This dataset contains the basic information of tourism resource units in Liangzhou District, Wuwei City in 2024, including key indicators such as unit number, name, category, level, type, location, longitude, latitude, and town level zoning. Based on the "Classification, Survey and Evaluation of Tourism Resources (GB/T18972-2017)", a comprehensive survey was conducted on 531 individual tourism resources to form the main category composition data and town level administrative unit distribution data of tourism resources in Liangzhou District. The dataset covers 531 individual tourism resources, including 7 main categories, 15 subcategories, and 48 basic types such as geological landscape, water landscape, biological landscape, astronomical and climatic landscape, architecture and facilities, historical relics, and tourism products. This data can provide data support for regional tourism planning, resource development, and protection in Liangzhou District.
| collect time | 2026/02/06 - 2026/02/06 |
|---|---|
| collect place | Liangzhou District, Wuwei City, Gansu Province |
| data size | 34.2 KiB |
| data format | *.shp |
| Data time resolution | year |
| Coordinate system | WGS84 |
This data is led by the Culture, Sports, Radio, Television and Tourism Bureau of Liangzhou District, Wuwei City, Gansu Province, in collaboration with multiple departments and professional technical teams, and obtained through the process of "data collection pre catalog preparation field investigation indoor organization results preparation". The census work is strictly carried out in accordance with the "Classification, Investigation and Evaluation of Tourism Resources (GB/T18972-2017)", "Technical Regulations for the Census of Tourism Resources in Gansu Province", and "Handbook for the Census of Tourism Resources in Gansu Province". Data collection is combined with literature review and field investigation. The literature covers local chronicles, tourism planning, cultural relics archives, natural resource data, etc., sourced from the cultural and tourism, housing and construction, natural resources and other departments of Liangzhou District, as well as official media platforms; Based on the pre catalog, the on-site investigation is divided into survey units, and positioning instruments, imaging equipment, and tourism resource digital acquisition systems are used to conduct two rounds of field supplementary investigations, synchronously completing information input and three-level review. Data processing integrates literature, graphics, tables, images, and other materials to form a resource directory, individual survey forms, and achievement reports, comprehensively recording the types, characteristics, distribution, and development and protection status of tourism resources in Liangzhou District, and ultimately forming detailed information data of 531 individual tourism resources.
Input the original tourism resource point vector data (point feature layer, including resource location coordinates); Overlay the administrative boundary vector layer of Liangzhou District as a geographic reference, and finally output it in SHP format.
This dataset is a derived data product that converts discrete resource points into continuous density fields through standard spatial analysis processes, used to reveal the spatial agglomeration pattern of tourism resources.
(1) Basic data quality control: The original point data is obtained by the official census team through field investigation, archive verification, and multi-source positioning, following unified national standards to ensure the standardization and authority of resource classification, positioning, and attributes; The census process includes multiple rounds of internal audits and expert reviews.
(2) Data processing quality control: In the ArcGIS 10.8 platform, kernel density analysis is strictly performed according to standard tool parameters; Visual inspection and statistical verification before and after processing (comparing the consistency between the original point distribution and density hotspots); Manually review outliers (high-density isolated points).
(3) Complete generation process: raw point data collection (field survey+spatial positioning) → data cleaning and vector layer construction → ArcGIS kernel density estimation analysis (parameter setting+calculation) → hierarchical rendering and administrative boundary overlay → output dataset.
(4) Usage: The mature ArcGIS spatial analysis module is used throughout the process, with no custom scripts or non-standard algorithms.
| # | number | name | type |
| 1 | 2025KY025 | Measurement of Value-Added and Economic Contribution of Cultural and Tourism Industry in Gansu Province Based on the IO-TSA Integrated Model | other |
This work is licensed under
CC BY 4.0 (Creative Commons Attribution 4.0 International License).
| # | title | file size |
|---|---|---|
| 1 | 2024年凉州区旅游资源单体数据集.zip | 34.2 KiB |
| # | category | title | author | year |
|---|---|---|---|---|
| 1 | paper | 2024 Spatial Distribution Dataset of Tourism Resources in Liangzhou District, Wuwei City, Gansu Province | Wen Qian | 2026 |
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