Search Results (3)

The land problem is the key to the implementation of the rural revitalization strategy, and the land suitability evaluation is the basis for the renovation and classification of idle rural residential areas. Taking Yuzhong County in the Loess Hilly region of Longzhong, China as the research area, this study constructed an idle residential identification matrix by combining the evaluation results of ecological protection suitability, agricultural production suitability, and construction and development suitability, and realizing renovation zoning of rural residents through the advantage type identification method. The results show that: (1) The waste in rural residential is serious, and there are significant phenomena of “one household with two houses” and “one household with multiple houses.” The renovation potential of 1700 idle rural residential patches is 1.18 km². (2) The spatial differences in the suitability of rural residents in Yuzhong County are significant, and through the rational guidance and planning layout of rural residential renovation, it can provide an important decision-making basis for the rational utilization of rural residents and national land–space planning. (3) The renovation of rural residential should be guided by national land–space planning; make a solid plan for the renovation of rural residential areas; formulate a scientific plan for the renovation, relocation, and reuse of rural “hollow houses”; stimulate the vitality of rural land resources; and promote the revitalization of the countryside and the improvement of the rural living environment. Full article

As a crucial part of China’s development strategy, the redevelopment of urban villages and the redevelopment willingness of villagers have attracted considerable scholarly interest. However, the literature to date has neglected the effect of the geographical location of urban villages on the redevelopment willingness of villagers. The purpose of this study is to examine the influential factors of the redevelopment willingness of urban villagers, especially with regard to geographical differences and their effects. Based on prospect theory and 1083 questionnaires administered in 45 selected urban villages in Guangzhou, we use the ordinal logistic regression model to explore the influential factors behind villagers’ redevelopment willingness in inner villages (<15 km from the city center), urban fringe villages (15–40 km from the city center), and suburban villages (>40 km from the city center). The results show that in inner villages the confirmation of residential land rights can significantly increase redevelopment willingness, but in urban fringe villages the number of stories in dwelling houses significantly decreases the willingness. Further, a high level of villagers’ trust in the government, market enterprises, and the village collective each has a significant positive impact on the redevelopment willingness of villagers in urban fringe villages. However, only trust in the government and market enterprises have significant positive impacts on redevelopment willingness in the inner villages and only trust in the village collective is significant in this regard in suburban villages. The effects of geographical differences imply that China’s redevelopment policy should be applied in a differentiated way based on the geographical locations of urban villages. Full article

China’s rural population has declined markedly with the acceleration of urbanization and industrialization, but the area under rural homesteads has continued to expand. Proper rural land use and management require large-scale, efficient, and low-cost rural residential surveys; however, such surveys are time-consuming and difficult to accomplish. Unmanned aerial vehicle (UAV) technology coupled with a deep learning architecture and 3D modelling can provide a potential alternative to traditional surveys for gathering rural homestead information. In this study, a method to estimate the village-level homestead area, a 3D-based building height model (BHM), and the number of building floors based on UAV imagery and the U-net algorithm was developed, and the respective estimation accuracies were found to be 0.92, 0.99, and 0.89. This method is rapid and inexpensive compared to the traditional time-consuming and costly household surveys, and, thus, it is of great significance to the ongoing use and management of rural homestead information, especially with regards to the confirmation of homestead property rights in China. Further, the proposed combination of UAV imagery and U-net technology may have a broader application in rural household surveys, as it can provide more information for decision-makers to grasp the current state of the rural socio-economic environment. Full article