Spatial-temporal characteristics and causes of changes to the county-level administrative toponyms cultural landscape in the eastern plains of China

Abstract

As part of the cultural landscape, administrative toponyms do not only reflect natural and sociocultural phenomena, but also help with related management and naming work. Historically, county-level administrative districts have been stable and basic administrative regions in China, playing a role in the country's management. We explore the spatio-temporal evolutionary characteristics of the county-level administrative toponyms cultural landscape in China's eastern plains areas. A Geographical Information System (GIS) analysis, Geo-Informatic Tupu, Kernel Density Estimation, and correlation coefficients were conducted. We constructed a GIS database of county-level administrative toponyms from the Sui dynasty onward using the Northeast China, North China, and Yangtze Plains as examples. We then summarized the spatio-temporal evolutionary characteristics of the county-level administrative toponyms cultural landscape in China's eastern plains areas. The results indicate that (1) the number of toponyms has roughly increased over time; (2) toponym densities on the three plains are higher than the national average in the corresponding timeframe since the Sui; and (3) county-level administrative toponyms related to mountains and hydrological features accounted for more than 30% of the total in 2010. However, the percentage of county-level administrative toponyms related to natural factors on the three plains has decreased since the Sui. To explore the factors influencing this spatio-temporal evolution, we analyzed the correlations between the toponyms and natural factors and human/social factors. The correlation degree between toponym density and population density is the highest, and that between toponym density and Digital Elevation Model (DEM) the lowest. Temperature changes were important in toponym changes, and population changes have influenced toponym changes over the last 400 years in China.

Fig 1. Distribution map of county-level administrative toponyms with the time of being named from 1,000 years ago.

The dots represent data on county-level administrative toponyms with naming time from 1,000 years ago. The green dots represent county-level administrative toponyms being named for 1,000–1,499 years, blue dots those being named for 1,500–1,999 years, and red dots those being named for 2,000 years ago.

Fig 2. Map of the case study areas.

Fig 3. Generation and transmission mode of Geo-Informatic Tupu.

Fig 4. Spatio-temporal evolution of county-level administrative toponyms in the Northeast China Plain since the Sui dynasty.

Fig 5. Spatio-temporal evolution of county-level administrative toponyms in the North China Plain since the Sui dynasty.

Fig 6. Spatio-temporal evolution of county-level administrative toponyms in the Yangtze Plain since the Sui dynasty.

Fig 7. Distribution characteristics of naming time of county-level administrative toponyms in 2010.

Fig 8. DEM data of the case study areas.

DEM data at a resolution of 30 m were provided by the RESDC.

Fig 9. Spatial distribution of toponym density and county GDP of the Northeast China Plain.

The statistical data on China’s GDP in 2010 (Figs 8, 10, 12) were obtained from the RESDC.

Fig 10. Spatial distribution of toponym density and county population density in the Northeast China Plain.

Population data at the county level (Figs 9, 11, 13) were obtained from the 6^th Census of China (2010).

Fig 11. Spatial distribution of toponym density and county GDP of the North China Plain.

Fig 12. Spatial distribution of toponym density and county population density in the North China Plain.

Fig 13. Spatial distribution of toponym density and county GDP of the Yangtze Plain.

Fig 14. Spatial distribution of toponym density and county population density in the Yangtze Plain.

Fig 15. Trend chart of toponym, population, and temperature changes.

The temperature values in Fig 15 are the change values with the current temperature. For historical population data, we referred to the statistical data from the National Earth System Science Data Sharing Infrastructure, National Science & Technology Infrastructure of China, and made some adjustments.