Ecological risk assessment is an important part of the sustainable development of World Heritage. The Ming Great Wall Heritage (MGWH) plays an important role in World Heritage conservation as a representative of large linear heritage, yet its ecological risks have not received much attention. This study assessed the ecological risk of MGWH based on simultaneous consideration of spatial heterogeneity and autocorrelation of geographic factors, and four protection zones were further identified from the perspective of preservation status and risk by using GeoDetector, principal component analysis and bivariate autocorrelation. The results showed that there were statistically significant differences in the preservation status of MGWH at different elevations. Based on this assessed ecological risk, it was found that 63.49% of MGWH grids were in the low to medium risk, while the highest risk areas (16.61%) were mainly concentrated in lower (200–500 m) and medium (500–1000 m) elevation. As elevation increased, the dominant factor of ecological risk shifted from human factors to natural factors and the main ecological risk showed a trend of increasing and then decreasing with increasing elevation. In addition, four types of risk protection zones (i.e., Protection—Restricted, Restoration—Moderate exploited, Restoration—Restricted and Protection—Moderate exploited) and policy suggestions were identified in this study from the perspectives of conservation, restoration and development, respectively. Future ecological protection of the MGWH should be based on the principle of “cultural heritage protection first”, with restricted development and use (e.g., tourism and education) and enhanced ecological restoration and environmental management of the surrounding area. This study provides references for the risk assessment of the cultural heritage at a large spatial scale, which is conducive to the maintenance and improvement of heritage value.

The visit paths, dwell time, and taking pictures are all variables of great significance to our understanding of tourists’ spatio-temporal behavior. Does having a large number of visitors mean that tourists are interested in a tourist location? What is the relationship between the dwell time and taking pictures? Are there differences in tourist behavior in different seasons? These issues are of great significance to tourism research but they have not been rigorously analyzed yet. This paper aims to understand the relationship between tourists’ visit path, dwell time, and taking pictures, and test whether there are differences in tourist behavior in different seasons. We used open global positioning systems (GPS) trajectory data at Yuanmingyuan Park from January 2014 to August 2020. Using Python and ArcGIS tools, we found hot spots of tourist passing, hot spots of tourist gathering, high average dwell time areas, and tourist interest areas. It is further found that: (1) passenger flow strongly explains dwell time, while the correlation between passenger flow and average dwell time is weak. (2) There was a close relationship between tourists’ stay and photo-taking behavior, which provided a theoretical basis for defining tourist photo behavior as tourists’ stay behavior. (3) Seasons did not significantly affect tourist behavior in Yuanmingyuan Park. This study presents a grid-based open GPS trajectory data processing framework that clarified the potential of an open GPS trajectory in tourist behavior research. Furthermore, our study explored the relationship between essential indicators and found that there is a strong consistency in tourist behavior across seasons.

In this study, the spatial-temporal distribution pattern and tourism utilization potential of national ICH are analyzed based on GIS technology in the Yellow River Basin. The results show that: (1) The national ICH of the Yellow River Basin is distributed in an aggregated spatial pattern with the characteristic of “one belt and two cores”. The cities in Shanxi, Henan and Shandong provinces constitute the high-density and sub-high-density continuous belts. Haidong and Chengdu are the high-density and sub-high-density core areas, respectively. (2) The five batches of national ICH present a temporal distribution pattern of “Northeast to Southwest”. The distribution scope of national ICH in medium and high-density areas expands gradually and finally tends to be balanced. (3) For the single-factor evaluation of tourism utilization potential, there is an obvious gap in the evaluation grade among the cities. However, for the comprehensive evaluation of tourism utilization potential, there are 72 cities with an evaluation grade of three or above, accounting for 63%. This indicates that the tourism utilization potential of the national ICH in this basin is great. (4) The national ICH tourism in this basin can be developed from two aspects: regional differential development and regional linkage development.