China’s Intangible Cultural Heritage (ICH) refers to cultural heritage that exists in non-material forms and is transmitted through intangible means. This heritage encompasses a wide range of cultural practices, including oral traditions, performing arts, social customs, festivals, and traditional craftsmanship skills. Conceptually, ICH can be viewed as a form of intangible cultural legacy, encompassing traditional knowledge such as Beijing Opera, Kunqu Opera, paper-cutting, embroidery, Traditional Chinese Medicine, and herbal medicine.

The United Nations Educational, Scientific and Cultural Organization (UNESCO) has inscribed 43 elements from China on its Lists of the Intangible Cultural Heritage of Humanity. Since 2006, the Chinese government has announced five batches of nationally representative ICH projects, currently totaling 3,000 entries. The national-level recognition and documentation of ICH are crucial for its protection, transmission, and dissemination.

In a data journalism research project aimed at exploring the relationship between ICH and economic development in rural and remote areas, we attempted to utilize 3,610 entries recorded on the “China Intangible Cultural Heritage · China Intangible Cultural Heritage Digital Museum” Using the Baidu Map API, we geocoded these data to county-level precision, subsequently generating a heat map of ICH distribution.

Data crawling

The data source is the list of nationally representative ICH projects (including 3,610 sub-items) recorded on the China Intangible Cultural Heritage Network. Through web scraping, information such as the name, category, time, nominating region or unit, and the organization responsible for protecting the cultural heritage can be obtained for each item. To create the distribution heat map, we retained the nominating region. An example of county-level precision data is as follows:

Obtaining Geographic Information

In Python, it is possible to draw distribution maps with provincial-level accuracy by using the names of provinces. However, to achieve county-level accuracy, we need to obtain the latitude and longitude data for each county using the API provided by Baidu Maps. After obtaining the latitude and longitude data, we can then proceed to draw a heat map.

The final inclusion of latitude and longitude data should be as follows:

The method of obtaining latitude and longitude has been adapted according to StimuMing’s approach.

Alternative Methods

Certainly, if high precision is not a requisite or if the quantity of data points is amenable to manual or visual inspection, one might consider employing GPT to generate latitude and longitude coordinates. However, it is advisable to construct a prompt that encourages GPT to strive for maximum accuracy or to reference publicly available data sources.

Nevertheless, it is important to note that GPT may produce erroneous results with an air of authority when confronted with such geospatial queries.

Creating a Heatmap

Creating a heatmap can be effectively accomplished using the pyecharts library. Pyecharts is a powerful visualization tool that leverages the capabilities of the ECharts framework, which is developed by Baidu. This library allows for a wide array of data visualizations, including the creation of heatmaps, which are particularly useful for representing the intensity of data points across a two-dimensional plane.

Now, you have acquired a distribution heat map of intangible cultural heritage (ICH) elements. This visualization reveals a pattern that demonstrates a notable correlation with economic development levels—exhibiting a pronounced east-west gradient and a south-north disparity. The Beijing-Tianjin-Hebei region and the Yangtze River Delta (encompassing Jiangsu, Zhejiang, and Shanghai) unequivocally emerge as hotspots of ICH concentration.

Concomitantly, areas with significant ethnic minority populations, such as Guizhou, also manifest as regions of high ICH density. This phenomenon warrants further investigation into the interplay between cultural diversity, economic development, and the preservation of intangible cultural assets.

The observed distribution pattern raises several pertinent questions for investigations, data journalism, and even academic research:

1. To what extent does economic prosperity facilitate or impede the preservation and documentation of ICH?
2. How do urbanization and modernization processes influence the spatial distribution of ICH elements?
3. What role do ethnic minority communities play in maintaining and transmitting intangible cultural practices, particularly in economically less developed regions?
4. Are there policy implications to be drawn from this spatial distribution, particularly regarding the allocation of resources for ICH preservation and promotion?
5. How might this distribution pattern evolve over time, and what are the potential implications for cultural sustainability and national identity?

This spatial analysis provides a foundation for more nuanced investigations into the complex relationships between geography, economics, ethnicity, and cultural heritage in the Chinese context.