Introduction

Geographical scale, in terms of spatial extent, provide a basis for other branches of science. This dataset contains newly proposed geographical and geological GIS boundaries for the Pan-Tibetan Highlands (new proposed name for the High Mountain Asia), based on geological and geomorphological features. This region comprises the Tibetan Plateau and three adjacent mountain regions: the Himalaya, Hengduan Mountains and Mountains of Central Asia, and boundaries are also given for each subregion individually. The dataset will benefit quantitative spatial analysis by providing a well-defined geographical scale for other branches of research, aiding cross-disciplinary comparisons and synthesis, as well as reproducibility of research results.

The dataset comprises three subsets, and we provide three data formats (.shp, .geojson and .kmz) for each of them. Shapefile format (.shp) was generated in ArcGIS Pro, and the other two were converted from shapefile, the conversion steps refer to 'Data processing' section below. The following is a description of the three subsets:

(1) The GIS boundaries we newly defined of the Pan-Tibetan Highlands and its four constituent sub-regions, i.e. the Tibetan Plateau, Himalaya, Hengduan Mountains and the Mountains of Central Asia. All files are placed in the "Pan-Tibetan Highlands (Liu et al._2022)" folder.

(2) We also provide GIS boundaries that were applied by other studies (cited in Fig. 3 of our work) in the folder "Tibetan Plateau and adjacent mountains (Others’ definitions)". If these data is used, please cite the relevent paper accrodingly. In addition, it is worthy to note that the GIS boundaries of Hengduan Mountains (Li et al. 1987a) and Mountains of Central Asia (Foggin et al. 2021) were newly generated in our study using Georeferencing toolbox in ArcGIS Pro.

(3) Geological assemblages and characters of the Pan-Tibetan Highlands, including Cratons and micro-continental blocks (Fig. S1), plus sutures, faults and thrusts (Fig. 4), are placed in the "Pan-Tibetan Highlands (geological files)" folder.

Note: High Mountain Asia: The name ‘High Mountain Asia’ is the only direct synonym of Pan-Tibetan Highlands, but this term is both grammatically awkward and somewhat misleading, and hence the term ‘Pan-Tibetan Highlands’ is here proposed to replace it. Third Pole: The first use of the term ‘Third Pole’ was in reference to the Himalaya by Kurz & Montandon (1933), but the usage was subsequently broadened to the Tibetan Plateau or the whole of the Pan-Tibetan Highlands. The mainstream scientific literature refer the ‘Third Pole’ to the region encompassing the Tibetan Plateau, Himalaya, Hengduan Mountains, Karakoram, Hindu Kush and Pamir. This definition was surpported by geological strcture (Main Pamir Thrust) in the western part, and generally overlaps with the ‘Tibetan Plateau’ sensu lato defined by some previous studies, but is more specific.

More discussion and reference about names please refer to the paper. The figures (Figs. 3, 4, S1) mentioned above were attached in the end of this document.

Data processing

We provide three data formats. Conversion of shapefile data to kmz format was done in ArcGIS Pro. We used the Layer to KML tool in Conversion Toolbox to convert the shapefile to kmz format. Conversion of shapefile data to geojson format was done in R. We read the data using the shapefile function of the raster package, and wrote it as a geojson file using the geojson_write function in the geojsonio package.

Version

Version 2022.1.

Acknowledgements

This study was supported by the Strategic Priority Research Program of Chinese Academy of Sciences (XDB31010000), the National Natural Science Foundation of China (41971071), the Key Research Program of Frontier Sciences, CAS (ZDBS-LY-7001). We are grateful to our coauthors insightful discussion and comments. We also want to thank professors Jed Kaplan, Yin An, Dai Erfu, Zhang Guoqing, Peter Cawood, Tobias Bolch and Marc Foggin for suggestions and providing GIS files.

Citation

Liu, J., Milne, R. I., Zhu, G. F., Spicer, R. A., Wambulwa, M. C., Wu, Z. Y., Li, D. Z. (2022). Name and scale matters: Clarifying the geography of Tibetan Plateau and adjacent mountain regions. Global and Planetary Change, In revision

Jie Liu & Guangfu Zhu. (2022). Geographical and geological GIS boundaries of the Tibetan Plateau and adjacent mountain regions (Version 2022.1). https://doi.org/10.5281/zenodo.6432940

Contacts

Dr. Jie LIU: E-mail: liujie@mail.kib.ac.cn;

Mr. Guangfu ZHU: zhuguangfu@mail.kib.ac.cn

Institution: Kunming Institute of Botany, Chinese Academy of Sciences

Address: 132# Lanhei Road, Heilongtan, Kunming 650201, Yunnan, China

Copyright

This dataset is available under the Attribution-ShareAlike 4.0 International (CC BY-SA 4.0).

geodata data package providing geojson polygons for all the world's countries

Overview

Empower your location data visualizations with our edge-matched polygons, even in difficult geographies.

Our self-hosted GIS data cover administrative and postal divisions with up to 6 precision levels: a zip code layer and up to 5 administrative levels. All levels follow a seamless hierarchical structure with no gaps or overlaps.

The geospatial data shapes are offered in high-precision and visualization resolution and are easily customized on-premise.

Use cases for the Global Boundaries Database (GIS data, Geospatial data)

• In-depth spatial analysis

• Clustering

• Geofencing

• Reverse Geocoding

• Reporting and Business Intelligence (BI)

Product Features

• Coherence and precision at every level

• Edge-matched polygons

• High-precision shapes for spatial analysis

• Fast-loading polygons for reporting and BI

• Multi-language support

For additional insights, you can combine the GIS data with:

• Population data: Historical and future trends

• UNLOCODE and IATA codes

• Time zones and Daylight Saving Time (DST)

Data export methodology

Our geospatial data packages are offered in variable formats, including - .shp - .gpkg - .kml - .shp - .gpkg - .kml - .geojson

All GIS data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.

Why companies choose our map data

• Precision at every level

• Coverage of difficult geographies

• No gaps, nor overlaps

Note: Custom geospatial data packages are available. Please submit a request via the above contact button for more details.

GIS2DJI is a Python 3 program created to exports GIS files to a simple kml compatible with DJI pilot. The software is provided with a GUI. GIS2DJI has been tested with the following file formats: gpkg, shp, mif, tab, geojson, gml, kml and kmz. GIS_2_DJI will scan every file, every layer and every geometry collection (ie: MultiPoints) and create one output kml or kmz for each object found. It will import points, lines and polygons, and converted each object into a compatible DJI kml file. Lines and polygons will be exported as kml files. Points will be converted as PseudoPoints.kml. A PseudoPoints fools DJI to import a point as it thinks it's a line with 0 length. This allows you to import points in mapping missions. Points will also be exported as Point.kmz because PseudoPoints are not visible in a GIS or in Google Earth. The .kmz file format should make points compatible with some DJI mission software.

The geopusher extension for CKAN automatically converts KML and Shapefile resources uploaded to a CKAN instance into GeoJSON resources. This conversion process allows users to easily access and utilize geospatial data in a modern, web-friendly format without needing to manually reformat the files. The extension operates as a celery task, meaning it can be configured to run automatically when resources are added or updated within CKAN. Key Features: Automatic GeoJSON Conversion: Converts KML and Shapefile resource uploads into GeoJSON format, increasing data usability and accessibility. Celery Task Integration: Operates as a Celery task, enabling asynchronous and automatic conversion upon resource creation or update and allowing other asynchronous operations to be processed at defined times. Batch Conversion: Provides functionality to convert all Shapefile resources on a CKAN instance or a specific subset of datasets at once. Technical Integration: The geopusher extension integrates with CKAN by listening to resource update events. The celery daemon needs to be running for automatic conversion to occur. The extension requires GDAL to be installed on the server to handle the geospatial data conversion. The README shows that the installation and usage involve updating the CKAN configuration Benefits & Impact: By automatically converting geospatial data into GeoJSON, the geopusher extension simplifies the use of KML and Shapefile data within web applications. This automation reduces manual effort, increases accessibility, and helps users to more readily integrate CKAN data into mapping and analysis tools. The automatic conversion ensures that when geospatial data is uploaded to a CKAN repository, users are able to immediately access the data in a suitable format for a wide range of web-based mapping applications, supporting improved data dissemination and collaboration.

These contours come from the city site, myDijon.fr. They were converted to SHP and GeoJSON.

Water Meter points within Fuquay-Varina. Most meter devices are owned and maintained by the Town, which provides water utility services. However, on some commercial sites, for example, the meter box and meter yoke are actually privately owned and maintained while the meter device is owned and maintained by the Town. This water meter dataset is constantly under development and improvement as there is increasing demand to integrate GIS meter information with other solutions. Please note that some meter points are not field-validated and some are not associated with a valid METERID for water service, and may essentially be duplicated legacy locations from old GIS data. Please note that ALL public utility data layers can be downloaded in a single .mpkx (ArcGIS Pro map package file), updated every Friday evening. This .mpkx file can be opened directly with ArcGIS Pro version 3+. Alternatively, you can extract the file geodatabase within it by renaming the file ending .mpkx to .zip and treating it like a zip archive file, for use in any version of ArcGIS Pro or ArcMap software. You can also use QGIS, a powerful, free, and open-source GIS software.The Town of Fuquay-Varina creates, maintains, and serves out a variety of utility information to the public, including its Potable Water System, Sanitary Sewer System, and Stormwater Collection System features. This is the same utility data displayed in our public web map. This utility data includes some features designated as 'private' that are not owned or maintained by the Town, but may be helpful for modeling and other informational purposes. Please pay particular attention to the terms of use and disclaimer associated with these data. Some data includes the use of Subtypes and Domains that may not translate well to Shapefile or GeoJSON downloads available through our Open Data site. Please beware the dangers of cartographic misrepresentation if you are unfamiliar with filtering and symbolizing data based on attributes. Water System Layers:Water LinesWater ValvesWater ManholesFire HydrantsFire Department ConnectionsWater MetersRPZ (Backflow Preventers)Water TankWater Booster StationsHarnett County Water District AreaSewer System Layers:Gravity Sewer LinesForced Sewer LinesSewer ManholesSewer ValvesSewer CleanoutsSewer Pump StationsWastewater Treatment PlantsStormwater System Layers:Stormwater Lines (Pipes)Stormwater Points (Inlets/Outlets/Manholes)Stormwater Control Measure Points (SCM's, such as Wet Ponds / Retention Basins)

1. The numerical range of the geological sensitive area is the data of the geological sensitive area delineation process, which is only for planning reference. When overlaying the relevant map layers, attention should be paid to whether coordinate transformation, base map type, and accuracy will produce errors in order to avoid misinterpretation of the overlaid data. The actual range is still subject to the announced map data. Please download the relevant announcement data from the website of the Central Geological Survey, Ministry of Economic Affairs (https://www.moeacgs.gov.tw) in the Geological Law Zone.2. The boundaries of geological sensitive areas are delineated based on relevant map data, and are subsequently overlaid on topographic maps of equal or smaller scales for announcement. The digitalization of map data is subject to scale and accuracy limitations. When using the geological sensitive area digitalized map layers for overlay, consideration should still be given to the existence of errors. For the delineation method of geological sensitive areas, please refer to the respective delineation plan.3. This dataset has been converted from the original SHP format to GeoJSON format for convenient use through a program. It only includes data related to Tainan, and the conversion results are for reference only.

Overview

Empower your location data visualizations with our edge-matched polygons, even in difficult geographies.

Our self-hosted geospatial data cover administrative and postal divisions with up to 5 precision levels. All levels follow a seamless hierarchical structure with no gaps or overlaps.

The geospatial data shapes are offered in high-precision and visualization resolution and are easily customized on-premise.

Use cases for the Global Administrative Boundaries Database (Geospatial data, Map data)

• In-depth spatial analysis

• Clustering

• Geofencing

• Reverse Geocoding

• Reporting and Business Intelligence (BI)

Product Features

• Coherence and precision at every level

• Edge-matched polygons

• High-precision shapes for spatial analysis

• Fast-loading polygons for reporting and BI

• Multi-language support

For additional insights, you can combine the map data with:

• Population data: Historical and future trends

• UNLOCODE and IATA codes

• Time zones and Daylight Saving Time (DST)

Data export methodology

Our location data packages are offered in variable formats, including - .shp - .gpkg - .kml - .shp - .gpkg - .kml - .geojson

All geospatial data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.

Why companies choose our map data

• Precision at every level

• Coverage of difficult geographies

• No gaps, nor overlaps

Note: Custom geospatial data packages are available. Please submit a request via the above contact button for more details.

117 original plate boundaries from Esri Data and Maps (2007) edited to better match 10 years of earthquakes, land forms and bathymetry from Mapping Our World's WSI_Earth image from module 2. Esri Canada's education layer of plate boundaries and the Smithsonian's ascii file from the download section of the 'This Dynamic Planet' site plate boundaries were used to compare the resulting final plate boundaries for significant differences.

The iotrans extension enhances CKAN's capabilities by allowing users to convert datastore resources into various file formats and, for spatial data, transform them between Coordinate Reference Systems (EPSG). This extension addresses the need to download datastore resources in multiple formats and projections beyond CKAN's built-in options, leveraging Python libraries for data conversion. It provides CKAN actions to facilitate file format conversion and data transformation, primarily intended for administrative users. Key Features: Datastore Resource Conversion: Converts CKAN datastore resources to various formats, including CSV, GeoJSON, GPKG, SHP, JSON, and XML. Coordinate Reference System Transformation: Transforms spatial data between different EPSG codes, enabling data compatibility across various GIS applications. Admin-Only Actions: Introduces two CKAN actions, to_file and prune, accessible only to administrator users for file conversion and temporary file cleanup. Disk-Based Processing: Streams data from the CKAN datastore to a temporary CSV file, reducing memory consumption during format conversion. Spatial Data Handling: Identifies spatial data based on the presence of a "geometry" attribute and converts non-Multi geometry types to their Multi counterparts (e.g., Point to MultiPoint) to ensure consistent geometry types within output files. Shapefile Support: Handles shapefile-specific limitations by truncating column names longer than 10 characters, creating unique column names, and documenting the original-to-truncated name mapping in a zipped text file within the shapefile. Temporary File Management: Uses the /tmp directory as a staging area for file conversions, with a prune action to remove files or directories within this location. Technical Integration: The iotrans extension functions by adding new API actions to CKAN (to_file and prune). These actions interact directly with the CKAN datastore extension, retrieving data in chunks via sequential calls to CKAN's datastore_search API, converting it to different formats, and storing these in the /tmp directory. It requires the CKAN Datastore extension to be active. Benefits & Impact: The iotrans extension streamlines the process of extracting and transforming data from the CKAN datastore, enabling users to easily access data in preferred formats and coordinate reference systems. This enhances data usability and interoperability, making it easier to integrate CKAN data into other applications and workflows. It is especially useful for organizations that need to provide data in various formats to meet diverse user needs.

Easements GIS Layer
The city of Williamsburg's Information Technology Department serves these up for the public as shapefiles.
Converted to GeoJSON, and TopoJSON where applicable.
ref:
http://www.williamsburgva.gov/Index.aspx?page=793

Wetlands GIS Layer
The city of Williamsburg's Information Technology Department serves these up for the public as shapefiles.
Converted to GeoJSON, and TopoJSON where applicable.
ref:
http://www.williamsburgva.gov/Index.aspx?page=793

Sewer Cleanout points in Fuquay-Varina. Note: some cleanouts are privately owned and maintaned but mapped for modeling and informational purposes. Cleanout points from developments prior to 2010's or so may have questionable accuracy in this dataset. Please note that ALL public utility data layers can be downloaded in a single .mpkx (ArcGIS Pro map package file), updated every Friday evening. This .mpkx file can be opened directly with ArcGIS Pro version 3+. Alternatively, you can extract the file geodatabase within it by renaming the file ending .mpkx to .zip and treating it like a zip archive file, for use in any version of ArcGIS Pro or ArcMap software. You can also use QGIS, a powerful, free, and open-source GIS software.The Town of Fuquay-Varina creates, maintains, and serves out a variety of utility information to the public, including its Potable Water System, Sanitary Sewer System, and Stormwater Collection System features. This is the same utility data displayed in our public web map. This utility data includes some features designated as 'private' that are not owned or maintained by the Town, but may be helpful for modeling and other informational purposes. Please pay particular attention to the terms of use and disclaimer associated with these data. Some data includes the use of Subtypes and Domains that may not translate well to Shapefile or GeoJSON downloads available through our Open Data site. Please beware the dangers of cartographic misrepresentation if you are unfamiliar with filtering and symbolizing data based on attributes. Water System Layers:Water LinesWater ValvesWater ManholesFire HydrantsFire Department ConnectionsWater MetersWater Meter VaultsRPZ (Backflow Preventers)Water TankWater Booster StationsHarnett County Water District AreaSewer System Layers:Gravity Sewer LinesForced Sewer LinesSewer ManholesSewer ValvesSewer CleanoutsSewer Pump StationsWastewater Treatment PlantsStormwater System Layers:Stormwater Lines (Pipes)Stormwater Points (Inlets/Outlets/Manholes)Stormwater Control Measure Points (SCM's, such as Wet Ponds / Retention Basins)

Wastewater Treatment Plant points in Fuquay-Varina. Notes: Gravity sewer in the Cape Fear river basin (SW side of Town, broadly speaking) primarily flows to the Harnett County Wastewater Treatment Plant. Kenneth Creek WWTP is no longer in service but the point is still shown as a landmark reference point of sorts.Please note that ALL public utility data layers can be downloaded in a single .mpkx (ArcGIS Pro map package file), updated every Friday evening. This .mpkx file can be opened directly with ArcGIS Pro version 3+. Alternatively, you can extract the file geodatabase within it by renaming the file ending .mpkx to .zip and treating it like a zip archive file, for use in any version of ArcGIS Pro or ArcMap software. You can also use QGIS, a powerful, free, and open-source GIS software.The Town of Fuquay-Varina creates, maintains, and serves out a variety of utility information to the public, including its Potable Water System, Sanitary Sewer System, and Stormwater Collection System features. This is the same utility data displayed in our public web map. This utility data includes some features designated as 'private' that are not owned or maintained by the Town, but may be helpful for modeling and other informational purposes. Please pay particular attention to the terms of use and disclaimer associated with these data. Some data includes the use of Subtypes and Domains that may not translate well to Shapefile or GeoJSON downloads available through our Open Data site. Please beware the dangers of cartographic misrepresentation if you are unfamiliar with filtering and symbolizing data based on attributes. Water System Layers:Water LinesWater ValvesWater ManholesFire HydrantsFire Department ConnectionsWater MetersWater Meter VaultsRPZ (Backflow Preventers)Water TankWater Booster StationsHarnett County Water District AreaSewer System Layers:Gravity Sewer LinesForced Sewer LinesSewer ManholesSewer ValvesSewer CleanoutsSewer Pump StationsWastewater Treatment PlantsStormwater System Layers:Stormwater Lines (Pipes)Stormwater Points (Inlets/Outlets/Manholes)Stormwater Control Measure Points (SCM's, such as Wet Ponds / Retention Basins)

This data set is a conversion of Califonia building footprint file from GeoJSON format to shapefile format. The California building footprint file which contains 10,988,525 computer generated building footprints in California state is extracting from US building footprint dataset by Microsoft (2018).

Overview

Empower your location data visualizations with our edge-matched polygons, even in difficult geographies.

Our self-hosted geospatial data cover postal divisions for the whole world. The geospatial data shapes are offered in high-precision and visualization resolution and are easily customized on-premise.

Use cases for the Global Boundaries Database (Geospatial data, Map data, Polygon daa)

• In-depth spatial analysis

• Clustering

• Geofencing

• Reverse Geocoding

• Reporting and Business Intelligence (BI)

Product Features

• Coherence and precision at every level

• Edge-matched polygons

• High-precision shapes for spatial analysis

• Fast-loading polygons for reporting and BI

• Multi-language support

For additional insights, you can combine the map data with:

• Population data: Historical and future trends

• UNLOCODE and IATA codes

• Time zones and Daylight Saving Time (DST)

Data export methodology

Our location data packages are offered in variable formats, including - .shp - .gpkg - .kml - .shp - .gpkg - .kml - .geojson

All geospatial data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.

Why companies choose our map data

• Precision at every level

• Coverage of difficult geographies

• No gaps, nor overlaps

Note: Custom geospatial data packages are available. Please submit a request via the above contact button for more details.

Abstract

Geodata from Uganda Uganda administrative boundaries and distribution of electic lines have been converted from shapefiles (.shp) to tables including the geospatial information in a geojson or geobuf_* column using NodeJS shapefile utilities.

Stormwater Pipe/Conveyance Lines in Fuquay-Varina. Please note that many of the stormwater line features represent privately owned and maintained pipes, and these are essential for mapping and understanding the stormwater drainage network sub-systems at the neighborhood level. Please pay attention to the Subtype field to identify the different categories of public vs. private and culvert type stormwater lines. Directionality (start vs. end vertices) of these line features reflects real world flow direction. The GIS data in the area of Downtown Fuquay-Varina has a lot of old and erroneous stormwater features. A project is currently underway to correct much of this inaccurate stormwater data. Please note that ALL public utility data layers can be downloaded in a single .mpkx (ArcGIS Pro map package file), updated every Friday evening. This .mpkx file can be opened directly with ArcGIS Pro version 3+. Alternatively, you can extract the file geodatabase within it by renaming the file ending .mpkx to .zip and treating it like a zip archive file, for use in any version of ArcGIS Pro or ArcMap software. You can also use QGIS, a powerful, free, and open-source GIS software.The Town of Fuquay-Varina creates, maintains, and serves out a variety of utility information to the public, including its Potable Water System, Sanitary Sewer System, and Stormwater Collection System features. This is the same utility data displayed in our public web map. This utility data includes some features designated as 'private' that are not owned or maintained by the Town, but may be helpful for modeling and other informational purposes. Please pay particular attention to the terms of use and disclaimer associated with these data. Some data includes the use of Subtypes and Domains that may not translate well to Shapefile or GeoJSON downloads available through our Open Data site. Please beware the dangers of cartographic misrepresentation if you are unfamiliar with filtering and symbolizing data based on attributes. Water System Layers:Water LinesWater ValvesWater ManholesFire HydrantsFire Department ConnectionsWater MetersWater Meter VaultsRPZ (Backflow Preventers)Water TankWater Booster StationsHarnett County Water District AreaSewer System Layers:Gravity Sewer LinesForced Sewer LinesSewer ManholesSewer ValvesSewer CleanoutsSewer Pump StationsWastewater Treatment PlantsStormwater System Layers:Stormwater Lines (Pipes)Stormwater Points (Inlets/Outlets/Manholes)Stormwater Control Measure Points (SCM's, such as Wet Ponds / Retention Basins)

Description: These files contain the gazetteer used to record distinct, repeated sampling sites across the SAFE Project, including locations in the experimental landscape, the converted landscape surrounding SAFE and forest reserves and protected areas. The data files include a geojson file containing the sampling locations and their associated metadata and a CSV file containing recognized aliases for official gazetteer locations. The data in the csv alias file is deliberately not included in this metadata spreadsheet as the data is primarily used in this CSV format by data checking and other processes. The GIS geometries in the geojson file (using WGS84 coordinates) are taken from a wide range of original GIS files collected from researchers at SAFE: the source files are indicated in the geometry metadata and most will also be available in the SAFE Zenodo community. The files also include the R code used to collate the geometry data from the various source files and create the geojson and aliases files.This update adds new LOMBOK river transects (RRSJI1-6, RR8, RR10, RR19, RR20) Project: This dataset was collected as part of the following SAFE research project: SAFE CORE DATA XML metadata: GEMINI compliant metadata for this dataset is available here Files: This dataset consists of 4 files: SAFE_Gazetteer_metadata_v3.xlsx, gazetteer.geojson, location_aliases.csv, gazetteer_sf.R SAFE_Gazetteer_metadata_v3.xlsx This file only contains metadata for the files below gazetteer.geojson Description: A geojson file containing officially recognised SAFE Project sampling locations, along with basic metadata. This file contains 1 data tables:

SAFE Gazetteer (described in worksheet gazetteer.geojson) Description: This worksheet describes the feature data associated with the geometries in the Gazeetteer.geojson file. Number of fields: 15 Number of data rows: Unavailable (table metadata description only). Fields:

location: The primary ID code used for this location (Field type: id) type: Broad categories describing the different sampling types and campaigns that have been included in the gazetteer (Field type: categorical) plot_size: Intended geometry area for area based sampling locations. (Field type: categorical) display_order: Integer value used to control plotting order in displaying gazetteer data (Field type: numeric) parent: ID of parent location, for locations nested within larger sampling areas (Field type: categorical) region: Broad sampling regions within the SAFE Project (Field type: categorical) fractal_order: Fractal nesting level for core SAFE sampling sites (Field type: numeric) transect_order: Position along sampling point transect within blocks (Field type: numeric) centroid_x: Longitudinal centroid of feature geometry, not defined for linear geometries (Field type: numeric) centroid_y: Latitudinal centroid of feature geometry, not defined for linear geometries (Field type: numeric) source: Name of of original GIS source file containing geometry data (Field type: categorical) bbox_xmin: Geographic bound of geometry (Field type: numeric) bbox_ymin: Geographic bound of geometry (Field type: numeric) bbox_xmax: Geographic bound of geometry (Field type: numeric) bbox_ymax: Geographic bound of geometry (Field type: numeric)

location_aliases.csv Description: A CSV file containing pairs of official location names and accepted aliases, with an additional column showing where a location in an published dataset has been accepted as a gazeteer location This file contains 1 data tables:

SAFE Gazetteer location aliases (described in worksheet location_aliases.csv) Description: This file contains pairs of known aliases for locations and the matching official location ID. Aliases can be global or can be tied to a specific dataset ID. Number of fields: 3 Number of data rows: Unavailable (table metadata description only). Fields:

zenodo_record_id: location_aliases.csv (Field type: id) location: An official SAFE gazetteer location name (Field type: id) alias: A commonly used alternative alias for the location (Field type: id)

gazetteer_sf.R Description: The R file used to generate the two gazetteer files from the source files. The source files are not included in this record as they are published under separate records. Date range: 2010-10-01 to 2020-05-19 Latitudinal extent: 4.4121 to 4.9618 Longitudinal extent: 116.9471 to 117.9959