and/or carcass counts, counts of fish collected at dams, weirs, or traps, and redd counts. Harvest data has been compiled for many streams, and hatchery return data has been compiled for the states mitigation facilities. A draft format has been developed for juvenile abundance and awaits final approval. This CalFish Abundance Database shapefile was generated from fully routed 1:100,000 hydrography. In a few cases streams had to be added to the hydrography dataset in order to provide a means to create shapefiles to represent abundance data associated with them. Streams added were digitized at no more than 1:24,000 scale based on stream line images portrayed in 1:24,000 Digital Raster Graphics (DRG).These features generally represent abundance counts resulting from stream surveys. The linear features in this layer typically represent the location for which abundance data records apply. This would be the reach or length of stream surveyed, or the stream sections for which a given population estimate applies. In some cases the actual stream section surveyed was not specified and linear features represent the entire stream. In many cases there are multiple datasets associated with the same length of stream, and so, linear features overlap. Please view the associated datasets for detail regarding specific features. In CalFish these are accessed through the "link" that is visible when performing an identify or query operation. A URL string is provided with each feature in the downloadable data which can also be used to access the underlying datasets.The coho data that is available via the CalFish website is actually linked directly to the StreamNet website where the database's tabular data is currently stored. Additional information about StreamNet may be downloaded at http://www.streamnet.org. Complete documentation for the StreamNet database may be accessed at http://http://www.streamnet.org/def.html

This data publication is a compilation of six different multibeam surveys covering the previously unmapped Queen Charlotte Fault offshore southeast Alaska and Haida Gwaii, Canada. These data were collected between 2005 and 2018 under a cooperative agreement between the U.S. Geological Survey, Natural Resources Canada, and the National Oceanic and Atmospheric Administration. The six source surveys from different multibeam sonars are combined into one terrain model with a 30-meter resolution. A complementary polygon shapefile records the extent of each source survey in the output grid.

This resource contains the test data for the GeoServer OGC Web Services tutorials for various GIS applications including ArcGIS Pro, ArcMap, ArcGIS Story Maps, and QGIS. The contents of the data include a polygon shapefile, a polyline shapefile, a point shapefile, and a raster dataset; all of which pertain to the state of Utah, USA. The polygon shapefile is of every county in the state of Utah. The polyline is of every trail in the state of Utah. The point shapefile is the current list of GNIS place names in the state of Utah. The raster dataset covers a region in the center of the state of Utah. All datasets are projected to NAD 1983 Zone 12N.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Face refers to the areal (polygon) topological primitives that make up MTDB. A face is bounded by one or more edges; its boundary includes only the edges that separate it from other faces, not any interior edges contained within the area of the face. The Topological Faces Shapefile contains the attributes of each topological primitive face. Each face has a unique topological face identifier (TFID) value. Each face in the shapefile includes the key geographic area codes for all geographic areas for which the Census Bureau tabulates data for both the 2020 Census and the annual estimates and surveys. The geometries of each of these geographic areas can then be built by dissolving the face geometries on the appropriate key geographic area codes in the Topological Faces Shapefile.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Face refers to the areal (polygon) topological primitives that make up MTDB. A face is bounded by one or more edges; its boundary includes only the edges that separate it from other faces, not any interior edges contained within the area of the face. The Topological Faces Shapefile contains the attributes of each topological primitive face. Each face has a unique topological face identifier (TFID) value. Each face in the shapefile includes the key geographic area codes for all geographic areas for which the Census Bureau tabulates data for both the 2020 Census and the annual estimates and surveys. The geometries of each of these geographic areas can then be built by dissolving the face geometries on the appropriate key geographic area codes in the Topological Faces Shapefile.

This city boundary shapefile was extracted from Esri Data and Maps for ArcGIS 2014 - U.S. Populated Place Areas. This shapefile can be joined to 500 Cities city-level Data (GIS Friendly Format) in a geographic information system (GIS) to make city-level maps.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. ZIP Code Tabulation Areas (ZCTAs) are approximate area representations of U.S. Postal Service (USPS) ZIP Code service areas that the Census Bureau creates to present statistical data for each decennial census. The Census Bureau delineates ZCTA boundaries for the United States, Puerto Rico, American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands once each decade following the decennial census. Data users should not use ZCTAs to identify the official USPS ZIP Code for mail delivery. The USPS makes periodic changes to ZIP Codes to support more efficient mail delivery. The Census Bureau uses tabulation blocks as the basis for defining each ZCTA. Tabulation blocks are assigned to a ZCTA based on the most frequently occurring ZIP Code for the addresses contained within that block. The most frequently occurring ZIP Code also becomes the five-digit numeric code of the ZCTA. These codes may contain leading zeros. Blocks that do not contain addresses but are surrounded by a single ZCTA (enclaves) are assigned to the surrounding ZCTA. Because the Census Bureau only uses the most frequently occurring ZIP Code to assign blocks, a ZCTA may not exist for every USPS ZIP Code. Some ZIP Codes may not have a matching ZCTA because too few addresses were associated with the specific ZIP Code or the ZIP Code was not the most frequently occurring ZIP Code within any of the blocks where it exists. The ZCTA boundaries in this release are those delineated following the 2020 Census.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Edge refers to the linear topological primitives that make up MTDB. The All Lines Shapefile contains linear features such as roads, railroads, and hydrography. Additional attribute data associated with the linear features found in the All Lines Shapefile are available in relationship (.dbf) files that users must download separately. The All Lines Shapefile contains the geometry and attributes of each topological primitive edge. Each edge has a unique TIGER/Line identifier (TLID) value.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The TIGER/Line shapefiles include both incorporated places (legal entities) and census designated places or CDPs (statistical entities). An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division (MCD), which generally is created to provide services or administer an area without regard, necessarily, to population. Places always nest within a state, but may extend across county and county subdivision boundaries. An incorporated place usually is a city, town, village, or borough, but can have other legal descriptions. CDPs are delineated for the decennial census as the statistical counterparts of incorporated places. CDPs are delineated to provide data for settled concentrations of population that are identifiable by name, but are not legally incorporated under the laws of the state in which they are located. The boundaries for CDPs often are defined in partnership with state, local, and/or tribal officials and usually coincide with visible features or the boundary of an adjacent incorporated place or another legal entity. CDP boundaries often change from one decennial census to the next with changes in the settlement pattern and development; a CDP with the same name as in an earlier census does not necessarily have the same boundary. The only population/housing size requirement for CDPs is that they must contain some housing and population. The boundaries of most incorporated places in this shapefile are as of January 1, 2020, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The boundaries of all CDPs were delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census.