Roads are the link between geographic space and human socio-economic activities, promoting local economic development, and simultaneously causing various negative effects, such as segmentation, interference, destruction, degradation, and pollution. In China, the construction of roads is rapid, which might affect wildlife movement, landscape pattern, and land use change, thereby, affecting the conservation of heritage sites. In the present study, the minimum cumulative resistance model, along with geographic information system technology, was adopted to compute the ecological corridor for wildlife movement between the source patches and to analyze ecological corridor changes under two conditions (road presence/absence) at two time points in Kanas, nominated as a World Natural Heritage site. The relationships between the ecological corridor changes and various factors, including the cutting index of the ‘road-effect zones’, terrain, and road geometric characteristics, were examined using the geographical detector model to identify the influencing factors and mechanisms of the corridor changes, in order to rationally simulate the potential ecological corridors. In addition, the detached and fragmented ecological patches can be connected to effectively protect the biodiversity, biological habitats, and species, which are important means to achieve regional sustainable development and ecological construction.

Monitoring the ecosystem health for world natural heritage sites is essential for protecting them and benefits the formulation of more targeted protection policies. This study used Bayanbulak world natural heritage site as a case, established a framework for assessing the ecosystem health through remote sensing based on the parameters of ecosystem vigour, organization, resilience, and services. Then, we verified the obtained results through field sampling. The results show that the ecosystem health in the overall study area had declined over time, however, the health within the property zone remained at high levels and stable. The area proportion of low health was low and primarily distributed in the buffer zone. Thus, in general, the ecosystem in the study area was healthy. Besides, the ecosystem health exhibited distinct spatial agglomeration characteristics, and the degree of agglomeration enhanced over time. In addition, the field vegetation samplings were consistent with the changes in the ecosystem health levels, therefore, the result of RS monitoring of ecosystem health were credible. Thus, this study provides a scientific basis for heritage managers to formulate suitable ecological protection policies and should aid further research on the ecological monitoring of heritage sites.

Ecological environment assessment would be helpful for a rapid and systematic understanding of ecological status and would contribute to formulate appropriate strategies for the sustainability of heritage sites. A procedure based on spatial principle component analysis was employed to measure the ecological status in Bayinbuluke; exploratory spatial data analysis and geo-detector model were introduced to assess the spatio-temporal distribution characteristics and detect the driving factors of the ecological environment. Five results are presented: (1) During 2007–2018, the average values of moisture, greenness, and heat increased by 51.72%, 23.10%, and 4.99% respectively, and the average values of dryness decreased by 56.70%. However, the fluctuation of each indicator increased. (2) The ecological environment of Bayinbuluke was improved from 2007 to 2018, and presented a distribution pattern that the heritage site was better than the buffer zone, and the southeast area was better than the northwest area. (3) The ecological environment presented a significant spatial clustering characteristic, and four types of spatial associations were proposed for assessing spatial dependence among the samples. (4) Elevation, protection partition, temperature, river, road, tourism, precipitation, community resident, and slope were statistically significant with respect to the changes in ecological status, and the interaction of any two factors was higher than the effect of one factor alone. (5) The remote-sensing ecological index (RSEI) could reflect the vegetation growth to a certain extent, but has limited ability to respond to species structure. Overall, the framework presented in this paper realized a visual and measurable approach for a detailed monitoring of the ecological environment and provided valuable information for the protection and management of heritage sites.

The protection of World Natural Heritage Sites (WNHSs) has become a global undertaking, wherein Outstanding Universal Value (OUV) is an important aspect of heritage protection. Focusing on the protection of the aesthetic and bioecological values of Bogda (one component of Xinjiang Tianshan WNHS), 17 indicators are selected to construct a Heritage Value Protection Significance Index (HVPSI) and a related Heritage Value Protection Index (HVI). From these, the level of OUV conservation is obtained according to the five aspects of integrity, vulnerability, sensitivity, degree of human impact and environmental factors. The spatial autocorrelation analysis method was applied to the OUV conservation indices to comprehensively reflect the spatial-pattern characteristics of the heritage value in the study area. According to the spatial-division of the HVPSI, the plant community composition and diversity characteristics of different HVPSI zones are analyzed by a field survey (July 2018 and 2019). To verify the rationality of space partition and identify the OUV elements in each HVPSI district, a spatial-econometric model is then used to explore the relationship among HVPSI, HVI and community diversity. This study provides a scientific basis for management of heritage sites and a theoretical basis for further investigation into heritage site indicators.