The Banking Bureau of the Department of Insurance Securities and Banking (DISB) regulates District of Columbia Chartered Banks, mortgage companies, and consumer finance companies. The Bureau strives to ensure a sound and thriving financial services community that provides the products, credit, and capital vital to the needs of District of Columbia residents and businesses. DISB charters and regulates District of Columbia banks and other DC depository financial institutions. DISB also regulates non-depository financial institutions such as mortgage lenders and brokers, money transmitters, consumer finance companies, and check cashers. The data is updated as needed.

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).

Data OriginThe dataset provided by Ofwat is rooted in legal records. The dataset is digitised from the official appointments of companies as water and sewage undertakers, which include legally binding documents and maps. These documents establish the specific geographic areas each water company is responsible for. The dataset was sourced from Constituency information: Water companiesData TriageAnonymisation is not required for this dataset, since the data is publicly available and focuses on geographical boundaries of water companies rather than individual or sensitive information. The shapefile serves a specific purpose related to geospatial analysis and regulatory compliance, offering transparent information about the service areas of different water companies as designated by Ofwat.Further ReadingBelow is a curated selection of links for additional reading, which provide a deeper understanding of the water company boundaries datasetOfwat (The Water Services Regulation Authority): As the regulatory body for water and wastewater services in England and Wales, Ofwat's website is a primary source for detailed information about the water industry, including company boundaries.Data.gov.uk: This site provides access to national datasets, including the Water Resource Zone GIS Data (WRMP19), which covers all water resource zones in England. This dataset is crucial for understanding geographical boundaries related to water management.Water UK: As a trade body representing UK water and wastewater service providers, Water UK's website offers insights into the industry's workings, including aspects related to geographical boundaries.Specifications and CaveatsWhen compiling the dataset, the following specifications and caveats were made:This shapefile is intended solely for geospatial analysis. The authoritative legal delineation of areas is maintained in the maps and additional details specified in the official appointments of companies as water and/or sewerage undertakers, along with any alterations to their areas.The shapefile does not encompass data on any structures or properties that, despite being outside the designated boundary, are included in the area, or those within the boundary yet excluded from the area.In terms of geospatial analysis and visual representation, the Mean High Water Line has been utilized to define any boundary extending into the sea, though it's more probable that the actual boundary aligns with the low water mark. Furthermore, islands that are incorporated into the area might not be included in this representation.Ofwat’s data was last updated on 25th May 2022Contact Details If you have a query about this dataset, please email foi@ofwat.gov.uk

North Carolina Division of Emergency Management branches.

Polygons in this feature service are derived from many sources. These include state divisions' data, irrigation company websites and other online information, shapefiles received from various entities, and some unknown sources. The hope is to discover the unknown sources, or to replace them with new ones. Ideally, all boundaries will be derived with input from irrigation companies. This feature service is a work in progress, and known to not be complete.

Version: GOGI_V10_2This data was downloaded as a File Geodatabse from EDX at https://edx.netl.doe.gov/dataset/global-oil-gas-features-database. This data was developed using a combination of big data computing, custom search and data integration algorithms, and expert driven search to collect open oil and gas data resources worldwide. This approach identified over 380 data sets and integrated more than 4.8 million features into the GOGI database.Access the technical report describing how this database was produced using the following link: https://edx.netl.doe.gov/dataset/development-of-an-open-global-oil-and-gas-infrastructure-inventory-and-geodatabase” Acknowledgements: This work was funded under the Climate and Clean Air Coalition (CCAC) Oil and Gas Methane Science Studies. The studies are managed by United Nations Environment in collaboration with the Office of the Chief Scientist, Steven Hamburg of the Environmental Defense Fund. Funding was provided by the Environmental Defense Fund, OGCI Companies (Shell, BP, ENI, Petrobras, Repsol, Total, Equinor, CNPC, Saudi Aramco, Exxon, Oxy, Chevron, Pemex) and CCAC.Link to SourcePoint of Contact: Jennifer Bauer email:jennifer.bauer@netl.doe.govMichael D Sabbatino email:michael.sabbatino@netl.doe.gov

Welcome to Apiscrapy, your ultimate destination for comprehensive location-based intelligence. As an AI-driven web scraping and automation platform, Apiscrapy excels in converting raw web data into polished, ready-to-use data APIs. With a unique capability to collect Google Address Data, Google Address API, Google Location API, Google Map, and Google Location Data with 100% accuracy, we redefine possibilities in location intelligence.

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GIST Impact in partnership with the Integrated Biodiversity Assessment Tool (IBAT) offers a suite of science-based ESG data products that provide an accurate and comprehensive picture of companies’ impacts and dependencies on nature.

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By defining a buffer as an influence area, we have carefully determined the assets intersecting with both KBA and WDPA boundaries. Our analysis extends beyond the mere identification of asset intersections, delving into the realm of environmental impact. We have thoroughly examined the influence areas of assets located within KBA regions, identifying the presence of IUCN Red List threatened species. This critical assessment sheds light on the potential impact of corporate activities on endangered species, emphasizing the need for proactive conservation measures.

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