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.

QGIS is a Free and Open Source Geographic Information System. This dataset contains all the information to get you started.

This dataset contains both large (A0) printable maps of the Torres Strait broken into six overlapping regions, based on a clear sky, clear water composite Sentinel 2 composite imagery and the imagery used to create these maps. These maps show satellite imagery of the region, overlaid with reef and island boundaries and names. Not all features are named, just the more prominent features. This also includes a vector map of Ashmore Reef and Boot Reef in Coral Sea as these were used in the same discussions that these maps were developed for. The map of Ashmore Reef includes the atoll platform, reef boundaries and depth polygons for 5 m and 10 m.

This dataset contains all working files used in the development of these maps. This includes all a copy of all the source datasets and all derived satellite image tiles and QGIS files used to create the maps. This includes cloud free Sentinel 2 composite imagery of the Torres Strait region with alpha blended edges to allow the creation of a smooth high resolution basemap of the region.

The base imagery is similar to the older base imagery dataset: Torres Strait clear sky, clear water Landsat 5 satellite composite (NERP TE 13.1 eAtlas, AIMS, source: NASA).

Most of the imagery in the composite imagery from 2017 - 2021.


Method:
The Sentinel 2 basemap was produced by processing imagery from the World_AIMS_Marine-satellite-imagery dataset (01-data/World_AIMS_Marine-satellite-imagery in the data download) for the Torres Strait region. The TrueColour imagery for the scenes covering the mapped area were downloaded. Both the reference 1 imagery (R1) and reference 2 imagery (R2) was copied for processing. R1 imagery contains the lowest noise, most cloud free imagery, while R2 contains the next best set of imagery. Both R1 and R2 are typically composite images from multiple dates.

The R2 images were selectively blended using manually created masks with the R1 images. This was done to get the best combination of both images and typically resulted in a reduction in some of the cloud artefacts in the R1 images. The mask creation and previewing of the blending was performed in Photoshop. The created masks were saved in 01-data/R2-R1-masks. To help with the blending of neighbouring images a feathered alpha channel was added to the imagery. The processing of the merging (using the masks) and the creation of the feathered borders on the images was performed using a Python script (src/local/03-merge-R2-R1-images.py) using the Pillow library and GDAL. The neighbouring image blending mask was created by applying a blurring of the original hard image mask. This allowed neighbouring image tiles to merge together.

The imagery and reference datasets (reef boundaries, EEZ) were loaded into QGIS for the creation of the printable maps.

To optimise the matching of the resulting map slight brightness adjustments were applied to each scene tile to match its neighbours. This was done in the setup of each image in QGIS. This adjustment was imperfect as each tile was made from a different combinations of days (to remove clouds) resulting in each scene having a different tonal gradients across the scene then its neighbours. Additionally Sentinel 2 has slight stripes (at 13 degrees off the vertical) due to the swath of each sensor having a slight sensitivity difference. This effect was uncorrected in this imagery.


Single merged composite GeoTiff:
The image tiles with alpha blended edges work well in QGIS, but not in ArcGIS Pro. To allow this imagery to be used across tools that don't support the alpha blending we merged and flattened the tiles into a single large GeoTiff with no alpha channel. This was done by rendering the map created in QGIS into a single large image. This was done in multiple steps to make the process manageable.

The rendered map was cut into twenty 1 x 1 degree georeferenced PNG images using the Atlas feature of QGIS. This process baked in the alpha blending across neighbouring Sentinel 2 scenes. The PNG images were then merged back into a large GeoTiff image using GDAL (via QGIS), removing the alpha channel. The brightness of the image was adjusted so that the darkest pixels in the image were 1, saving the value 0 for nodata masking and the boundary was clipped, using a polygon boundary, to trim off the outer feathering. The image was then optimised for performance by using internal tiling and adding overviews. A full breakdown of these steps is provided in the README.md in the 'Browse and download all data files' link.

The merged final image is available in export\TS_AIMS_Torres Strait-Sentinel-2_Composite.tif.


Source datasets:
Complete Great Barrier Reef (GBR) Island and Reef Feature boundaries including Torres Strait Version 1b (NESP TWQ 3.13, AIMS, TSRA, GBRMPA), https://eatlas.org.au/data/uuid/d2396b2c-68d4-4f4b-aab0-52f7bc4a81f5

Geoscience Australia (2014b), Seas and Submerged Lands Act 1973 - Australian Maritime Boundaries 2014a - Geodatabase [Dataset]. Canberra, Australia: Author. https://creativecommons.org/licenses/by/4.0/ [license]. Sourced on 12 July 2017, https://dx.doi.org/10.4225/25/5539DFE87D895

Basemap/AU_GA_AMB_2014a/Exclusive_Economic_Zone_AMB2014a_Limit.shp
The original data was obtained from GA (Geoscience Australia, 2014a). The Geodatabase was loaded in ArcMap. The Exclusive_Economic_Zone_AMB2014a_Limit layer was loaded and exported as a shapefile. Since this file was small no clipping was applied to the data.

Geoscience Australia (2014a), Treaties - Australian Maritime Boundaries (AMB) 2014a [Dataset]. Canberra, Australia: Author. https://creativecommons.org/licenses/by/4.0/ [license]. Sourced on 12 July 2017, http://dx.doi.org/10.4225/25/5539E01878302
Basemap/AU_GA_Treaties-AMB_2014a/Papua_New_Guinea_TSPZ_AMB2014a_Limit.shp
The original data was obtained from GA (Geoscience Australia, 2014b). The Geodatabase was loaded in ArcMap. The Papua_New_Guinea_TSPZ_AMB2014a_Limit layer was loaded and exported as a shapefile. Since this file was small no clipping was applied to the data.

AIMS Coral Sea Features (2022) - DRAFT
This is a draft version of this dataset. The region for Ashmore and Boot reef was checked. The attributes in these datasets haven't been cleaned up. Note these files should not be considered finalised and are only suitable for maps around Ashmore Reef. Please source an updated version of this dataset for any other purpose.
CS_AIMS_Coral-Sea-Features/CS_Names/Names.shp
CS_AIMS_Coral-Sea-Features/CS_Platform_adj/CS_Platform.shp
CS_AIMS_Coral-Sea-Features/CS_Reef_Boundaries_adj/CS_Reef_Boundaries.shp
CS_AIMS_Coral-Sea-Features/CS_Depth/CS_AIMS_Coral-Sea-Features_Img_S2_R1_Depth5m_Coral-Sea.shp
CS_AIMS_Coral-Sea-Features/CS_Depth/CS_AIMS_Coral-Sea-Features_Img_S2_R1_Depth10m_Coral-Sea.shp

Murray Island 20 Sept 2011 15cm SISP aerial imagery, Queensland Spatial Imagery Services Program, Department of Resources, Queensland
This is the high resolution imagery used to create the map of Mer.

World_AIMS_Marine-satellite-imagery
The base image composites used in this dataset were based on an early version of Lawrey, E., Hammerton, M. (2024). Marine satellite imagery test collections (AIMS) [Data set]. eAtlas. https://doi.org/10.26274/zq26-a956. A snapshot of the code at the time this dataset was developed is made available in the 01-data/World_AIMS_Marine-satellite-imagery folder of the download of this dataset.


Data Location:
This dataset is filed in the eAtlas enduring data repository at: data\custodian\2020-2029-AIMS\TS_AIMS_Torres-Strait-Sentinel-2-regional-maps. On the eAtlas server it is stored at eAtlas GeoServer\data\2020-2029-AIMS.


Change Log:
2025-05-12: Eric Lawrey
Added Torres-Strait-Region-Map-Masig-Ugar-Erub-45k-A0 and Torres-Strait-Eastern-Region-Map-Landscape-A0. These maps have a brighten satellite imagery to allow easier reading of writing on the maps. They also include markers for geo-referencing the maps for digitisation.

2025-02-04: Eric Lawrey
Fixed up the reference to the World_AIMS_Marine-satellite-imagery dataset, clarifying where the source that was used in this dataset. Added ORCID and RORs to the record.

2023-11-22: Eric Lawrey
Added the data and maps for close up of Mer.
- 01-data/TS_DNRM_Mer-aerial-imagery/
- preview/Torres-Strait-Mer-Map-Landscape-A0.jpeg
- exports/Torres-Strait-Mer-Map-Landscape-A0.pdf
Updated 02-Torres-Strait-regional-maps.qgz to include the layout for the new map.

2023-03-02: Eric Lawrey
Created a merged version of the satellite imagery, with no alpha blending so that it can be used in ArcGIS Pro. It is now a single large GeoTiff image. The Google Earth Engine source code for the World_AIMS_Marine-satellite-imagery was included to improve the reproducibility and provenance of the dataset, along with a calculation of the distribution of image dates that went into the final composite image. A WMS service for the imagery was also setup and linked to from the metadata. A cross reference to the older Torres Strait clear sky clear water Landsat composite imagery was also added to the record.

The Digital Geologic-GIS Map of Yosemite National Park and Vicinity, California is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (yose_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (yose_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (yose_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (yose_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (yose_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (yose_geology_metadata_faq.pdf). Please read the yose_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey and California Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (yose_geology_metadata.txt or yose_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:62,500 and United States National Map Accuracy Standards features are within (horizontally) 31.8 meters or 104.2 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

OpenStreetMap (OSM) is a free, editable map & spatial database of the whole world. This dataset is an extract of OpenStreetMap data for French Polynesia in a GIS-friendly format.

The OSM data has been split into separate layers based on themes (buildings, roads, points of interest, etc), and it comes bundled with a QGIS project and styles, to help you get started with using the data in your maps. This OSM product will be updated weekly.

The goal is to increase awareness among Pacific GIS users of the richness of OpenStreetMap data in Pacific countries, as well as the gaps, so that they can take advantage of this free resource, become interested in contributing to OSM, and perhaps join the global OSM community.

OpenStreetMap data is open data, with a very permissive licence. You can download it and use it for any purpose you like, as long as you credit OpenStreetMap and its contributors. You don't have to pay anyone, or ask anyone's permission. When you download and use the data, you're granted permission to do that under the Open Database Licence (ODbL). The only conditions are that you Attribute, Share-Alike, and Keep open.

The required credit is “© OpenStreetMap contributors”. If you make a map, you should display this credit somewhere. If you provide the data to someone else, you should make sure the license accompanies the data

Here is an image of the global municipal tax (founcier bati + habitation). Average tax per asset Nancy 2014

To do it again you will need: — QGIS software (Free: https://www.qgis.org/fr/site/forusers/download.html), — a qgs file of your department (http://www.actualitix.com/shapefiles-des-departements-de-france.html) — an export of tax rates (https://www.data.gouv.fr/fr/datasets/impots-locaux/ > Municipal and intercommunal data > Your Department > Local Direct Tax Data 2014 (XLS format)) — data (most days of INSEE here 2012 http://www.insee.fr/fr/themes/detail.asp?reg_id=99&ref_id=base-cc-emploi-pop-active-2012)

Operating Mode: — process your data in your favorite spreadsheet (Excel or OpenOffice Calc) by integrating impot data, and INSEE to pull out the numbers that seem revealing to you — Install QGIS — Open the.qgs of your department

Add columns — Right click property on the main layer — Go to the field menu (on the left) — Add (via pencil) the desired columns (here average housing tax per asset, average property tax per asset, and the sum of both) — These are reals of precision 2, and length 6 — Register

Insert data: — Right-click on the “Open attribute table” layer — Select all — Copy — Paste in excel (or openOffice calcs) — Put the ad hoc formulas in excel (SOMME.SI.ENS to recover the rate) — Save the desired tab in CSV DOS with the new values — In QGIS > Menu > Layer > Add a delimited layer of text — Import the CSV

Present the data: — To simplify I advise you to make a layer by rate, and layers sums. So rots you in three clicks out the image of the desired rate — For each layer (or rate) — Right click properties on the csv layer — Labels to add city name and desired rate — Style for fct coloring of a csv field

Print the data in pdf: — To print, you need to define a print template — In the menu choose new printing dialer — choose the format (a department in A0 is rather readable) — Add vas legend, scale, and other — Print and here...

NB: this method creates aberrations: — in the case where the INSEE does not have a number or numbers that have moved a lot since — it is assumed that only assets pay taxes (which is more fair, but not 100 %)

With this add in it is possible to create map templates from GIS files in KML format, and create choropleths with them. Providing you have access to KML format map boundary files, it is possible to create your own quick and easy choropleth maps in Excel. The KML format files can be converted from 'shape' files. Many shape files are available to download for free from the web, including from Ordnance Survey and the London Datastore. Standard mapping packages such as QGIS (free to download) and ArcGIS can convert the files to KML format. A sample of a KML file (London wards) can be downloaded from this page, so that users can easily test the tool out. Macros must be enabled for the tool to function. When creating the map using the Excel tool, the 'unique ID' should normally be the area code, the 'Name' should be the area name and then if required and there is additional data in the KML file, further 'data' fields can be added. These columns will appear below and to the right of the map. If not, data can be added later on next to the codes and names. In the add-in version of the tool the final control, 'Scale (% window)' should not normally be changed. With the default value 0.5, the height of the map is set to be half the total size of the user's Excel window. To run a choropleth, select the menu option 'Run Choropleth' to get this form. To specify the colour ramp for the choropleth, the user needs to enter the number of boxes into which the range is to be divided, and the colours for the high and low ends of the range, which is done by selecting coloured option boxes as appropriate. If wished, hit the 'Swap' button to change which colours are for the different ends of the range. Then hit the 'Choropleth' button. The default options for the colours of the ends of the choropleth colour range are saved in the add in, but different values can be selected but setting up a column range of up to twelve cells, anywhere in Excel, filled with the option colours wanted. Then use the 'Colour range' control to select this range, and hit apply, having selected high or low values as wished. The button 'Copy' sets up a sheet 'ColourRamp' in the active workbook with the default colours, which can just be extended or deleted with just a few cells, so saving the user time. The add-in was developed entirely within the Excel VBA IDE by Tim Lund. He is kindly distributing the tool for free on the Datastore but suggests that users who find the tool useful make a donation to the Shelter charity. It is not intended to keep the actively maintained, but if any users or developers would like to add more features, email the author. Acknowledgments Calculation of Excel freeform shapes from latitudes and longitudes is done using calculations from the Ordnance Survey.

Here is an image of the overall municipal tax rate (foncier bati + habitation, for municipalities and inter-municipalities). http://physaphae.noip.me/Img/2015_Rate_54" alt="Local tax rate 54 of 2015" title="Local tax rate 54 of 2015">

Given that it is at the departmental mesh, it is not useful to include the departmental rate, and national... That would not be part of the comparison.

To do it again yourself you will need: - QQGIS software (Free: https://www.qgis.org/en/site/forusers/download.html), - a qgs file of your department (http://www.actualitix.com/shapefiles-des-departements-de-france.html) - an export of tax rates (https://www.data.gouv.fr/en/datasets/local taxes/)

Procedure: Install QGIS Open your department's .qgs

Add columns - Right click property on the main layer - Go to the fields menu (on the left) - Add (via the pencil) the desired columns (here municipal tax rate, intercommunal built land and housing) - These are reals of a precision 2, and a length 4 - Register

Insert data: - Right click on the layer "Open attribute table" - Select all - Copy - Paste into excel (or openOffice calcs) - Put the ad hoc formulas in excel (SUM.SI.ENS to recover the rate) - Save the desired tab in CSV DOS with the new values - In QGIS > Menu > Layer > Add a delimited text layer - Import the CSV

Present the data: - To simplify I advise you to make one layer per rate, and layers are. Thus rots you in three clicks take out the image of the desired rate - For each layer (or rate) - Right click properties on the csv layer - Labels to add the name of the city and the desired rate - Style for coloring in fct of a csv field

Print the data in pdf: - To print, you need to define a print template - In the menu choose new print dialler - choose the format (a department in A0 is rather readable) - Add vas legend, ladder, and other - Print and voila...

The base map consists of the city’s basic geographical information and has the highest level of detail used in the urban development area as a whole. The map is also used outside the city’s activities in areas such as planning and planning. By providing the base map as open data, the city opens up for wider use and the possibility of new innovative applications.ContentBasic map includes:

BuildingsCommunicationMarket useAddressesRegistermap (property limits and rights, etc.) The information in the register map has no legal effect and may be poorly accurate. In case of exact information requirements, verification should be carried out on the basis of decision documents.AtkomstBaskartan is downloaded via http://kartor.helsingborg.se/oppnageodata/baskarta.phpFormat and object modelThe map is delivered as a zip file containing one GeoJSON file per object type. Coordinate system is SWEREF99 13 30. The files are a direct export from the Helsingborg City Planning Administration’s database and are named as follows:

Object types sometimes have attributes that come from domains. Then a value can be represented in a digit instead of saving a string over and over again. During export we have exploded the domains with the suffix “_resolved” so that they can still be seen in plain text.“PURPOSE”:10, “PURPOSE_resolved”:“Småhus — detached”

The tables in the theme “Registration map” have a specific title in two letters. Exempel:Registerkarta AQIn order to understand the contents of those tables, it may help to examine the attribute “dep” where a more readable description is given. Complete documentation on the registry map is currently missing. However, Lantmäteriet provides similar products where table names exist. Please see exempel:https://www.lantmateriet.se/globalassets/kartor-oc...MetadataEn mapping to translate table names into English can be found here. Structure:[{“Geo object class”:“Facility, point”, “Geo object class English”:“MAPCONSTRUCTIONP”},... ]

Refresh rate The zip file is updated weekly, the night between Saturday and Sunday. In the zip file there is a folder metadata. In it is readme.txt which contains a date stamp that tells you when the actual export was made.

FAQ base map

How can I look at the map without any specific program? Download the zip file and unpack it. Search “GeoJSON viewer” in your browser. For example, http://www.mapshaper.org/. Drag in and drop a GeoJSON file to view it.

Can I use the base map in my CAD system?Plugin/app is available to Autodesk. https://apps.autodesk.com/ACD/en/Detail/Index?id=5...

Can I use the base map in my GIS? QGIS has good support for GeoJSON. ArcMap requires Data Interopability add-on. FME can read and convert.

Can I convert GeoJSON to shape? Several free services are available to convert to shape. Among others, http://www.mapshaper.org/.

Location of areas of cuttings of hardwood or softwood on the Department of Landes between 2012 and 2014 in order to facilitate the organisation of cutting controls on the department. The controls focus on softwood cuttings, the owners of which are obliged, within 5 years, to restore the stands. The creation of this data is part of a request from the Ministry of Agriculture, Agri-Food and Forestry, to develop a method for detecting clean cuts using free software (qgis) and free satellite data.

Location of areas of cuttings of deciduous or softwood on the department of the Pyrénées Atlantiques between 2010 and 2011 in order to facilitate the organisation of the controls of the cuts on the department. The controls focus on softwood cuttings, the owners of which are obliged, within 5 years, to restore the stands. The creation of this data is part of a request from the Ministry of Agriculture, Agri-Food and Forestry, to develop a method for detecting clean cuts using free software (qgis) and free satellite data.

The High Resolution Digital Elevation Model (HRDEM) product is derived from airborne LiDAR data (mainly in the south) and satellite images in the north. The complete coverage of the Canadian territory is gradually being established. It includes a Digital Terrain Model (DTM), a Digital Surface Model (DSM) and other derived data. For DTM datasets, derived data available are slope, aspect, shaded relief, color relief and color shaded relief maps and for DSM datasets, derived data available are shaded relief, color relief and color shaded relief maps. The productive forest line is used to separate the northern and the southern parts of the country. This line is approximate and may change based on requirements. In the southern part of the country (south of the productive forest line), DTM and DSM datasets are generated from airborne LiDAR data. They are offered at a 1 m or 2 m resolution and projected to the UTM NAD83 (CSRS) coordinate system and the corresponding zones. The datasets at a 1 m resolution cover an area of 10 km x 10 km while datasets at a 2 m resolution cover an area of 20 km by 20 km. In the northern part of the country (north of the productive forest line), due to the low density of vegetation and infrastructure, only DSM datasets are generally generated. Most of these datasets have optical digital images as their source data. They are generated at a 2 m resolution using the Polar Stereographic North coordinate system referenced to WGS84 horizontal datum or UTM NAD83 (CSRS) coordinate system. Each dataset covers an area of 50 km by 50 km. For some locations in the north, DSM and DTM datasets can also be generated from airborne LiDAR data. In this case, these products will be generated with the same specifications as those generated from airborne LiDAR in the southern part of the country. The HRDEM product is referenced to the Canadian Geodetic Vertical Datum of 2013 (CGVD2013), which is now the reference standard for heights across Canada. Source data for HRDEM datasets is acquired through multiple projects with different partners. Since data is being acquired by project, there is no integration or edgematching done between projects. The tiles are aligned within each project. The product High Resolution Digital Elevation Model (HRDEM) is part of the CanElevation Series created in support to the National Elevation Data Strategy implemented by NRCan. Collaboration is a key factor to the success of the National Elevation Data Strategy. Refer to the “Supporting Document” section to access the list of the different partners including links to their respective data.

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.

A dataset describing exposed bedrock and surficial geology of Antarctica constructed by the GeoMAP Action Group of SCAR (The Scientific Committee on Antarctic Research) and GNS Science, New Zealand. Legacy geological map data have been captured into a geographic information system (GIS), refining its spatial reliability, harmonising classification, then improving representation of glacial sequences and geomorphology. A total 99,080 polygons have been unified for depicting geology at 1:250,000 scale, but locally there are some areas with higher spatial precision. Geological definition in GeoMAP v.2022-08 is founded on a mixed chronostratigraphic- and lithostratigraphic-based classification. Description of rock and moraine polygons employs international GeoSciML data protocols to provide attribute-rich and queriable data; including bibliographic links to 589 source maps and scientific literature. Data are provided under CC-BY License as zipped ArcGIS geodatabase, QGIS geopackage or GoogleEarth kmz files. GeoMAP is the first detailed geological dataset covering all of Antarctica. GeoMAP depicts 'known geology' of rock exposures rather than 'interpreted' sub-ice features and is suitable for continent-wide perspectives and cross-discipline interrogation.

The tile server displays the data and technical specifications aimed at viewing, through any appropriately configured GIS software, the orthophotos published by the Local Information System (SIT) of the Municipality of Bologna.Here you can download the individual tiles (2017)Here you can download the individual tiles (2020)Here you can download the individual tiles (2020)Here you can download the individual tiles (2021)Here you can download the individual tiles (2022)Here you can download the individual tiles (2023)Images are displayed in the WGS 84 Pseudo-Mercator coordinate system (EPSG 3857).The service allows the display of raster images in the form of tiles, previously created and published via a webserver. The technical instructions for viewing can be found in the attached files at the bottom of the page.The images are thus presented very quickly to the user who accesses them. In the manual you will find all the useful references and by way of example, the steps to view the server tile with the QGIS software, a free GIS application.

This guide helps iwi, hapū and whānau set up a simple offline GIS on your computer. The dataset and mapping layers cover all mainland areas of Aotearoa. You can install free tools, download the Matawhenua starter package, open the supplied QGIS project, add LINZ basemaps, and create local copies for your own rohe.This toolset lets you maintain complete data sovereignty. All data is stored on your computer and no one else can access it. The software and data are free and ready to use. There are no licence fees or ongoing costs.You keep control of your kōrero and decide what to share, when, and with whom. No cloud storage or accounts are required. The datasets are current as at August 2025 and do not update automatically.

OpenStreetMap (OSM) is a free, editable map & spatial database of the whole world. This dataset is an extract of OpenStreetMap data for Papua New Guinea in a GIS-friendly format.

The OSM data has been split into separate layers based on themes (buildings, roads, points of interest, etc), and it comes bundled with a QGIS project and styles, to help you get started with using the data in your maps. This OSM product will be updated weekly.

The goal is to increase awareness among Pacific GIS users of the richness of OpenStreetMap data in Pacific countries, as well as the gaps, so that they can take advantage of this free resource, become interested in contributing to OSM, and perhaps join the global OSM community.

This layer shows the countries of Africa. You can click on the map to get info on each country, including its name and flag, as well as links to detailed information in The World Factbook and UN Human Development Reports.The Africa Countries layer was created by joining country population data from The World Factbook to the World Countries (Generalized) layer, using ArcGIS Online analysis tools. The popup for the map uses Arcade expressions to reference other online resources based on the country code for the selected country.The Flags of countries are provided by reference to Flagpedia, which provides flags of countries of the world and the U.S. states for display and download.

This file contains Indus river shapefile made by referring Google hybrid satellite data in Qgis 3.28.1.

SSURGO PortalThe newest version of SSURGO Portal with Soil Data Viewer is available via the Quick Start Guide. Install Python to C:\Program Files. This is a different version than what ArcGIS Pro uses.If you need data for multiple states, we also offer a prebuilt large database with all SSURGO for the entire United States and all Islands. The prebuilt saves you time but it’s large and takes a while to download.You can also use the prebuilt gNATSGO GeoPackage database in SSURGO Portal – Soil Data Viewer. Read the ReadMe.txt in the folder. More about gNATSGO here. You can also import STATSGO2 data into SSURGO Portal and create a database to use in Soil Data Viewer – Available for download via the Soils Box folder. SSURGO Portal NotesThis 10 minute video covers it all, other than installation of SSURGO Portal and the GIS tool. Installation is typically smooth and easy.There is also a user guide on the SSURGO Portal website that can be very helpful. It has info about using the data in ArcGIS Pro or QGIS. SQLite SSURGO database be opened and queried with DB Browser. It’s essentially free Microsoft Access.Guidance about setting up DB Browser to easily open SQLite databases is available in section 4 of this Installation Guide.Workflow if you need to make your own databaseInstall SSURGO PortalInstall SSURGO Downloader GIS tool (Refer to the Installation and User Guide for assistance)There is one for QGIS and one for ArcGIS Pro. They both do the same thing. Quickly download California SSURGO data with toolEnter two digit state symbol followed by asterisk in “Search by Areasymbol” to download all data for state.For example, enter CA* to batch download all data for CaliforniaOpen SSURGO Portal and create a new SQLite SSURGO Template database (Refer to the User Guide for assistance)Import SSURGO data you downloaded into databaseYou can import SSURGO data from many states at once, building a database that spans many statesAfter SSURGO data is done importing, click on Soil Data Viewer tab and run ratingsThese are the exact same ratings as Web Soil SurveyA new table is added to your database for each ratingYou can search for ratings by keywordIf desired, open database in GIS and make a map (Refer to the User Guide for assistance)Workflow if you need use large prebuilt database (don’t make own database) Install SSURGO PortalIn SSURGO Portal, browse to unzipped prebuilt GeoPackage database with all SSURGOprebuilt large database with all SSURGOgNATSGO GeoPackage databaseIn SSURGO Portal, click on Soil Data Viewer tab and run ratingsThese are the exact same ratings as Web Soil SurveyA new table is added to your database for each ratingYou can search for ratings by keywordIf desired, open database in GIS and make a mapIf you have trouble installing SSURGO Portal. Its usually the connection with Python. Create Desktop short cut that tells SSURGO Portal which Python to useThese were created for Windows 11 Right click anywhere on your desktop and choose New > ShortcutIn the text bar enter your path to the python.exe and your path to the SSURGO Portal.pyz. Notes:Example of format:"C:\Program Files\Python310\python.exe" "C:\SSURGO Portal\SSURGO_Portal-0.3.0.8.pyz"Include quotation marks.Paths may be different on your machine. To avoid typing, you can browse to python.exe in windows explorer, right click and select "Copy as Path and paste results into box. Paste into short location and then do the same for SSURGO Portal.pyz file, but paste to the right of the python.exe path. Click NextName the shortcut anything you want.