The attached zip file contains the shapefile for Oakland's city council districts. You need all the files included in the zip file to open the .shp file, so please download the whole zip archive.

The 2022 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. This file depicts the shape of the United States clipped back to a generalized coastline. This nation layer covers the extent of the fifty states, the District of Columbia, Puerto Rico, and each of the Island Areas (American Samoa, the Commonwealth of the Northern Mariana Islands, Guam, and the U.S. Virgin Islands) when scale appropriate.

Ferromanganese crusts in the world's oceans may serve as potential sources of metals, such as cobalt and magnesium, valuable to civilian and military industry; these are metals that the United States would otherwise be dependent on foreign sources. Unlike abyssal ferromanganese nodules, which form in areas of low disturbance and high sediment accumulation, ferromanganese crusts have been found to contain three to five times more cobalt than abyssal ferromanganese nodules and can be found on harder, steeper substrates than abyssal plains, which can be too steep for permanent sediment accumulation. Ferromanganese crusts have also been documented on seamounts and plateaus within the U.S. exclusive economic zone in the Pacific and Atlantic Oceans and are therefore of strategic importance to the United States Government as well as to civilian mining and metallurgical industries. A database containing ferromanganese crust occurrences throughout the world's oceans was assembled from pu ...

This data package contains extracts from open datasets to support
the tutorials available at https://github.com/nismod/snail/

This version of the data goes with v0.1 of the tutorials:

https://github.com/nismod/snail/releases/tag/v0.1

WRI Aqueduct Flood Hazard Maps

`flood_layer` contains data extracted and derived from the Aqueduct
Flood Hazard Maps (version 2, updated October 20, 2020).

See https://www.wri.org/resources/data-sets/aqueduct-floods-hazard-maps

These data are shared under the CC-BY Creative Commons Attribution
License 4.0 - https://creativecommons.org/licenses/by/4.0/

Citation: Ward, P.J., H.C. Winsemius, S. Kuzma,
M.F.P. Bierkens, A. Bouwman, H. de Moel, A. Díaz Loaiza, et
al. 2020. “Aqueduct Floods Methodology.” Technical Note.
Washington, D.C.: World Resources Institute. Available online at:
www.wri.org/publication/aqueduct-floods-methodology.

Ghana - Subnational Administrative Boundaries

`gha_admbnda_gss_20210308_shp` contains data from Ghana Statistical
Services (GSS) contributed to Humanitarian Data Exchange by the OCHA
Regional Office for West and Central Africa, updated 11 March 2021.

See https://data.humdata.org/m/dataset/ghana-administrative-boundaries

These data are shared under the Creative Commons Attribution for
Intergovernmental Organisations (CC BY-IGO) - https://creativecommons.org/licenses/by/3.0/igo/

Ghana OpenStreetMap Extract

`ghana-latest-free.shp` contains data extracted from OpenStreetMap
and downloaded from GeoFabrik.

The files in this archive have been created from OpenStreetMap data
and are licensed under the Open Database 1.0 License. See
www.openstreetmap.org for details about the project.

This file contains OpenStreetMap data as of 2021-03-22T21:21:57Z.

More recent updates will be made available daily here:

http://download.geofabrik.de/africa/ghana-latest-free.shp.zip

A documentation of the layers in this shape file is available here:

http://download.geofabrik.de/osm-data-in-gis-formats-free.pdf

Ghana Road Network

`GHA_OSM_roads.gpkg` contains data derived from the OpenStreetMap
extract above, and can be reproduced by running through nismod/snail
tutorial 01.

These data are shared under the same Open Database 1.0 License. See
www.openstreetmap.org for details about the project.

Natural Earth Country Boundaries

`ne_10m_admin_0_countries` contains Natural Earth 1:10m Cultural Vectors,
Admin ) - Countries version 4.1.0

See https://www.naturalearthdata.com/downloads/10m-cultural-vectors/10m-admin-0-countries/

These data are declared to be in the public domain, and may be shared
and modified without restriction - https://www.naturalearthdata.com/about/terms-of-use/

QGIS project

`overview.qgz` is a QGIS project intended to help preview and explore
the data in this package.

It is shared under the CC-BY Creative Commons Attribution
License 4.0 - https://creativecommons.org/licenses/by/4.0/

Please cite it as part of this data package, by Tom Russell (2021).

Results

`results` contains the results of analysis that can be reproduced
by running through all the nismod/snail tutorials.

These are derived from all the data above, shared under the
combined terms of Open Database 1.0 License and CC-BY licenses as
applicable to derived, extracted and modified data.

This is a link to the QGIS website where you can download open-source GIS software for viewing, analyzing and manipulating geodata like our downloadable shapefiles.

Legal boundries of Marin County including embedded shoreline

These data are the urban woodland habitat networks of eleven different cities: Nottingham, Plymouth, Stoke-on-Trent, Milton Keynes, Coventry, Wolverhampton, Northampton, Birkenhead, Derby, Luton and Kingston-Upon-Hull.Three types of data are used to create the shape files:The OS MasterMap Topography (EDINA Digimap Ordnance Survey Service, 2024) ‘Natural Environment’ layer.This was overlain upon the latest version of the LandCover Map (EDINA Environment Digimap Service, 2022) for each urban area using QGIS (https://qgis.org/). Urban area boundaries were determined and clipped using the experimental urban extent polygons for the UK (ONS, 2019).ReferencesEDINA Digimap Ordnance Survey Service (2024) OS MasterMap® Topography Layer [GeoPackage geospatial data], Scale 1:1250, Tiles: GB, Updated: 1 February 2024, Ordnance Survey (GB). Available at: https://digimap.edina.ac.uk (Accessed: 10 July 2024).EDINA Environment Digimap Service (2022) Land Cover Map 2021 [FileGeoDatabase geospatial data], Scale 1:250000, Tiles: GB, Updated: 10 August 2022, CEH. Available at: https://digimap.edina.ac.uk (Accessed: 10 July 2024).ONS (2019) Experimental urban extent for UK - Office for National Statistics. Available at: https://www.ons.gov.uk/aboutus/transparencyandgovernance/experimentalurbanextentforuk (Accessed: 26 August 2024).

A Shape file of Nigeria detailing boundaries of Local Government Areas and communities.

There are two types of boundary files: cartographic and digital. Cartographic boundary files portray the geographic areas using only the major land mass of Canada and its coastal islands. Digital boundary files portray the full extent of the geographic areas, including the coastal water area.

Complete Topographic dataset in shapefile format. Consume this dataset if you wish to download the entire Topographic dataset at once.

This dataset contains all zip codes in Montgomery County. Zip codes are the postal delivery areas defined by USPS. Zip codes with mailboxes only are not included.

As this is geographic data, SHP and KMZ formats are available for download.

This is an ESRI shape file of school point locations based on the official address. It includes some additional basic and pertinent information needed to link to other data sources. It also includes some basic school information such as Name, Address, Principal, and Principal’s contact information.

The center's "Topographic Map Digital Data File for Economic Development (scale of 1:25,000, 1:50,000 and 1:100,000)" was classified as Category A data at the "2nd meeting of the Administrative Data Open Consultation Subgroup of the Executive Yuan in 2016." It was also revised and published by the Ministry of the Interior on July 26, 2016 under Order No. 1051306149 of the Taiwan Ministry of the Interior, amending the "Charging Standards for Land Surveying and Mapping Results Data" in Appendix 2 of Article 2, and the data is open for free download and use. This data is the result of the planning update from 112 to 116.

This dataset contains shapefile boundaries for CA State, counties and places from the US Census Bureau's 2023 MAF/TIGER database. Current geography in the 2023 TIGER/Line Shapefiles generally reflects the boundaries of governmental units in effect as of January 1, 2023.

TRCA GIS Open data on ArcGIS online. This link will take you to an external site URL: https://trca-camaps.opendata.arcgis.com/

The Ontario government, generates and maintains thousands of datasets. Since 2012, we have shared data with Ontarians via a data catalogue. Open data is data that is shared with the public. Click here to learn more about open data and why Ontario releases it. Ontario’s Open Data Directive states that all data must be open, unless there is good reason for it to remain confidential. Ontario’s Chief Digital and Data Officer also has the authority to make certain datasets available publicly. Datasets listed in the catalogue that are not open will have one of the following labels: If you want to use data you find in the catalogue, that data must have a licence – a set of rules that describes how you can use it. A licence: Most of the data available in the catalogue is released under Ontario’s Open Government Licence. However, each dataset may be shared with the public under other kinds of licences or no licence at all. If a dataset doesn’t have a licence, you don’t have the right to use the data. If you have questions about how you can use a specific dataset, please contact us. The Ontario Data Catalogue endeavors to publish open data in a machine readable format. For machine readable datasets, you can simply retrieve the file you need using the file URL. The Ontario Data Catalogue is built on CKAN, which means the catalogue has the following features you can use when building applications. APIs (Application programming interfaces) let software applications communicate directly with each other. If you are using the catalogue in a software application, you might want to extract data from the catalogue through the catalogue API. Note: All Datastore API requests to the Ontario Data Catalogue must be made server-side. The catalogue's collection of dataset metadata (and dataset files) is searchable through the CKAN API. The Ontario Data Catalogue has more than just CKAN's documented search fields. You can also search these custom fields. You can also use the CKAN API to retrieve metadata about a particular dataset and check for updated files. Read the complete documentation for CKAN's API. Some of the open data in the Ontario Data Catalogue is available through the Datastore API. You can also search and access the machine-readable open data that is available in the catalogue. How to use the API feature: Read the complete documentation for CKAN's Datastore API. The Ontario Data Catalogue contains a record for each dataset that the Government of Ontario possesses. Some of these datasets will be available to you as open data. Others will not be available to you. This is because the Government of Ontario is unable to share data that would break the law or put someone's safety at risk. You can search for a dataset with a word that might describe a dataset or topic. Use words like “taxes” or “hospital locations” to discover what datasets the catalogue contains. You can search for a dataset from 3 spots on the catalogue: the homepage, the dataset search page, or the menu bar available across the catalogue. On the dataset search page, you can also filter your search results. You can select filters on the left hand side of the page to limit your search for datasets with your favourite file format, datasets that are updated weekly, datasets released by a particular organization, or datasets that are released under a specific licence. Go to the dataset search page to see the filters that are available to make your search easier. You can also do a quick search by selecting one of the catalogue’s categories on the homepage. These categories can help you see the types of data we have on key topic areas. When you find the dataset you are looking for, click on it to go to the dataset record. Each dataset record will tell you whether the data is available, and, if so, tell you about the data available. An open dataset might contain several data files. These files might represent different periods of time, different sub-sets of the dataset, different regions, language translations, or other breakdowns. You can select a file and either download it or preview it. Make sure to read the licence agreement to make sure you have permission to use it the way you want. Read more about previewing data. A non-open dataset may be not available for many reasons. Read more about non-open data. Read more about restricted data. Data that is non-open may still be subject to freedom of information requests. The catalogue has tools that enable all users to visualize the data in the catalogue without leaving the catalogue – no additional software needed. Have a look at our walk-through of how to make a chart in the catalogue. Get automatic notifications when datasets are updated. You can choose to get notifications for individual datasets, an organization’s datasets or the full catalogue. You don’t have to provide and personal information – just subscribe to our feeds using any feed reader you like using the corresponding notification web addresses. Copy those addresses and paste them into your reader. Your feed reader will let you know when the catalogue has been updated. The catalogue provides open data in several file formats (e.g., spreadsheets, geospatial data, etc). Learn about each format and how you can access and use the data each file contains. A file that has a list of items and values separated by commas without formatting (e.g. colours, italics, etc.) or extra visual features. This format provides just the data that you would display in a table. XLSX (Excel) files may be converted to CSV so they can be opened in a text editor. How to access the data: Open with any spreadsheet software application (e.g., Open Office Calc, Microsoft Excel) or text editor. Note: This format is considered machine-readable, it can be easily processed and used by a computer. Files that have visual formatting (e.g. bolded headers and colour-coded rows) can be hard for machines to understand, these elements make a file more human-readable and less machine-readable. A file that provides information without formatted text or extra visual features that may not follow a pattern of separated values like a CSV. How to access the data: Open with any word processor or text editor available on your device (e.g., Microsoft Word, Notepad). A spreadsheet file that may also include charts, graphs, and formatting. How to access the data: Open with a spreadsheet software application that supports this format (e.g., Open Office Calc, Microsoft Excel). Data can be converted to a CSV for a non-proprietary format of the same data without formatted text or extra visual features. A shapefile provides geographic information that can be used to create a map or perform geospatial analysis based on location, points/lines and other data about the shape and features of the area. It includes required files (.shp, .shx, .dbt) and might include corresponding files (e.g., .prj). How to access the data: Open with a geographic information system (GIS) software program (e.g., QGIS). A package of files and folders. The package can contain any number of different file types. How to access the data: Open with an unzipping software application (e.g., WinZIP, 7Zip). Note: If a ZIP file contains .shp, .shx, and .dbt file types, it is an ArcGIS ZIP: a package of shapefiles which provide information to create maps or perform geospatial analysis that can be opened with ArcGIS (a geographic information system software program). A file that provides information related to a geographic area (e.g., phone number, address, average rainfall, number of owl sightings in 2011 etc.) and its geospatial location (i.e., points/lines). How to access the data: Open using a GIS software application to create a map or do geospatial analysis. It can also be opened with a text editor to view raw information. Note: This format is machine-readable, and it can be easily processed and used by a computer. Human-readable data (including visual formatting) is easy for users to read and understand. A text-based format for sharing data in a machine-readable way that can store data with more unconventional structures such as complex lists. How to access the data: Open with any text editor (e.g., Notepad) or access through a browser. Note: This format is machine-readable, and it can be easily processed and used by a computer. Human-readable data (including visual formatting) is easy for users to read and understand. A text-based format to store and organize data in a machine-readable way that can store data with more unconventional structures (not just data organized in tables). How to access the data: Open with any text editor (e.g., Notepad). Note: This format is machine-readable, and it can be easily processed and used by a computer. Human-readable data (including visual formatting) is easy for users to read and understand. A file that provides information related to an area (e.g., phone number, address, average rainfall, number of owl sightings in 2011 etc.) and its geospatial location (i.e., points/lines). How to access the data: Open with a geospatial software application that supports the KML format (e.g., Google Earth). Note: This format is machine-readable, and it can be easily processed and used by a computer. Human-readable data (including visual formatting) is easy for users to read and understand. This format contains files with data from tables used for statistical analysis and data visualization of Statistics Canada census data. How to access the data: Open with the Beyond 20/20 application. A database which links and combines data from different files or applications (including HTML, XML, Excel, etc.). The database file can be converted to a CSV/TXT to make the data machine-readable, but human-readable formatting will be lost. How to access the data: Open with Microsoft Office Access (a database management system used to develop application software). A file that keeps the original layout and

This data is a mosaic of CTX DEM and ORI’s covering the ExoMars rover landing site in Oxia Planum. This data is a basemap for Oxia Planum and will act as a georeferencing base layer for future High resolution datasets of the rover landing site.ContentsThis data set contains 4 directories:03_a Sets of elevation contours at 100 m and 25 m spacing made from the DEM and smoothed for use in map publications.03_b Mosaic of orthorectified CTX images that accompany the DEM. These data are provided in an equirectangular projection centered at 335.45°E 03_c Hillshade model of the CTX DEM mosaic. These data are provided to help assess the variability and quality of the DEM. These data are provided in an equirectangular projection centered at 335.45°E03_d CTX DEM mosaic. These data are provided in an equirectangular projection centered at 335.45°EGuide to individual files03_a_CTX_DEM_contoursNaming convention: CTX_OXIA_DEM = data from which the contours where created, _cont = contour data, _m = vertical separation of the contours (25 or 100.)File name (example) Description CTX_OXIA_DEM_cont_100m.cpg CTX_OXIA_DEM_cont_100m.dbf CTX_OXIA_DEM_cont_100m.prj Projection information CTX_OXIA_DEM_cont_100m.sbx CTX_OXIA_DEM_cont_100m.shp <- Shape file data Open this data in GiS with the other supporting files in the same directoryCTX_OXIA_DEM_cont_100m.shp.xml Geoprocessing history CTX_OXIA_DEM_cont_100m.shx 03_b_CTX_ORINaming convention: CTX = Instrument, OXIA = Location, ORI = Orthorectified image, 6m = pixel sizeFile name Description CTX_OXIA_ORI_6m.tfw World file <- Open this data in GiS with the other supporting files in the same directoryCTX_OXIA_ORI_6m.tif Image data CTX_OXIA_ORI_6m.tif.aux.xml Auxiliary symbology statistics CTX_OXIA_ORI_6m.tif.ovr Image overviews CTX_OXIA_ORI_6m.tif.xml Geoprocessing history These data are provided with the following projection: Equirectangular_Mars_Oxia_Planum, Projections = Equidistant_Cylindrical, Datum = D_Mars_2000 Spheroid, Central meridian = 335.4503_c_CTX_DEM_hsNaming convention: CTX = Instrument, OXIA = Location, DEM = Digital Elevation Model, 20m = Pixel Size, _hs = hill shade model (sun potion 315°, azimuth 45°)File name Description CTX_OXIA_DEM_20m_hs.tfw World file <- Open this data in GiS with the other supporting files in the same directoryCTX_OXIA_DEM_20m_hs.tif Image data CTX_OXIA_DEM_20m_hs.tif.aux.xml Auxiliary symbology statistics CTX_OXIA_DEM_20m_hs.ovr Image overviews CTX_OXIA_ DEM_20m_hs.tif.xml Geoprocessing history 03_d_CTX_DEMNaming convention: CTX = Instrument, OXIA = Location, DEM = Digital Elevation Model, 20m = Pixel SizeFile name Description CTX_OXIA_DEM_20m.tfw World file <- Open this data in GiS with the other supporting files in the same directoryCTX_OXIA_DEM_20m.tif Image data CTX_OXIA_DEM_20m.tif.aux.xml Auxiliary symbology statistics CTX_OXIA_DEM_20m.ovr Image overviews These data are provided with the following projection: Equirectangular_Mars_Oxia_Planum, Projections = Equidistant_Cylindrical, Datum = D_Mars_2000 Spheroid, Central meridian = 335.45Digital elevation models Digital elevation models (DEMs) were produced from CTX stereo images using the USGS Integrated Software for Imagers and Spectrometers (ISIS) software and the BAE photogrammetric package SOCET SET according to the method of Kirk et al. (2008). We selected 6 CTX image pairs to maximise coverage of the canyon. Tie points were automatically populated in SOCET SET between each image pair. In a departure from previous methods, we ran bundle adjustments on adjacent stereo pairs, removing erroneous tie points until the remaining points had an RMS pixel matching error of ≤ 0.6 pixels. This approach resulted in improved coregistration between stereo pairs, and minimal topographic artefacts across stereo pair boundaries. Each resultant DEM was tied vertically to Mars Orbital Laser Altimeter (MOLA; Zuber et al., 1992) topography and exported with a horizontal post spacing of 20 m/pixel. We then exported orthorectified images from SOCET SET at a resolution of 6 m/pixel. The orthorectified images (ORI) and DEMs were then post-processed in ISIS, mosaicked in the software ENvironment for Visualising Images (ENVI), provided by Harris Geospatial, before manual georeferencing in ArcGIS. Finally, the georeferenced image mosaic was blended in Adobe Photoshop to remove seamlines using the Avenza Geographic Imager extension, which retains geospatial information in the blended product.The output from SocetSet® are 18 – 20 m/pix DEM resolving topography of ~50 – 60 m features and 12 orthorectified CTX images at 6 m/pix. The Expected Vertical Precision (EVP) in each CTX DEM can be estimated based on viewing geometry and pixel scale (Randolph L. Kirk et al., 2003, 2008) e.g. EVP = Δp IFOV / (parallax/height). Where: Δp is the RMS stereo matching error in pixel units, assumed to be 0.2 pixels (Cook et al., 1996) and confirmed with matching software for several other planetary image data sets (Howington-Kraus et al., 2002; R. L. Kirk et al., 1999). The pixel matching error is influenced by signal-to-noise ratio, scene contrast and differences in illumination between the images. Pattern noise can also be introduced by the automatic terrain extraction algorithm, especially in areas of low correlation. These can be identified as patches of ‘triangles’ in the hillshade model (e.g., smooth, low contrast slopes and along shadows). IFOV is the instantaneous field of view of the image (pixel size in metres). If the paired images have different IFOV the RMS values is used e.g. IFOV = √(pixel scale image 1 + pixel scale image 2). The parallax/height ratio, calculated from the three-dimensional intersection geometry, reduces to tan(e) for an image with emission angle ‘e’ paired with a nadir image, e.g., parallax/height = tan(e) where e = |emission angle 1 − emission angle 2|.GeoreferencingMars Express High Resolution Stereo Camera (HRSC; Gwinner et al., 2016) MC11- mosaic (Kersten et al., 2018) has been used as the base control mosaic (tile HMC_11W24_co5ps.tif http://hrscteam.dlr.de/HMC30/).. This data is controlled to the Mars Orbital Laser Altimeter (MOLA; Smith et al., 2001) data the most accurate elevation data for Mars.Registration of the CTX DEM mosaic to the HRSC mosaic used manual tie points between the CTX ORI and HRSC mosaic and applying these tie points to the DEM mosaic. Manual tie points were used because automatic methods gave unsatisfactory results. The CTX mosaic data was rectified using the spline transformation. which optimizes for local accuracy but not global accuracy (Esri, 2020). This method provided good results for images with a range of viewing angles and accounts well for local adjustments needed for abrupt elevation changes.Topographic contoursTopographic contours were created at 25 m intervals from a CTX DEM down sampled to 100 m/pix, and contours shorter than 1500 m were removed and the lines smoothed using the PAEK algorithm at a tolerance of 200 m (USGS & MRCTR GIS Lab, 2018).

Shapefiles for Ethiopia's Administrative boundaries: Regions, Zones and Woredas

The "Digital Elevation Model (scale of 1:25,000, 1:50,000 and 1:100,000)" of this center was listed as Class A data in the "Second Meeting of the 2016 Executive Yuan Open Data Committee" and was amended and released by the Ministry of the Interior on July 26, 2016, under the order number 1051306149, "Fee Standards for Land Surveying and Mapping Results Data." Table 2, Attachment 2, to open the data for free download and use. Note: The Digital Elevation Model does not include contour layers.

The center's "Numerical data files of the constructed version of topographic maps (scales are 1/25,000, 1/50,000, and 1/100,000)" were previously reviewed at the 2nd meeting of the 105th Executive Yuan Information Openness Advisory Group is classified as Category A data, and was revised and published in Appendix 2 of Schedule 2 of Article 2 of the Charging Standards for Land Surveying and Mapping Results Data issued by the Ministry of Interior Taiwan Mainland China Order No. 1051306149 on July 26, 2015. The open data is available for free downloading. Note: The numerical data file of the constructed version of the topographic map does not include the contour layer.