This paper provides an analysis of China’s land border cultural heritage, aiming to offer guidance for its protection and development. The study compiled a comprehensive database of heritage sites and analyzed their mathematical characteristics based on quantity, type, and quality. The spatial pattern of the cultural heritage was described using kernel density analysis, spatial variability, and spatial correlation, while the driving mechanism was measured based on Geo-Detector model. The findings revealed that the land border areas of China have a total of 1227 cultural heritage, comprising two main types and 18 subtypes. National cultural heritage accounted for 22.74%, with ancient city ruins being the largest type of cultural heritage. The Southwest and Northeast regions of China exhibited high-high clusters and low-low clusters, respectively. Moreover, the study identified history of administrative succession, evolution of historical and cultural, altitude, distance from the city, population density, minority population ratio, urbanization process, and per capita GDP as significant factors impacting the spatial pattern of land border cultural heritage in China. Based on these findings, the study suggests that the government should invest more in border cultural heritage, improve transportation infrastructure in border areas, ensure dynamic inheritance and protection of cultural heritage, and promote the joint development of different types of cultural heritage. The research results will provide data support and decision-making reference for the sustainable development of cultural heritage in land border areas, and can provide a new perspective for the management of cultural heritage in similar areas.

Spatial distribution of Intangible Cultural Heritage exhibits significant complexity shaped by diverse geographical and socio-cultural contexts, yet conventional analyses often overlook its intricate heterogeneity and scale effects. Using Geographically Weighted Regression (MGWR) on 3610 Chinese national ICH items, we simultaneously address spatial non-stationarity and scale effects. Results show: (1) Significant spatial clustering (Moran’s I = 0.337, p < 0.01) exists in ICH distribution, confirming an “east-dense, west-sparse” pattern. (2) Pronounced spatial heterogeneity exists; temperature and per capita GDP exhibit opposing effects in different regions, challenging simplistic assumptions. (3) Drivers operate at distinct scales: NDVI functions broadly (bandwidth>360), while topography and economic indicators operate locally (bandwidth<100). These findings reveal complex multi-scalar dynamics, resolving the methodological challenge of concurrently capturing spatial heterogeneity and factor-specific scale effects. Theoretically, it reveals fundamental ICH distribution patterns and mechanisms in China; Practically, it provides a basis for spatially differentiated conservation strategies in China and globally.

The assessment of suitability is the cornerstone for the development of ecotourism in nature reserves. This paper adopts the Delphi method to invite 30 experts to score and screen a series of indicators and then calculates the weight of each indicator through the hierarchical analysis method (AHP) to establish a comprehensive evaluation index system for the suitability of ecotourism development. The AHP method includes four constraints layers (tourism resources, socio-economic environment, ecological conditions, and tourism market), in addition to eleven element layers and thirty-eight indicators. It establishes overarching criteria for evaluating ecotourism suitability. Our research focuses on Dinghushan, Xilin Gol Grassland, Hongze Lake Wetland, and Jiuzhai valley, and the results are as follows: (1) Ecotourism suitability evaluation level is divided into five levels, level I (0 ≤ S < 30) ecotourism development suitability is the lowest, meaning an area is extremely unsuitable for ecotourism development. Level V (90 ≤ S < 100) has a very high ecotourism value, meaning an area is highly suitable for ecotourism development. (2) Jiuzhai valley scored the highest ecotourism suitability evaluation score of 87.63, and Xilingol Grassland scored the lowest score of 81.27. However, the composite scores of all the nature reserves were above 80, placing them at Suitability Level IV, and thereby indicating a high suitability for ecotourism development. (3) Divergences in ecotourism suitability emerge among various nature reserve types, with grassland and meadow reserves exhibiting lower suitability levels. Addressing this, a robust management and monitoring system is imperative, alongside intensified efforts in ecological restoration, vegetation protection, community engagement, education, awareness, and increased policy support and tourism capital investment. (4) The results of the expert questionnaire showed that the maximum weight of the indicators affecting the evaluation of the suitability of ecotourism was the satisfaction of tourists (0.120), and the minimum weight was the accommodation facilities (0.002), which illustrated the important role of tourists in the ecotourism development carried out in the nature reserve. (5) Through empirical analysis of numerous cases, the study validates the practicality and effectiveness of the index system and provides scientific guidelines for the suitability of existing nature reserves for further ecotourism development. This contributes to the research theory on the suitability evaluation of ecotourism development and serves as a valuable reference for the future ecotourism development of diverse nature reserves.

This paper evaluated the regional tourism competitiveness of 22 county-level administrative regions in Ningxia Hui Autonomous Region, China. The study analyzed the connotation of regional tourism competitiveness from the perspectives of resources and economic and environmental benefits, and established an evaluation index system for comprehensive competitiveness. The study used entropy weight TOPSIS to measure the level of tourism competitiveness in Ningxia, and used spatial association and hot and cold analysis to describe the spatial pattern of comprehensive tourism competitiveness in Ningxia. The results indicated that Lingwu City, Xixia District, and Huinong District have high comprehensive tourism competitiveness, while Jingyuan County, Haiyuan County, and Hongsipu District exhibit the weakest comprehensive competitiveness. The study also showed that regional economic development level competitiveness had the greatest impact on the comprehensive competitiveness of county tourism in Ningxia. The northern region and the southern region of Ningxia were the regions with high-high clusters and low-low clusters of tourism competitiveness, respectively. Based on the comprehensive evaluation results, the development level of tourism of Ningxia county was classified into four types: advanced development type, marginal dependence type, improved optimization type, and backward development type. Finally, the paper put forward targeted optimization suggestions in order to provide reference for Ningxia tourism functional zoning and high-quality development.

As a part of cultural landscapes, toponyms with abundant cultural connotations and a long history are valuable cultural heritage assets. Choronyms not only reflect natural and social phenomena but also help with relevant management and naming work. In order to explore the historical development sequence of choronymic cultural landscape evolution, we analyze the spatial–temporal pattern evolution, spatial–temporal variation, spatial association, and semantic evolution of choronymic cultural landscapes since the Qin dynasty. We adopt the sequent snapshot model and an event-based state amendment model to establish a spatio-temporal database. That can provide decision supports and theoretical reference for the sustainable development of toponymic landscapes. Results indicate the following: (1) Spatial distribution of toponym density has been different since the Qin dynasty. The cores of toponym density spread from the middle-lower reaches of the Yellow River to Yangtze Plain, Chengdu Plain, Pearl River Delta Plain. (2) Spatial distribution of choronyms is agglomerative since the Qin dynasty and uneven at national and provincial scales since the Yuan dynasty. Temporal distribution of toponyms at different levels is centralized. (3) Spatial agglomeration phenomena of toponyms are positively clustered in nine periods. The Ming dynasty presents the largest degree of spatial aggregation. (4) Words relevant to blessings, orientation, and hydrological features have high proportions in the top 20 words. (5) Spatial distribution of county-level choronyms named over the last 1000 years and “Millennium Ancient Counties” are unbalanced at national and provincial scales.