为深入探究黄河流域非物质文化遗产的空间分布格局、与自然-社会经济环境因子的复杂耦合关系，明晰非遗旅游开发掣肘点，本研究系统性地整合与构建了本数据集。当前研究非遗的样本数据遴选上，缺乏地方性和多样性的省级非物质文化遗产。本数据集旨在填补该空白，为从事文化遗产地理学、区域可持续发展、文化旅游规划等领域的研究者提供基础数据支撑，服务于黄河流域生态保护与高质量发展的国家战略。\n
一、细节描述：\n
核心数据采集：非遗名录数据通过政府公开名录人工校对相结合的方式获取；国家级非遗源于中国非物质文化遗产数字博物馆https://www.ihchina.cn/ 公布的五批国家级非物质文化遗产项目；省级非遗源于黄河八省人民政府公布的省级非物质文化遗产，各项非遗源起时间源于各县志。\n
空间化处理：所有具有空间位置的信息（如非遗传承点）均通过地理编码转换为地理坐标（经纬度，采用WGS 1984坐标系统）。\n
时空范围：以黄河流域736个县域为基本空间分析单元，包含迄今为止，各县志记录在册的省级、国家级非遗。\n
二、数据优势与特点：\n
当前国家级非遗研究较为完善，学者对省级非遗研究较少，在地方性与文化多样性方面缺乏科学性。将代表性强、更具地方性的省级非遗纳入非遗研究中，为空间异质性检测提供科学样本，对正确认识非遗分布与地理环境要素关系提供理论基础。\n
三、本数据集支持多学科、多尺度的研究与应用，包括但不限于：\n
1深化地方性非遗研究\n
系统性分析：为省级非遗研究提供标准样本，支持分析其空间分布与地方自然、人文环境的耦合关系，揭示被国家级名录掩盖的文化多样性。\n
传承风险评估：通过关联非遗点位与周边环境变量，构建“文化基因”图谱，识别文化圈范围，并评估城镇化等因素对地方性非遗存续的潜在风险。\n
2揭示空间分异规律\n
多尺度异质性检测：利用高密度非遗点与多分辨率环境数据，在流域至县域等多尺度上，运用空间计量模型精确检测影响非遗分布的关键因子及其空间非平稳性。\n
人地关系机理建模：构建“非遗-环境-社会”耦合模型，定量解析地形、河流、经济等要素对非遗形成与演变的驱动机制，为理解非遗分布规律提供理论基础。\n
3支持区域保护与发展\n
资源评估与潜力区划定：整合景区、村落等载体数据，评估非遗资源的旅游转化潜力与空间匹配度，为文化旅游线路设计和保护区划定提供依据。\n
城乡发展适应性研究：结合土地利用与人口经济数据，模拟城市化进程中的非遗传承空间变迁，研究其在生产性保护与社区活化中的适应性策略。\n
4推动数字人文与技术应用\n
时空可视化与传播分析：基于非遗的时空属性，构建演化序列地图与知识图谱，可视化文化传播路径，并结合数字化指数分析其在数字时代的传播网络。\n
预测性建模与前瞻保护：利用机器学习算法，以多源环境和社会经济指标预测潜在的非遗富集区域，为田野调查和遗产保护提供前瞻指引。", "ds_source": "
本研究使用的多源数据主要包括通过公开平台下载、政府公开名录整理及统计年鉴摘录获取。国家级非遗源于中国非物质文化遗产数字博物馆https://www.ihchina.cn/ 公布的五批国家级非物质文化遗产项目；省级非遗源于黄河八省人民政府公布的省级非物质文化遗产，各项非遗源起时间源于各县志。截止2023年10月，非遗数据除去无固定传承点，无考究的源起时间外，共7423项。", "ds_process_way": "
一、 属性与文本数据的数字化\n
此类数据主要指以非空间表格或列表形式存在的原始资料，数字化手段如下：\n
统计资料与名录：国家级非遗和省级非遗，采用人工录入与交叉核对的方式，将中国非物质文化遗产数字博物馆https://www.ihchina.cn/ 公布的五批国家级非物质文化遗产项目；省级非遗源于黄河八省人民政府公布的省级非物质文化遗产，各项非遗源起时间源于各县志内包含的关键信息（如名称、所属行政区、年份、数值指标）录入至结构化表格。为确保准确性，关键字段（如行政区划名称）与国家标准代码进行关联校验。\n
二、 空间数据的数字化与处理\n
所有具有地理空间信息或需要空间化展示的数据，均采用地理信息系统（GIS）软件进行处理。坐标系统一与地理配准：所有栅格与矢量数据均统一转换为 GCS_WGS_1984地理坐标系，并视分析需要进一步投影至适当的投影坐标系，以确保空间位置精确匹配。", "ds_quality": "
截止2023年10月，所搜集的8041项非遗数据包含固定传承点和非固定传承点，有考究时间与无考究时间，非遗数据除去无固定传承点，无考究的源起时间外，共7423项。", "ds_acq_start_time": "2022-10-11 00:00:00", "ds_acq_end_time": "2022-10-11 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": 886340, "ds_files_count": 2, "ds_format": "", "ds_space_res": "", "ds_time_res": "", "ds_coordinate": "WGS84", "ds_projection": "WGS 1984 World Mercator", "ds_thumbnail": "55e03a96-f52e-4c2e-b634-bfa4167d57f6.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 18:25:35", "last_updated": "2026-02-05 09:53:46", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.NIEER.DB7065.2026", "i18n": { "en": { "title": "Intangible Cultural Heritage Dataset for the Yellow River Basin", "ds_format": "", "ds_source": "
The multi-source data used in this study mainly includes downloading through public platforms, compiling government public directories, and extracting statistical yearbooks. National intangible cultural heritage originates from the Digital Museum of China's Intangible Cultural Heritage https://www.ihchina.cn/ Five batches of national intangible cultural heritage projects announced; Provincial intangible cultural heritage originates from the provincial intangible cultural heritage announced by the people's governments of the eight provinces along the Yellow River, and the origin time of each intangible cultural heritage source comes from the county annals. As of October 2023, there are a total of 7423 items of intangible cultural heritage data, excluding those without fixed inheritance points and uncertain origin times.", "ds_quality": "
As of October 2023, the collected 8041 intangible cultural heritage data includes both fixed and non fixed inheritance points, with and without investigation time. Excluding non fixed inheritance points and non investigation origin time, there are a total of 7423 intangible cultural heritage data.", "ds_ref_way": "", "ds_abstract": "
In order to further explore the spatial distribution pattern of intangible cultural heritage in the Yellow River Basin, the complex coupling relationship with natural socio-economic environmental factors, and clarify the constraints of intangible cultural heritage tourism development, this study systematically integrated and constructed this dataset. There is a lack of provincial-level intangible cultural heritage with locality and diversity in the selection of sample data for current research on intangible cultural heritage. This dataset aims to fill this gap and provide basic data support for researchers engaged in cultural heritage geography, regional sustainable development, cultural tourism planning, and other fields, serving the national strategy of ecological protection and high-quality development in the Yellow River Basin.\n
1、 Detail description:\n
Core data collection: The intangible cultural heritage list data is obtained through a combination of manual verification of the government's public list; National intangible cultural heritage originates from the Digital Museum of China's Intangible Cultural Heritage https://www.ihchina.cn/ Five batches of national intangible cultural heritage projects announced; Provincial intangible cultural heritage originates from the provincial intangible cultural heritage announced by the people's governments of the eight provinces along the Yellow River, and the origin time of each intangible cultural heritage source comes from the county annals.\n
Spatialization processing: All information with spatial location (such as non genetic inheritance points) is converted into geographic coordinates (latitude and longitude, using the WGS 1984 coordinate system) through geocoding.\n
Time and space scope: Based on 736 counties in the Yellow River Basin as the basic spatial analysis unit, including provincial and national intangible cultural heritage recorded in the county annals so far.\n
2、 Data advantages and characteristics:\n
At present, the research on national intangible cultural heritage is relatively complete, and scholars have less research on provincial intangible cultural heritage, lacking scientific rigor in terms of locality and cultural diversity. Include provincial intangible cultural heritage with strong representativeness and more local characteristics in intangible cultural heritage research, providing scientific samples for spatial heterogeneity detection and theoretical basis for correctly understanding the relationship between intangible cultural heritage distribution and geographical environmental factors.\n
3、 This dataset supports interdisciplinary and multi-scale research and applications, including but not limited to:\n
1. Deepen research on local intangible cultural heritage\n
Systematic analysis: Provide standard samples for provincial intangible cultural heritage research, support the analysis of the coupling relationship between its spatial distribution and local natural and cultural environment, and reveal the cultural diversity obscured by national level lists.\n
Inheritance risk assessment: By associating intangible cultural heritage sites with surrounding environmental variables, constructing a \"cultural gene\" map, identifying the scope of cultural circles, and evaluating the potential risks of urbanization and other factors to the survival of local intangible cultural heritage.\n
Revealing the laws of spatial differentiation\n
Multi scale heterogeneity detection: Using high-density intangible cultural heritage sites and multi-resolution environmental data, spatial econometric models are used to accurately detect key factors and their spatial non stationarity that affect the distribution of intangible cultural heritage at multiple scales from watersheds to counties.\n
Modeling of Human Environment Relationship Mechanism: Constructing a \"Intangible Cultural Heritage Environment Society\" coupling model to quantitatively analyze the driving mechanisms of terrain, rivers, economy, and other factors on the formation and evolution of intangible cultural heritage, providing a theoretical basis for understanding the distribution patterns of intangible cultural heritage.\n
3. Support regional protection and development\n
Resource assessment and potential area delineation: Integrate data from scenic spots, villages, and other carriers to evaluate the tourism conversion potential and spatial matching of intangible cultural heritage resources, providing a basis for cultural tourism route design and protection area delineation.\n
Research on the Adaptability of Urban and Rural Development: Combining land use and population economic data, simulate the spatial changes of intangible cultural heritage inheritance in the process of urbanization, and study its adaptive strategies in productive protection and community revitalization.\n
4. Promote the application of digital humanities and technology\n
Spatiotemporal Visualization and Communication Analysis: Based on the spatiotemporal attributes of intangible cultural heritage, construct an evolutionary sequence map and knowledge graph, visualize cultural communication paths, and analyze their communication networks in the digital age by combining digital indices.\n
Predictive modeling and prospective conservation: Using machine learning algorithms to predict potential areas of intangible cultural heritage enrichment based on multiple environmental and socio-economic indicators, providing prospective guidance for field investigations and heritage conservation.", "ds_time_res": "", "ds_acq_place": "Yellow River Basin", "ds_space_res": "", "ds_projection": "", "ds_process_way": "
1、 Digitization of attributes and textual data\n
This type of data mainly refers to raw materials that exist in non spatial table or list forms, and the digital methods are as follows:\n
Statistical data and list: National and provincial intangible cultural heritage will be manually recorded and cross checked, and the China Intangible Cultural Heritage Digital Museum will be established https://www.ihchina.cn/ Five batches of national intangible cultural heritage projects announced; Provincial intangible cultural heritage originates from the provincial intangible cultural heritage announced by the people's governments of the eight provinces along the Yellow River. The origin time of each intangible cultural heritage source is derived from key information contained in the county annals (such as name, administrative region, year, numerical indicators) and entered into a structured table. To ensure accuracy, key fields (such as administrative division names) are associated and verified with national standard codes.\n
2、 Digitization and Processing of Spatial Data\n
All data with geographic spatial information or requiring spatial display are processed using Geographic Information System (GIS) software. Coordinate System One and Geographic Registration: All raster and vector data are uniformly converted to the GCSWGS_1984 geographic coordinate system and further projected to an appropriate projection coordinate system as needed for analysis to ensure accurate spatial position matching.", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "recommendation_value": 0, "license_type": "https://creativecommons.org/licenses/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, "belong_to_nieer": false, "ds_topic_tags": [ "省级非物质文化遗产", "国家级非物质文化遗产" ], "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" }