本数据集源于甘肃省武威市民勤县文体广电和旅游局牵头组织的系统性旅游资源普查，旨在科学揭示旅游资源的空间集聚格局。生产方法基于普查获取的权威点位数据，利用ArcGIS平台，通过核密度估计方法，生成连续的资源密度栅格表面。数据核心要素为旅游资源的核密度值，空间范围覆盖民勤县全域，时间上对应普查时点的资源现状。密度值依据五级区间进行分级命名与可视化，空间分辨率由分析设定的栅格大小决定，并叠加行政边界作为地理参考。
本数据集将离散资源点转化为连续密度场，直观量化了资源分布的热点与空间结构，弥补了传统统计在空间连续性表达上的不足。主要适用于区域旅游规划、资源开发评估、空间格局分析及相关地理学研究。", "ds_source": "
本数据集来源于甘肃省武威市民勤县文体广电和旅游局联合多部门及专业技术团队，通过系统性的实地普查、档案整理与空间定位工作获取的旅游资源单体点位数据。数据采集过程遵循统一的旅游资源分类与调查国家标准，确保了数据源的规范性与权威性。在数据处理与生成方法上，本数据集基于上述获取的旅游资源点位矢量数据，利用专业地理信息系统软件（ArcGIS平台）进行空间分析。具体采用了核密度估计（Kernel Density Estimation）方法，将离散的资源点转换为连续的密度表面，以直观反映旅游资源在空间上的集聚程度与分布热区。密度值结果根据预设的人口密度类比区间进行分级渲染，并叠加了民勤县的行政边界作为地理参照。因此，本数据集属于对原始调查数据进行深度空间分析与可视化加工后形成的派生数据产品，通过特定的空间建模与分析流程（使用ArcGIS软件及核密度估计工具）生产得出，最终生成了反映旅游资源空间集聚格局的核密度栅格数据集。", "ds_process_way": "
输入原始旅游资源点位矢量数据（点要素图层，包含资源位置坐标）。\n使用ArcGIS空间分析工具箱中的“核密度估计”（Kernel Density Estimation）工具，将离散点位转换为连续密度栅格表面；密度值结果按五级区间进行分级渲染（自然断裂法）；叠加民勤县行政边界矢量图层作为地理参考，最终输出为GeoTIFF格式。\n
所用算法：核密度估计（Kernel Density Estimation）。\n
该数据集为派生数据产品，通过标准空间分析流程将离散资源点转化为连续密度场，用于揭示旅游资源空间集聚格局。", "ds_quality": "
（1）基础数据质量控制：原始点位数据由官方普查团队通过实地调查、档案核实、多源定位获取，遵循统一国家标准，确保资源分类、定位与属性的规范性和权威性；普查过程包括多轮内部审核与专家复核。\n
（2）数据加工质量控制：在ArcGIS10.8平台中，严格按照标准工具参数执行核密度分析；处理前后进行目视检查与统计验证（对比原始点位分布与密度热点一致性）；对异常值（孤立点高密度）进行手动复核。\n
（3）完整产生过程：原始点位数据采集（实地普查+空间定位）→数据清洗与矢量图层构建→ArcGIS核密度估计分析（参数设定+计算）→分级渲染与行政边界叠加→输出数据集。\n
（4）使用方法：全程采用成熟的ArcGIS空间分析模块，无自定义脚本或非标准算法。", "ds_acq_start_time": "2026-01-28 00:00:00", "ds_acq_end_time": "2026-01-28 00:00:00", "ds_acq_place": "甘肃省武威市民勤县", "ds_acq_lon_east": 104.11999999999999, "ds_acq_lat_south": 38.03, "ds_acq_lon_west": 101.49, "ds_acq_lat_north": 39.269999999999996, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 74462, "ds_files_count": 2, "ds_format": "*.tif", "ds_space_res": "200 m", "ds_time_res": "年", "ds_coordinate": "WGS84", "ds_projection": "None", "ds_thumbnail": "870de502-8539-4589-aa5e-7c0cbb92d971.png", "ds_thumb_from": 0, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "52b7b79b-860c-49a5-9083-9a70cf8bed5a", "ds_serv_man": "李红星", "ds_serv_phone": "0931-4967592", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.4520" ], "quality_level": 3, "publish_time": "2026-03-24 17:13:01", "last_updated": "2026-04-23 16:49:50", "protected": false, "protected_to": "2026-10-20 00:00:00", "lang": "zh", "cstr": "11738.11.NCDC.TOURISM.DB7198.2026", "i18n": { "en": { "title_en": "2024 Minqin County Tourism Resource Core Density Dataset", "ds_format_en": "*.tif", "ds_source_en": "
This dataset is sourced from the Tourism Bureau of Minqin County, Wuwei City, Gansu Province, in collaboration with multiple departments and professional technical teams. Through systematic field surveys, archive organization, and spatial positioning, individual point data of tourism resources were obtained. The data collection process follows the unified national standards for tourism resource classification and survey, ensuring the standardization and authority of data sources. In terms of data processing and generation methods, this dataset is based on the obtained tourism resource point vector data, and spatial analysis is performed using professional geographic information system software (ArcGIS platform). Specifically, the Kernel Density Estimation method was used to convert discrete resource points into continuous density surfaces, in order to intuitively reflect the degree of spatial clustering and distribution hotspots of tourism resources. The density value results are rendered in a graded manner based on the preset population density analogy interval, and overlaid with the administrative boundaries of Minqin County as a geographic reference. Therefore, this dataset is a derived data product formed by deep spatial analysis and visualization processing of the original survey data. It is produced through specific spatial modeling and analysis processes (using ArcGIS software and kernel density estimation tools), and ultimately generates a kernel density raster dataset that reflects the spatial agglomeration pattern of tourism resources.", "ds_quality_en": "
(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.\r\n
(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).\r\n
(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.\r\n
(4) Usage: The mature ArcGIS spatial analysis module is used throughout the process, with no custom scripts or non-standard algorithms.", "ds_ref_way_en": "", "ds_abstract_en": "", "ds_time_res_en": "", "ds_acq_place_en": "Minqin County, Wuwei City, Gansu Province", "ds_space_res_en": "", "ds_projection_en": "", "ds_process_way_en": "
Input the original tourism resource point vector data (point feature layer, including resource location coordinates).\r\nUse the Kernel Density Estimation tool in the ArcGIS Spatial Analysis Toolbox to convert discrete points into a continuous density grid surface; The density value results are rendered in a graded manner according to a five level interval (natural fracture method); Overlay the administrative boundary vector layer of Minqin County as a geographic reference, and finally output it in GeoTIFF format.\r\n
Algorithm used: Kernel Density Estimation.\r\n
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.", "ds_ref_instruction_en": "" } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "CC BY 4.0 (Creative Commons Attribution 4.0 International License)", "doi_reg_from": "reg_local", "cstr_reg_from": "reg_local", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "ds_topic_tags": [ "旅游资源", "空间分布", "核密度" ], "ds_subject_tags": [ "人文地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "武威市", "民勤县" ], "ds_time_tags": [ 2024 ], "ds_contributors": [ { "true_name": "杨雪梅", "email": "yxm9693@163.com", "work_for": "兰州文理学院", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "杨雪梅", "email": "yxm9693@163.com", "work_for": "兰州文理学院", "country": "中国" } ], "ds_managers": [ { "true_name": "杨雪梅", "email": "yxm9693@163.com", "work_for": "兰州文理学院", "country": "中国" } ], "category": "社会经济文化" }