Comprehensively understanding the factors influencing crime is a prerequisite for preventing and combating crime. Although some studies have investigated the relationship between environmental factors and property crime, the interaction between factors was not fully considered in these studies, and the explanation of complex factors may be insufficient. This paper explored the influence of environmental factors on property crime using factor regression and factor interaction based on data from the central city of Lanzhou, China. Our findings showed that: (1) The distribution of crime cases showed the pattern of a local multi-center. Shop density, hotel density, entertainment density and house price were the four dominant environmental drivers of property crime; (2) The relationship between the light intensity and property crime had different correlation explanations in temporal projection and spatial projection. There was a normal distribution curve between the number of property crimes and the Price-to-Earnings Ratio (PE Ratio) of the community house price; and (3) The results of the factor interaction indicated that the effect of all factors on crime showed a two-factor enhancement. As an important catalyst, shop density had the strongest interaction with other factors. Shop density gradient influenced the degree of interpretation of spatial heterogeneity of property crime.

Recent rapid population growth and increasing urbanisation have led to fast vertical developments in urban areas. Therefore, in the context of the dynamic property market, factors related to the third dimension (3D) need to be considered. Current hedonic price modelling (HPM) studies have little explicit consideration for the third dimension, which may have a significant influence on modelling property values in complex urban environments. Therefore, our research aims to narrow the cognitive gap of the missing third dimension by assessing both 2D and 3D HPM and identifying important 3D factors for spatial analysis and visualisation in the selected study area, Xi’an, China. The statistical methods we used for 2D HPM are ordinary least squares (OLS) and geographically weighted regression (GWR). In 2D HPM, they both have very low R² (0.111 in OLS and 0.217 in GWR), showing a very limited generalisation potential. However, a significant improvement is observed when adding 3D factors, namely view quality, sky view factor (SVF), sunlight and property orientation. The obtained higher R² (0.414) shows the importance of the third dimension or—3D factors for HPM. Our findings demonstrate the necessity to include such factors into HPM and to develop 3D models with a higher level of details (LoD) to serve more purposes such as fair property taxation.

In the future, the pursuit of high-quality economic development and a focus on ecological environmental protection in China will inevitably result in significant conflicts between land use and ecological land use. Land use conflicts primarily occur in peri-urban areas characterized by prominent economic development and urban agglomeration. As a municipality situated in the Qin-Ba mountainous region, Ankang has been promoting ecological preservation for a span of two decades. The allocation of construction areas primarily focuses on the proximity of watersheds, while the northern and southern regions are predominantly characterized by mountainous and hilly terrain, thus exhibiting distinct regional attributes. Previous studies have mainly focused on analyzing the effects of land use on habitat quality during intense urbanization, with fewer studies focusing on integrating eco-regions with urbanization to assess changes in habitat quality. However, it is important to recognize that land pressure encompasses economic, ecological, and social aspects. Additionally, it aims to provide insights for the harmonious development of land use in eco-region-oriented cities. Using the SSPs-RCPs scenarios provided by the sixth phase of the Coupled Model Intercomparison Project (CMIP6), this paper employs a system analysis method, the emerging Patch-Generating Land Use Simulation model (PLUS) model, Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, and Land Use Conflict Measurement model to dynamically simulate the future habitat quality and spatial conflict patterns of land use in Ankang City. The study explores the spatial coupling effect of both factors under different scenarios. The results indicate the following: (1) The overall development trend reveals an intensification of land use conflicts and a decrease in habitat quality. The expansion rate of construction land is increasing and exhibiting aggregation, while agricultural land area is expanding, and forest land area is continuously decreasing. (2) Land use intensity exhibits a significant positive correlation with land conflict levels, while land conflict levels demonstrate a significant negative correlation with habitat quality. (3) Under different future shared socioeconomic path scenarios, land use intensity, and land conflict levels follow the order of SSP585 (high forcing scenario), SSP370 (medium to high forcing scenario), SSP245 (medium forcing scenario), and SSP126 (low forcing scenario), with intensity and conflict decreasing accordingly. These findings suggest that land use has had some impact on the ecological environment, with indications of habitat degradation. Even in Ankang, where ecological development is highly valued, the city will gradually face conflicts between ecological protection and economic development in future scenarios. The city already has the environment at heart, so it will be worse in cities where the priority is economic development. Therefore, it is crucial to allocate sufficient space for economic development while simultaneously prioritizing ecological protection. The results of the study can provide a reference for analyzing the trade-offs between land development and habitat protection in eco-mountainous cities and for eco-cities to avoid falling into the conflict dilemma of economic cities.

China has experienced fast urbanization with a growing urban population, which has inevitably led to the adoption of a vertical housing style with high-rise buildings. However, how people subjectively perceive the vertical dimension (3D) in the property market is neither adequately documented nor well understood. The 3D perception helps us to understand a myriad of social and psychological effects of living in high-rise buildings. We organized and conducted semi-structured expert interviews, focus groups, and the circulation and compilation of questionnaires in Xi’an, China, to investigate how different stakeholders in the property market perceive 3D. The results show that: (1) real estate developers do not adjust property prices for specific 3D factors, and the local government does not consider 3D in housing policies; (2) the current status of 3D modeling in Xi’an is still in the embryonic state; (3) 3D factors are highly valued by buyers but not well-understood by real estate developers and local government. In addition, 3D factors score higher than horizontal (2D) factors (1.12 to 0.88). Gender and age groups do not influence housing preferences concerning 2D and 3D factors. These findings provide valuable insights for real estate developers concerning pricing policies and the local government concerning housing policies. In the future, 3D perceptions and factors should be prioritized in order to improve urban infrastructure and ensure the increased availability of, and fair public access to welfare related to 3D in urban areas.

An assessment of rural development and its driving factors can effectively reflect the characteristics and transformation of rural areas and provide important information for the formulation and implementation of rural development strategies. Taking Northeast China as study area, a rural development index framework was constructed from three dimensions, i.e., basic rural conditions, the state of agricultural development, and farmers’ living standards, based on which the rural development level of each city in Northeast China for the years 2000, 2005, 2010, 2015 and 2020 was assessed. Then, an exploratory spatial data analysis was used to explore the spatial and temporal variations in the rural development level in Northeast China during the period 2000–2020. The driving factors were also analyzed using a geographically and temporally weighted regression model. The results showed that the rural development level showed an increasing trend overall, with a spatial pattern of “high in the central, low in the east and west” in most periods. The degree of spatial agglomeration of the rural development level also showed a strengthening trend overall. The hots spots of rural development were mainly distributed in the Southern and Northern regions, while the cold spots were mostly concentrated in the central, eastern and western regions. Urbanization processes, elevation, annual precipitation and other natural factors have weakened the level of rural development to a certain extent, while agricultural production upgrading, an increase in the general public budget expenditure per capita and the sound financial situation of the government can promote rural development in Northeast China. The effects of the natural environment and local economic conditions on rural development were different in different regions. To improve rural development in the future, we should scientifically grasp the basic conditions, such as rural resource endowment, location conditions, agricultural technology, policies, investment and other external conditions, and formulate regional rural development strategies according to local conditions and in light of local rural characteristics.