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.

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).

Four digital water-surface profile maps for a 14-mile reach of the Mississippi River near Prairie Island in Welch, Minnesota from the confluence of the St. Croix River at Prescott, Wisconsin to upstream of the United States Army Corps of Engineers (USACE) Lock and Dam No. 3 in Welch, Minnesota, were created by the U.S. Geological Survey (USGS) in cooperation with the Prairie Island Indian Community. The water-surface profile maps depict estimates of the areal extent and depth of inundation corresponding to selected water levels (stages) at the USGS streamgage Mississippi River at Prescott, Wisconsin (USGS station number 05344500). Current conditions for estimating near-real-time areas of water inundation by use of USGS streamgage information may be obtained on the internet at http://waterdata.usgs.gov/. Water-surface profiles were computed for the stream reach using HEC-GeoRAS software by means of a one-dimensional step-backwater HEC-RAS hydraulic model using the steady-state flow computation option. The hydraulic model used in this study was previously created by the USACE . The original hydraulic model previously created extended beyond the 14-mile reach used in this study. After obtaining the hydraulic model from USACE, the HEC-RAS model was calibrated by using the most current stage-discharge relations at the USGS streamgage Mississippi River at Prescott, Wisconsin (USGS station number 05344500). The hydraulic model was then used to determine four water-surface profiles for flood stages referenced to 37.00, 39.00, 40.00, and 41.00-feet of stage at the USGS streamgage on the Mississippi River at Prescott, Wisconsin (USGS station number 05344500). The simulated water-surface profiles were then combined with a digital elevation model (DEM, derived from light detection and ranging (LiDAR) in Geographic Information System (GIS) data having a 0.35-foot vertical and 1.97-foot root mean square error horizontal resolution) in order to delineate the area inundated at each stage. The calibrated hydraulic model used to produce digital water-surface profile maps near Prairie Island, as part of the associated report, is documented in the U.S. Geological Survey Scientific Investigations Report 2021-5018 (https://doi.org/10.3133/ sir20215018). The data provided in this data release contains three zip files: 1) MissRiverPI_DepthGrids.zip, 2) MissRiverPI_InundationLayers.zip, and 3) ModelArchive.zip. The MissRiverPI_DepthGrids.zip and MissRiverPI_InundationLayers.zip files contain model output water-surface profile maps as shapefiles (.shp) and Keyhole Markup Language files (.kmz) that can be opened using Esri GIS systems (.shp files) or Google Earth (.kmz files), while the ModelArchive.zip contains model inputs, outputs, and calibration data used in creating the water-surface profiles maps.

This data came from a desktop study in 2011. Updates were provided by Local Authorities when the paper cycle maps were updated. This dataset was last revised in 2018, and is not up-to-date as bike shops frequently open and close.

This cycle map data has been collated from a number of different sources by Transport for Greater Manchester and cannot be guaranteed to be fully correct.

Data available in MapInfo .tab, Google .kmz, and ESRI .shp file formats.

Please acknowledge the source of this information using the following attribution statement:

Contains Transport for Greater Manchester data. Contains OS data © Crown copyright and database right 2018.

This repository contains the shapefiles of airborne infrared-derived fire perimeters of the two California wildland fires (the 2013 Rim Fire and the 2021 Dixie Fire) used as examples to produce fire progression maps in the manuscript "Consistency in Pyrocartography Starts With Color" by Hatchett (2025).

The infrared perimeters for each fire were acquired from the National Interagency Fire Center's (NIFC) File Transfer Protocol Server (https://ftp.wildfire.gov). Files were initially downloaded in .kmz formats and converted to shapefiles using QGIS. Because not all days of a wildland fire receive aerial mapping due to aircraft availability or weather conditions (or for other reasons), all available near-daily perimeters were acquired, processed, and aggregated into an individual zip file for each fire. The original file names were maintained as acquired from the NIFC database.

Direct link to the Rim Fire data:

https://ftp.wildfire.gov/public/incident_specific_data/calif_s/2013_Incidents/2013_Rim_CA-STF-00028/IR/

Direct link to the Dixie Fire data:

https://ftp.wildfire.gov/public/incident_specific_data/calif_n/!CALFIRE/2021_Incidents/CA-BTU-009205_Dixie/IR/NIROPS/

Reference:

Hatchett, B. J., 2025: GCInsights: Consistency in Pyrocartography Starts With Color, Geoscience Communication, 8, 167–173, https://doi.org/10.5194/gc-8-167-2025.

This dataset presents the technical potential for offshore wind development at the country level, split into potential for fixed and floating foundations. The files are grouped per WB regions and delivered in .SHP, .KMZ (CRS:4326) and .EXCEL format. We recommend non-GIS users to explore the EXCEL files that summarize the technical potential per country; furthermore, users can explore the KML files interactively in Google Earth/ Google Maps application. Please read the METADATA file for more information on the methodology used for the spatial analysis. This analysis was undertaken as part of the World Bank Group’s Offshore Wind Development Program which is led by ESMAP in partnership with IFC. The program is supporting the inclusion of offshore wind into the energy sector policies and strategies of WBG client countries and the delivering the technical work needed to build a pipeline of bankable projects. Maps showing the technical resource potential for 56 countries and regions are provided here; The World Bank and ESMAP do not guarantee the accuracy of this data and accept no responsibility whatsoever for any consequences of their use. The maritime boundaries do not imply on the part of the World Bank any judgement on the legal status of any territory or the endorsement or acceptance of such boundaries.

The framework of the Cordilleran orogen of northwestern North America is commonly depicted as a ‘collage’ of terranes – crustal blocks containing records of a variety of geodynamic environments including continental fragments, pieces of island arc crust and oceanic crust. The series of maps available here are derived from a GIS compilation of terranes based on the map first published by Colpron et al. (2007) and more recently revised by Nelson et al. (2013). These maps are presented here in digital formats including ArcGIS file geodatabase (.gdb), shapefiles (.shp and related files), Google Earth (.kmz), as well as graphic files (.pdf). The GIS dataincludes terrane polygons and selected major Late Cretaceous and Tertiary strike-slip faults. Graphic PDF files derived from the GIS compilation were prepared for the Northern Cordillera (Alaska, Yukon and BC), the Canadian Cordillera (BC and Yukon), Yukon, and British Columbia. These maps are intended for page-size display (~1:5,000,000 and smaller). Polygons are accurate to ~1 km for Yukon and BC, ~5 km for Alaska. More detailed geological data are available from both BCGC, USGS and YGS websites. Descriptions of the terranes, their tectonic evolution and metallogeny can be found in Colpron et al. (2007), Nelson and Colpron (2007), Colpron and Nelson (2009), Nelson et al. (2013) and references therein.The terrane map project is a collaborative effort of the BC Geological Survey and the Yukon Geological Survey.Distributed from GeoYukon by the Government of Yukon. Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: geomatics.help@gov.yk.ca

The framework of the Cordilleran orogen of northwestern North America is commonly depicted as a ‘collage’ of terranes – crustal blocks containing records of a variety of geodynamic environments including continental fragments, pieces of island arc crust and oceanic crust. The series of maps available here are derived from a GIS compilation of terranes based on the map first published by Colpron et al. (2007) and more recently revised by Nelson et al. (2013). These maps are presented here in digital formats including ArcGIS file geodatabase (.gdb), shapefiles (.shp and related files), Google Earth (.kmz), as well as graphic files (.pdf). The GIS dataincludes terrane polygons and selected major Late Cretaceous and Tertiary strike-slip faults. Graphic PDF files derived from the GIS compilation were prepared for the Northern Cordillera (Alaska, Yukon and BC), the Canadian Cordillera (BC and Yukon), Yukon, and British Columbia. These maps are intended for page-size display (~1:5,000,000 and smaller). Polygons are accurate to ~1 km for Yukon and BC, ~5 km for Alaska. More detailed geological data are available from both BCGC, USGS and YGS websites. Descriptions of the terranes, their tectonic evolution and metallogeny can be found in Colpron et al. (2007), Nelson and Colpron (2007), Colpron and Nelson (2009), Nelson et al. (2013) and references therein.The terrane map project is a collaborative effort of the BC Geological Survey and the Yukon Geological Survey.Distributed from GeoYukon by the Government of Yukon. Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: geomatics.help@gov.yk.ca

This data includes the location of cycle stands (e.g. Sheffield Stands) which are generally on-street. All data comes from the Local Authorities. The dataset is available in MapInfo .tab, Google .kmz, and ESRI .shp file formats.

This cycle map data has been collated from a number of different sources by Transport for Greater Manchester and cannot be guaranteed to be fully correct.

Please acknowledge the source of this information using the following attribution statement:

Contains Transport for Greater Manchester data. Contains OS data © Crown copyright and database right 2018.

Cycle routes in Greater Manchester, including on-road, off-road, and canal towpaths and National Cycle Network routes. Data provided by the GM local authorities.

This cycle map data has been collated from a number of different sources by Transport for Greater Manchester and cannot be guaranteed to be fully correct.

Data available in MapInfo .tab, Google .kmz, and ESRI .shp file formats.

Please acknowledge the source of this information using the following attribution statement:

Contains Transport for Greater Manchester data. Contains OS data © Crown copyright and database right 2017.

Cycle routes in Greater Manchester, including on-road, off-road, and canal towpaths and National Cycle Network routes. Data provided by the GM local authorities. The dataset is available in MapInfo .tab, Google .kmz, and ESRI .shp file formats.

This cycle map data has been collated from a number of different sources by Transport for Greater Manchester and cannot be guaranteed to be fully correct.

Please acknowledge the source of this information using the following attribution statement:

Contains Transport for Greater Manchester data. Contains OS data © Crown copyright and database right 2022.

This data set provides a generalized outline of the 72 counties in Wisconsin. The data is derived from 1:24,000-scale sources.

This dataset contains the county boundaries of the state of Florida with an attribute for the Florida Department of Transportation District. This allows the user to display the boundaries of the FDOT District while also being able to segment them by county.

This feature class contains county boundaries for all 64 Colorado counties and 2010 US Census attributes data describing the population within each county.

This coverage contains polygons representing the county boundaries of the state of Iowa. COUNTY was developed from a set of 99 individual coverages of the Public Land Survey System (PLSS) for each county in the state. The PLSS coverages were digitized from paper copies of 7.5' topographic quadrangle maps. River boundaries were also digitized from 7.5' maps. This version also encompass' the Iowa-Nebraska Compact of 1943.