The historic environmental vulnerability of traditional villages (HEVTVs) is distinctly differentiated; however, the priority of relevant emergency management practices still lacks appropriate evaluation. This study proposes a new assessment system to quantify HEVTVs at the district level and an extended analysis of the influencing factors of adaptive capacity. This provides a basis to classify the emergency management of villages under geological hazard risks. Based on the coupled human–environment system, this research designed the assessment with three criteria, six factors, and 13 indexes from the perspective of HEVTVs. Furthermore, a demonstration test was conducted of 148 traditional villages in Lishui, China. The results showed that 64.19% of HEVTVs in Lishui were moderate or above, and that villages with very high vulnerability were mainly distributed at mid-elevation of mountains with strongly sloping terrain. In contrast, low-vulnerability villages were generally on plains at low altitudes. Furthermore, three high-vulnerability clustering groups were identified as critical improvement targets for which special zoning strategies should be proposed. Five influencing factors were found to be strongly related to the adaptive capacity, indicating a spatial variation of the impact intensity. This could be applied to streamline vulnerability optimization strategies according to local conditions.

Land use in traditional village clustering areas often exhibits slight dynamic changes; however, significant hidden ecological hazards may be present in local settlements. There is still a lack of dynamic ecological risk assessments for the corresponding classification-based prevention strategies and landscape ecosystem attributes’ enhancement. Based on the land-use changes, this study integrated the ecosystem structure and function to explore the characteristics of the landscape ecological risk in traditional village clustering areas. The clustering area of 24 national traditional villages in Songyang County of Lishui City in Zhejiang Province, China, served as the study region to evaluate and analyze the changes in the landscape ecological risk from 2010 to 2019. The results showed that the land-use transitions were subtle but dominated by changes from forest cultivated land, posing high risk and medium—high risk increased slowly in size. Additionally, significantly increased risks were located mainly in the boundary area of the five villages. Moreover, 22 settlements were found in the sensitive area with increased risks less than 600 m away. This assessment will provide a basis for traditional villages’ risk prevention and ecosystem protection.

In developing countries, the phenomena of rural depopulation have been an intense continuing, which have become a major bottleneck for the sustainable revitalization of traditional villages. However, the factors influencing the spatial disparity of population hollowing (SDPH) in traditional villages within a prefecture-level city have not been fully quantitatively researched. Based on the factors that influence general villages, this study incorporated historical and cultural factors related to traditional village characteristics to construct a targeted influencing factor index system and then identified the key factors by applying the geo-detector method. With the percentage of resident population (PRP) used as a metric, this study examined Lishui, one of China’s traditional village agglomeration regions, as an example to explore SDPH in traditional villages. The results of this study were revealed in the following. (1) The average PRP value in traditional villages in Lishui was 0.68, with clear spatial disparities between the northern region (0.73) and the southern region (0.57). (2) The factors driving the SDPH included both natural and anthropogenic factors; of these, altitude, the number of public facilities, and the number of communication base stations were the most significant influencing factors. In contrast, historical and cultural factors have relatively low impacts. (3) The interaction relationships of pair factors were often enhanced on a bivariate basis, with the highest enhanced impact occurring from the interaction of two variables: the degree of intangible cultural inheritance and altitude. (4) The intervals of the variables leading to the hollowing of the population above a moderate level can be detected. This method can effectively analyze the factors influencing SDPH in traditional villages; can help reveal the interaction impact of pair factors; and can help identify the factors’ risk intervals.