一、 生产背景\n
在非物质文化遗产（非遗）旅游利用潜力评价研究中，一个长期存在的局限是过于聚焦非遗资源自身的本体价值，而忽略了其赖以存续、展示与体验的物理空间基础。非遗的“无形性”决定了其文化内涵与旅游价值必须通过具体的场所、设施和地理语境才能被有效感知与转化。然而，既有研究在构建评价体系时，普遍缺乏对博物馆、传统村落、旅游景区等关键有形载体的系统性考量，更未深入探究非遗与这些载体之间的空间关联与匹配关系，导致潜力评估结果与现实开发可行性存在脱节。\n
为解决这一核心问题，支撑“非遗资源—空间载体”一体化评价新范式的研究，本数据集应运而生。它旨在系统整合黄河流域内可作为非遗展示、传承与旅游化利用核心平台的多类型有形空间载体，为从地理空间视角量化分析非遗旅游利用潜力提供精准、规范的基础数据。\n
二、 生产方法\n
数据采集：采用权威官方名录抓取与人工校验相结合的方式。所有数据均来源于国家及省级政府主管部门的权威公开名录，具体包括文化和旅游部、住房和城乡建设部、国家文物局等发布的正式公告、统计年鉴及专题名录。\n
数据整合与清洗：对来自不同来源的多源数据进行标准化处理，统一字段格式（如名称、级别、认定批次、所属行政区划），并剔除重复、废止或信息不全的记录。\n
空间化处理（核心步骤）：\n
坐标系统一：所有空间数据均统一至 WGS 1984 地理坐标系，以确保与其他空间数据（如自然环境、社会经济数据）的兼容性。\n
空间属性关联：为每个点位属性关联其所在的省、市、县等多级行政单元代码，便于多尺度分析。\n
核心属性字段包括：唯一ID、载体名称、载体类型、等级/批次、所属行政区划（省、市、县）、详细地址、经度（Longitude）、纬度（Latitude）、认定/公布年份、数据来源\n
三、 数据优势与特点\n
针对性强：专为破解“非遗旅游利用潜力评价中缺乏有形空间载体视角”这一学术痛点而设计，首次将多类型、多层级的文化旅游载体进行系统性空间集成，直接服务于“非遗-载体”耦合研究。\n
多源融合与空间显性：将七类关键载体的多源融合与统一空间化，使得进行载体空间格局分析、密度分析、以及与非遗点的空间关系（如邻近度、服务范围）量化分析成为可能。\n
四、 应用范围\n
本数据集支持文化遗产、旅游地理、城乡规划等多个领域的深入研究与实践应用，主要包括：\n
非遗旅游潜力“载体赋能”评价：作为核心输入数据，用于构建融入“空间载体支撑力”维度的非遗旅游利用潜力综合评价模型。\n
文化与旅游空间匹配分析：分析各类载体与非遗项目的空间分布耦合关系、匹配度及网络结
区域文化遗产保护与利用规划：为划定文化遗产密集区、设计跨区域文化旅游线路、规划遗产活化利用项目（如非遗工坊入驻传统村落、景区非遗体验区建设）提供精准的空间决策支持。\n
人地关系与区域可持续发展研究：结合其他地理数据，探究文化旅游载体分布与自然环境、社会经济因素之间的相互作用机制。", "ds_source": "
本数据集的数据生产主要基于多源权威数据的系统整合与空间化处理。其中，传统村落、历史文化名镇/名村及历史文化名城数据来源于住房和城乡建设部、文化和旅游部、国家文物局等国家部委联合发布的官方名录；A级旅游景区和旅游休闲街区信息通过访问文化和旅游部及各省（自治区、直辖市）文旅厅官方网站提取，并经过人工二次核对以确保准确；博物馆数据引自国家文物局发布的《2019年度全国博物馆名录》；酒店与民宿点位数据则通过高德地图平台，以“酒店”、“民宿”为关键词爬取获得。最后，所有条目均通过高德地图地理编码（Geocoding）API服务，将其详细地址批量转换为标准的经纬度坐标，从而完成数据的空间化，为后续的空间分析奠定基础。", "ds_process_way": "
本数据集通过系统整合多源权威数据，并经过核心两步处理构建而成。首先，对来自官方名录与网站的所有属性数据（如名称、等级、地址）进行人工清洗与标准化，确保信息的准确性与一致性。随后，利用高德地图地理编码（Geocoding）API 将文本地址批量转换为经纬度坐标，并统一至WGS 1984坐标系，完成空间化。最终，将生成的空间点位数据导入ArcGIS等专业软件中，进行地图可视化、空间查询与初步分析，以直观展示黄河流域文化旅游资源的分布格局与集聚特征，为后续研究提供清晰的空间数据基础。", "ds_quality": "
现存数据为A级景区3167项、旅游休闲街区34项、传统村落1204项、历史文化名城36项、历史文化名镇47项、历史文化名村132项、博物馆1399项，以上数据均经过空间一致性核查，通过GIS叠加分析，可快速发现冲突，如一个点位同时被标注为“A级景区”和“自然保护区核心区”，这种空间矛盾将提示人工重点复核。", "ds_acq_start_time": "2023-10-11 00:00:00", "ds_acq_end_time": "2023-10-11 00:00:00", "ds_acq_place": "黄河流域", "ds_acq_lon_east": 119.11472222222221, "ds_acq_lat_south": 32.11472222222223, "ds_acq_lon_west": 95.84138888888889, "ds_acq_lat_north": 42.805, "ds_acq_alt_low": -46.0, "ds_acq_alt_high": 6672.0, "ds_share_type": "apply-access", "ds_total_size": 1716224, "ds_files_count": 2, "ds_format": "*.xlsx", "ds_space_res": "", "ds_time_res": "", "ds_coordinate": "WGS84", "ds_projection": "WGS 1984 World Mercator", "ds_thumbnail": "b1f7b650-361b-4e8d-8180-99ebc7852ebc.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "76330c66-832b-46b3-b501-f5f6edb08dc2", "ds_serv_man": "敏玉芳", "ds_serv_phone": "0931-4967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.4520" ], "quality_level": 3, "publish_time": "2026-01-28 18:35:37", "last_updated": "2026-02-05 09:54:25", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.NIEER.DB7066.2026", "i18n": { "en": { "title": "Dataset of Cultural Tourism Resources in the Yellow River Basin", "ds_format": "*.xlsx", "ds_source": "
The data production of this dataset is mainly based on the systematic integration and spatialization of multi-source authoritative data. Among them, the data of traditional villages, historic and cultural towns/villages and historic and cultural cities are from the official directory jointly issued by the Ministry of Housing and Urban Rural Development, the Ministry of Culture and Tourism, the National Cutural Heritage Administration and other national ministries and commissions; The information of A-level tourist attractions and tourist leisure blocks is extracted by visiting the official websites of the Ministry of Culture and Tourism and the cultural and tourism departments of various provinces (autonomous regions, municipalities directly under the central government), and is manually double checked to ensure accuracy; The museum data is quoted from the 2019 National Museum Directory issued by the National Cutural Heritage Administration; The location data of hotels and homestays are obtained through the Gaode Map platform by crawling with keywords such as \"hotel\" and \"homestay\". Finally, all entries are processed through the Geocoding API service of Amap, which converts their detailed addresses into standard latitude and longitude coordinates in bulk, thus completing the spatialization of the data and laying the foundation for subsequent spatial analysis.", "ds_quality": "
The existing data includes 3167 A-level scenic spots, 34 tourist and leisure blocks, 1204 traditional villages, 36 historical and cultural cities, 47 historical and cultural towns, 132 historical and cultural villages, and 1399 museums. All of these data have undergone spatial consistency verification, and through GIS overlay analysis, conflicts can be quickly identified. For example, if a point is marked as both an \"A-level scenic spot\" and a \"core area of a nature reserve\", this spatial contradiction will prompt manual review.", "ds_ref_way": "", "ds_abstract": "
", "ds_time_res": "", "ds_acq_place": "Yellow River Basin", "ds_space_res": "", "ds_projection": "", "ds_process_way": "
This dataset is constructed by systematically integrating authoritative data from multiple sources and undergoing core two-step processing. Firstly, manually clean and standardize all attribute data (such as name, level, address) from official directories and websites to ensure the accuracy and consistency of the information. Subsequently, using the Geocoding API of Amap, the text addresses were batch converted into latitude and longitude coordinates and unified to the WGS 1984 coordinate system to complete spatialization. Finally, the generated spatial point data will be imported into professional software such as ArcGIS for map visualization, spatial queries, and preliminary analysis, in order to visually display the distribution pattern and aggregation characteristics of cultural tourism resources in the Yellow River Basin, providing a clear spatial data foundation for subsequent research.", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "CC BY 4.0", "doi_reg_from": "reg_local", "cstr_reg_from": "reg_local", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "is_paper_in_submitting": false, "ds_topic_tags": [ "有形空间载体", "无形性" ], "ds_subject_tags": [ "人文地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "黄河流域", "县域" ], "ds_time_tags": [ 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023 ], "ds_contributors": [ { "true_name": "康雷", "email": "kangleisxnu@126.com", "work_for": "山西师范大学", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "康雷", "email": "kangleisxnu@126.com", "work_for": "山西师范大学", "country": "中国" } ], "ds_managers": [ { "true_name": "康雷", "email": "kangleisxnu@126.com", "work_for": "山西师范大学", "country": "中国" } ], "category": "生态" }