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 Bright Earth eAtlas Basemap dataset collection is a satellite-derived global map of the world at a 1:1M scale for most of the world and 1:200k scale for Australia. This map was inspired by Natural Earth II (NEII) and NASA's Blue Marble Next Generation (BMNG) imagery.

Its aim was to provide a basemap similar to NEII but with a higher resolution (~10x).

This basemap is derived from the following datasets: Blue Marble Next Generation 2004-04 (NASA), VMap0 coastline, Coast100k 2004 Australian coastline (GeoScience Australia), SRTM30 Plus v8.0 (UCSD) hillshading, Natural Earth Vector 10m bathymetry and coastline v2.0 (NE), gbr100 hillshading (JCU).

This dataset (World_Bright-Earth-e-Atlas-basemap) contains all the files required to setup the Bright Earth eAtlas basemap in a GeoServer. All the data files are stored in GeoTiffs or shapefiles and so can also be loaded into ArcMap, however no styling has been included for this purpose.

This basemap is small enough (~900 MB) that can be readily used locally or deployed to a GeoServer.

Base map aesthetics (added 28 Jan 2025)

The Bright Earth e-Atlas Basemap is a high-resolution representation of the Earth's surface, designed to depict global geography with clarity, natural aesthetics with bright and soft color tones that enhance data overlays without overwhelming the viewer. The land areas are based on NASA's Blue Marble imagery, with modifications to lighten the tone and apply noise reduction filtering to soften the overall coloring. The original Blue Marble imagery was based on composite satellite imagery resulting in a visually appealing and clean map that highlights natural features while maintaining clarity and readability. Hillshading has been applied across the landmasses to enhance detail and texture, bringing out the relief of mountainous regions, plateaus, and other landforms.

The oceans feature three distinct depth bands to illustrate shallow continental areas, deeper open ocean zones, and the very deep trenches and basins. The colors transition from light blue in shallow areas to darker shades in deeper regions, giving a clear sense of bathymetric variation. Hillshading has also been applied to the oceans to highlight finer structures on the seafloor, such as ridges, trenches, and other geological features, adding depth and dimensionality to the depiction of underwater topography.

At higher zoom levels prominent cities are shown and the large scale roads are shown for Australia.

Rendered Raster Version (added 28 Jan 2025)

A low resolution version of the dataset is available as a raster file (PNG, JPG and GeoTiff) at ~2 km and 4 km resolutions. These rasters are useful for applications where GeoServer is not available to render the data dynamically. While the rasters are large they represent a small fraction of the full detail of the dataset. The rastered version was produced using the layout manager in QGIS to render maps of the whole world, pulling the imagery from the eAtlas GeoServer. This imagery from converted to the various formats using GDAL. More detail is provided in 'Rendered-bright-earth-processing.txt' in the download and browse section.

Change Log 2025-01-28: Added two rendered raster versions of the dataset at 21600x10800 and 10400x5400 pixels in size in PNG, JPG and GeoTiff format. Added

The Mid-Century Map (World Edition) web map provides a customized world basemap symbolized with a unique "Mid-Century" style. It takes its inspiration from the art and advertising of the 1950's with unique fonts. The symbols for cities and capitals have an atomic slant to them. The map data includes highways, major roads, minor roads, railways, water features, cities, parks, landmarks, building footprints, and administrative boundaries.This basemap, included in the ArcGIS Living Atlas of the World, uses the Mid-Century vector tile layer.The vector tile layer in this web map is built using the same data sources used for other Esri Vector Basemaps. For details on data sources contributed by the GIS community, view the map of Community Maps Basemap Contributors. Esri Vector Basemaps are updated monthly.Use this MapThis map is designed to be used as a basemap for overlaying other layers of information or as a stand-alone reference map. You can add layers to this web map and save as your own map. If you like, you can add this web map to a custom basemap gallery for others in your organization to use in creating web maps. If you would like to add this map as a layer in other maps you are creating, you may use the tile layer referenced in this map.

Spatial dataset derived from many different open data repositories and cropped on the Omo-Turkana Basin boundary, used to create a base-map describing the components of Water-Energy-Food nexus in the case study. omo-turkana.gpkg: vector dataset including the following layers, together with the related map style for QGIS Desktop used in the DAFNE Geoportal basemap: basin: Hydrological basin of the Omo-Turkana river (case study boundary) subbasin: Basins of the main tributaries waterbodies: Natural lakes and reservoirs boundaries rivers: River network dams: Existing dams protected_areas: Protected areas aei_pct_cells: Area equipped for irrigation, expressed as percentage of total area. roads: Main roads network cities: Main cities in the riparian countries countries: Administrative borders of riparian countries markers: DAFNE model components location, with existing and planned dams and power plants, irrigation schemes, environmental target areas. zambezi_raster.zip: raster dataset including the following layers: srtm_90m: Digital Elevation Model Global Surface Water: change: Occurrence Change Intensity map provides information on where surface water occurrence increased, decreased or remained the same between 1984-1999 and 2000-2015 extent: Maximum Water Extent shows all the locations ever detected as water over period 1984-2015 occurence: Occurrence shows where surface water occurred between 1984 and 2015 and provides information concerning overall water dynamics. recurrence: Recurrence provides information concerning the inter-annual behaviour of water surfaces and captures the frequency with which water returns from year to year. seasonality: Seasonality map provides information concerning the intra-annual behaviour of water surfaces for a single year (2015) and shows permanent and seasonal water and the number of months water was present. transitions: Transitions map provides information on the change in surface water seasonality between the first and last years (between 1984 and 2015) and captures changes between the three classes of not water, seasonal water and permanent water. Original data sources include: AQUASTAT, the FAO global information system on water resources and agricultural water management; Natural Earth, a public domain map dataset available at different scales; Protected Planet, the most up to date and complete source of data on protected areas and other effective area-based conservation measures, maintained by UNEP-WCMC and IUCN; OpenStreetMap, a collaborative project to create a free editable map of the world; NASA's Shuttle Radar Topography Mission (SRTM) Digital Elevation Database; Global Water Surface, a virtual time machine that maps the location and temporal distribution of water surfaces at the global scale.

AbstractCoastline for Antarctica created from various mapping and remote sensing sources, consisting of the following coast types: 'ice coastline', 'rock coastline', 'grounding line', 'ice shelf and front', 'ice rumple', and 'rock against ice shelf', provided as a surface attribute. Covering all land and ice shelves south of 60°S. Suitable for topographic mapping and analysis. High resolution versions of ADD data are suitable for scales larger than 1:1,000,000. The largest suitable scale is changeable and dependent on the region.Changes in v7.11 include updates to the coastline of Adelaide Island and surrounding islands, the grounding line of Alexander Island and the surrounding region, and the ice shelf front of the Brunt Ice Shelf. In addition, sourcedate and revdate attributes were updated to a consistent YYYY-MM-DD format. To indicate limited date precision for earlier records, sourceprec and revprec attributes were introduced.Data compiled, managed and distributed by the Mapping and Geographic Information Centre and the UK Polar Data Centre, British Antarctic Survey on behalf of the Scientific Committee on Antarctic Research. Further information and useful linksMap projection: WGS84 Antarctic Polar Stereographic, EPSG 3031. Note: by default, opening this layer in the Map Viewer will display the data in Web Mercator. To display this layer in its native projection use an Antarctic basemap. The currency of this dataset is November 2025 and will be reviewed every 6 months. This feature layer will always reflect the most recent version. For more information on, and access to other Antarctic Digital Database (ADD) datasets, refer to the SCAR ADD data catalogue. A related medium resolution dataset is also published via Living Atlas, as well medium and high resolution polygon datasets. For background information on the ADD project, please see the British Antarctic Survey ADD project page. LineageDataset compiled from a variety of Antarctic map and satellite image sources. The dataset was created using ArcGIS and QGIS GIS software programmes and has been checked for basic topography and geometry errors, but does not contain strict topology. Quality varies across the dataset, certain areas where high-resolution source data were available are suitable for large-scale maps, whereas other areas are only suitable for smaller scales. Each line has attributes detailing the source, which can give the user further indications of its suitability for specific uses. Attributes also give information, including surface (e.g. grounding line, ice coastline, ice shelf front) and revision date (revdate), accompanied by revprec - date precision, either day, month, or year. Compiled from sources ranging in time from 1990s-2025 - individual lines contain exact source dates in sourcedate field with the corresponding sourceprec field. CitationGerrish, L., Ireland, L., Fretwell, P., Cooper, P., & Skachkova, A. (2025). High resolution vector polylines of the Antarctic coastline (Version 7.11) [Data set]. NERC EDS UK Polar Data Centre. https://doi.org/10.5285/cc0b73c0-3b53-40fb-ae84-b5dce4ac163a If using for a graphic or if short on space, please cite as 'data from the SCAR Antarctic Digital Database, 2025'

Abstract Coastline for Antarctica created from various mapping and remote sensing sources, provided as polygons with surface values for 'land', 'ice shelf', 'ice tongue', or 'rumple'. Covering all land and ice shelves south of 60°S. Suitable for topographic mapping and analysis. This dataset has been generalised from the high resolution vector polygons. Medium resolution versions of ADD data are suitable for scales smaller than 1:1,000,000, although certain regions will appear more detailed than others due to variable data availability and coastline characteristics.Changes in v7.11 include updates to the coastline of Adelaide Island and surrounding islands, the grounding line of Alexander Island and the surrounding region, and the ice shelf front of the Brunt Ice Shelf.Data compiled, managed and distributed by the Mapping and Geographic Information Centre and the UK Polar Data Centre, British Antarctic Survey on behalf of the Scientific Committee on Antarctic Research. Further information and useful linksMap projection: WGS84 Antarctic Polar Stereographic, EPSG 3031. Note: by default, opening this layer in the Map Viewer will display the data in Web Mercator. To display this layer in its native projection use an Antarctic basemap. The currency of this dataset is November 2024 and will be reviewed every 6 months. This feature layer will always reflect the most recent version. For more information on, and access to other Antarctic Digital Database (ADD) datasets, refer to the SCAR ADD data catalogue. A related high resolution dataset is also published via Living Atlas, as well medium and high resolution line datasets. For background information on the ADD project, please see the British Antarctic Survey ADD project page. LineageDataset compiled from a variety of Antarctic map and satellite image sources. The dataset was created using ArcGIS and QGIS GIS software programmes and has been checked for basic topography and geometry errors, but does not contain strict topology. Quality varies across the dataset, certain areas where high resolution source data were available are suitable for large scale maps, whereas other areas are only suitable for smaller scales. Each polygon contains a surface attribute with either 'land', 'ice shelf', 'ice tongue' or 'rumple'. Details of when and how each line was created can be found in the attributes of the high or medium resolution polyline coastline dataset. Data sources range in time from the 1990s to 2025. This medium resolution version has been generalised from the high resolution version. All polygons <0.1km² not intersecting anything else were deleted and the simplify tool was used in ArcGIS with the retain critical points algorithm and a smoothing tolerance of 50m. Citation Gerrish, L., Ireland, L., Fretwell, P., Cooper, P., & Skachkova, A. (2025). Medium resolution vector polygons of the Antarctic coastline (Version 7.11) [Data set]. NERC EDS UK Polar Data Centre. https://doi.org/10.5285/981b1444-c57e-40f1-b6e9-884b44cad00eIf using for a graphic or if short on space, please cite as 'Data from the SCAR Antarctic Digital Database, 2025'.

Spatial dataset derived from many different open data repositories and cropped on the Zambezi River Basin boundary, used to create a base-map describing the components of Water-Energy-Food nexus in the case study. zambezi.gpkg: vector dataset including the following layers, together with the related map style for QGIS Desktop used in the DAFNE Geoportal basemap: basin: Hydrological basin of the Zambezi river (case study boundary) subbasin: Basins of the main tributaries of the Zambezi River waterbodies: Natural lakes and reservoirs boundaries rivers: River network stations: Streamflow, Water level and Rainfall Gauging stations dams: Existing dams wetlands: Wetlands protected_areas: Protected areas aei_pct_cells: Area equipped for irrigation, expressed as percentage of total area. roads: Main roads network cities: Main cities in the riparian countries countries: Administrative borders of riparian countries markers: DAFNE model components location, with existing and planned dams and power plants, irrigation schemes, environmental target areas. zambezi_raster.zip: raster dataset including the following layers: DEM_1km: Digital Elevation Model Global Surface Water: change: Occurrence Change Intensity map provides information on where surface water occurrence increased, decreased or remained the same between 1984-1999 and 2000-2015 extent: Maximum Water Extent shows all the locations ever detected as water over period 1984-2015 occurence: Occurrence shows where surface water occurred between 1984 and 2015 and provides information concerning overall water dynamics. recurrence: Recurrence provides information concerning the inter-annual behaviour of water surfaces and captures the frequency with which water returns from year to year. seasonality: Seasonality map provides information concerning the intra-annual behaviour of water surfaces for a single year (2015) and shows permanent and seasonal water and the number of months water was present. transitions: Transitions map provides information on the change in surface water seasonality between the first and last years (between 1984 and 2015) and captures changes between the three classes of not water, seasonal water and permanent water. Original data sources includes: AQUASTAT, the FAO global information system on water resources and agricultural water management; Natural Earth, a public domain map dataset available at different scales; Protected Planet, the most up to date and complete source of data on protected areas and other effective area-based conservation measures, maintained by UNEP-WCMC and IUCN; OpenStreetMap, a collaborative project to create a free editable map of the world; ZAMWIS, a management information system for the Zambezi River Basin; NASA's Shuttle Radar Topography Mission (SRTM) Digital Elevation Database; Global Water Surface, a virtual time machine that maps the location and temporal distribution of water surfaces at the global scale.

This dataset contains a set of data related to processed information deriving from fieldwork activities and elaboration of archival information and literature (v. Cat 3, Cat 4, Cat 6 Deliverable D6.2, DMP) collected, accessed, and consulted during the WP1 and WP2 research activities. It constitutes a fundamental part that supports the Land-In-Pro spatial and territorial analysis in WP3, which encompasses activities aimed at informing a webGIS that visualises the transformations the selected context/site has undergone over the years in the pilot site, capturing its former and current conditions and configurations, whilst allowing the definition of indicators for the development of the Land-In-Pro Assessment Tool. The Land-In-Pro Pilot Site Mapping GIS project has been structured to ensure usability for both expert GIS users and non-specialist audiences. The project has been set up by using the open-source mobile application Qfield (v.3.4) during fieldwork, and QGIS (v.3.34 Prizren) during the data processing phase. Set in the Roma40 reference system and Gauss–Boaga cartographic projection (EPSG:3003), it is organised into three main layers (zoning, buildings_mapping, views_mapping) with attribute tables containing information available in both Italian and English languages. The buildings_demolished layer is a support vector layer used only for spatial reference: it provides indicative geometries to georeference demolished buildings. For optimal use of the project, it is recommended to add a base map (e.g., Google Satellite or Bing Maps Satellite Imagery) within QGIS. This provides a clear cartographic background that facilitates the orientation and interpretation of the mapped data. This dataset has been curated by Dr Federica Pompejano and Dr Sara Mauri. It relates to:

• WP2
• Version 1.0; created on October 2, 2023; published on September 30, 2025.
• Federica Pompejano, Principal Investigator, RTD-A, Department Architecture and Design (DAD), Università di Genova (UniGe), federica.pompejano@unige.it (creator and depositor)
• Sara Mauri, Postdoctoral researcher, Department Architecture and Design (DAD), Università di Genova (UniGe), sara.mauri@edu.unige.it (depositor)
• Data originates from the collection of spatial data during fieldwork activities and from the processing of archival sources and literature.
• Keywords: NextGenerationEU, NextGenEu, Ministero dell'Università e della Ricerca, MUR, PNRR, UniGe, DAD, MSCA_0000005, Land-In-Pro, Post-industrial landscape, Industrial heritage, Landscape studies, Architectural conservation, Heritage studies, Fieldwork, Photo survey, Data processing, Architetture, Strutture, Paesaggio. Architecture, Landscape, Structures
• Link: https://landinpro.unige.it/pilotsitemapping

This dataset is part of the Land-In-Pro project, which has received funding from the Ministry of University and Research, General Directorate for Internationalisation and Communication – National Recovery and Resilience Plan (PNRR) - Mission 4 “Education and Research” - Component 2 “From Research to Business” - Investment 1.2 “Funding projects presented by young researchers” and the European Union – Next Generation EU. The content of this database reflects only the authors’ views. The authors, Host Institution, Ministry of University and Research and the European Commission are not responsible for any use that may be made of the information it contains.

This dataset contains a QGIS project (.qgz) along with supporting files including PDFs (.pdf), images (.jpg), text (.txt), XML metadata (.xml), and QGIS packages (.qpkg).

The metadata are contained in a markdown README file (.txt). Metadata is compiled using the online tool DataCite Metadata Generator - Kernel 4.4 provided by DataCite Metadata Working Group. (2021). DataCite Metadata Schema Documentation for the Publication and Citation of Research Data and Other Research Outputs. Version 4.4. DataCite e.V. https://doi.org/10.14454/3w3z-sa82.

Land-In-Pro Pilot Site Mapping © 2025 by Land-In-Pro Project - Federica Pompejano and Sara Mauri, Department of Architecture and Design (DAD), Università di Genova (UniGe) is licensed under Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). If not otherwise indicated, images were acquired by researchers during fieldwork and mapping activities conducted under Land-In-Pro research project's WP2 and WP3 within the territorial context of the pilot site (Ferrania, Cairo Montenotte, Savona, Italy). The information contained in each form is the result of a combined processing of raw fieldwork data and the elaboration of heterogeneous historical sources, including: archival materials (currently under inventory process) from the Ferrania Film Museum in Cairo Montenotte (SV); municipal building records (Municipal Archive of Building Practices, Municipality of Cairo Montenotte, Savona); and historical cadastral maps (Cadastral Map Collection, State Archives of Savona). All consultation permits were previously acquired. Consulted archive materials are available for on-site consultation under each archive's rules and conditions.

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.