Chuntao Li

Non-built-up green areas are essential for preserving the ecological functions of cities and fostering sustainable growth. Focusing on Shanghai, we developed a comprehensive framework of driving forces that integrates socioeconomic, natural, policy, and financial indicators. To assess the spatial-temporal changes in regional green space configurations and their underlying mechanisms between 2000 and 2020, we utilized stepwise regression alongside Geographically Weighted Regression (GWR) techniques. The results show that regional green space exhibited a clear stage-dependent evolution, with the total area decreasing from 580.56 km² in 2000 to 506.43 km² in 2005 and then increasing continuously to 905.70 km² in 2020. Forest land consistently expanded and became the dominant land type, while wetland showed a “decrease–increase” pattern and grassland experienced an early decline followed by partial recovery. The primary elements driving these changes underwent substantial transformations over the study period. During the initial phase, socioeconomic variables, particularly real estate investments (β = −0.296), demonstrated pronounced adverse impacts. Conversely, post-2005, financial allocations for landscaping and policy interventions emerged as the main favorable drivers (β = 0.598). Furthermore, environmental aspects like NDVI and waterway density provided a continuous positive influence on green space enlargement. Certain socioeconomic indicators, notably population density, transitioned from exerting adverse impacts to having beneficial effects during the latter periods. The primary drivers demonstrated considerable spatial variation; socioeconomic impacts were largely localized in regions undergoing urban growth, whereas environmental and policy variables exerted broader and more consistent influences. Overall, these outcomes highlight a shift from a socioeconomic-dominated evolutionary process to one governed by a synergy of multiple factors. This offers a theoretical foundation for refining urban ecological strategies and harmonizing city expansion with ecological conservation.

Wetlands, as vital components of urban ecological infrastructure, provide essential ecosystem services. However, they face increasing risks of degradation and loss due to their vulnerability, environmental changes, and human activities. Therefore, effective restoration efforts are urgently needed. This study adopts a novel approach by considering the urban–rural gradient and integrates land use data, ecological parameters, and anthropogenic factors in Hefei City. Through morphological spatial pattern analysis, principal component analysis, and affinity propagation, this study identifies and analyzes urban–rural gradients. Using the optimal parameter geographic detector, the drivers of wetland changes from 1990 to 2020 are quantitatively assessed across different urban–rural gradients in Hefei. The findings indicate the following. (1) A persistent reduction in wetland expanse throughout the study duration, diminishing from 1274.56 km² in 1990 to 1119.37 km² in 2020, constituting a decrement of 12.17%. (2) Based on geographic detector outcomes, disparate driving forces underpin wetland dynamics across urban–rural gradients, with urban locales predominantly influenced by organic carbon and the proportion of impervious surface factors. Meanwhile, in agricultural and semi-ecological villages, silt is the primary factor, while ecological villages are primarily modulated by both silt and gross domestic product factors. Additionally, synergistic interactions manifest heightened explanatory power. This study elucidates the mechanistic underpinnings of wetland dynamics along urban–rural gradients, providing pivotal insights for developing targeted wetland restoration and conservation policies pertinent to the urban–rural developmental trajectory in Hefei City. Concurrently, it offers relevant recommendations for the multifaceted stewardship and sustainable development of wetlands in Hefei City in the foreseeable future.

Context Wetlands persistently diminish due to their own vulnerability, along with the combined impact of changes in the ecological surroundings and interference from anthropogenic interventions. Comprehending the driving mechanisms of wetland changes is crucial for wetland conservation. Objectives This research seeks to analyze the dynamic change characteristics of wetlands in Hefei. The objective is to establish a framework for urban-rural gradient analysis, exploring the impact of ecological surroundings and anthropogenic interventions factors, as well as their interactions, on wetland dynamics across different urban-rural gradient regions. Methods In this research, an urban-rural gradient was defined utilizing a clustering indicator derived from the composition and configuration of land use. The optimal parameters-based geographical detector (OPGD) performed a quantitative statistical analysis of the driving forces behind wetland changes under different urban–rural gradients. Results The results indicate that: (1) From 1990 to 2020, wetland area exhibited an ongoing diminishing tendency. (2) The urban–rural gradient can be classified into four categories: urban, agricultural village, semi-ecological village, and ecological village. (3) The driving factors of wetland changes vary across different types of urban–rural gradient regions. The most significant factors influencing wetland changes in each type of gradient region during different periods are the cropland proportion, impervious surface, OC, silt, and GDP. (4) Interactions among driving factors generally exhibit stronger explanatory power. Conclusions The research results reveal the driving mechanisms that underlie wetland dynamics in different urban–rural gradient regions. This information supports the development of more targeted wetland restoration and protection plans, contributing to improved synergy between urban and rural development and ecological conservation efforts.

In the process of the evolution of urban-rural spatial patterns, traditional village forms have been seriously eroded and destroyed, resulting in the gradual loss of garden feature elements and the blurring of spatial features. Facing these problems, accurate and efficient acquisition of relevant data becomes the key to traditional village conservation. We take the typical Huizhou Shuikou garden Tangmo village as an example and conduct a study on how to use UAV aerial images to extract spatial feature data. Firstly, the UAV was used to acquire aerial images of the study area through a predefined mission. Then, the image data are processed by using structure from motion (SfM) software to obtain digital surface model (DSM), digital orthophoto map (DOM), point cloud, and 3D model. Finally, the produced spatial data are applied to the spatial feature extraction analysis study. The results show the following: (1) the data produced by UAV aerial images have a horizontal accuracy of 0.034 m and a vertical accuracy of 0.039 m, which meet the requirements of traditional village spatial data collection. (2) The results of spatial feature elements and terrain feature extraction show that the 3D model and DSM can accurately extract and analyze the micro and macro spatial feature of traditional villages. (3) By using the cloth simulation filtering (CSF) to extract point clouds of buildings and streets, and after statistical analysis, we could quickly obtain their spatial features. Based on the spatial data obtained by using UAV, the study achieves the accurate collection of Tangmo DSM, DOM, 3D model, and spatial feature data and forms a method of data collection, processing and spatial feature extraction. The results of the study can provide a scientific basis for data collection on the spatial features of other cultural heritages and the conservation of traditional villages.

Rural revitalization places higher demands on the productive–living–ecological (P-L-E) spaces of towns and cities. It is necessary, therefore, to identify, evaluate, and optimize P-L-E spaces to better guide spatial planning. Existing studies typically evaluate a single space, lacking a comprehensive consideration of whole-area integration. This study, therefore, developed a coupled spatial/developmental suitability evaluation system for Feixi County, Anhui Province, China, combining spatial quality evaluation, a coupled coordination model, and future land-use simulation (FLUS) model. The spatial quality of Feixi County in 2010, 2015, and 2020 was obtained by applying the evaluation system to the spatial development pattern. The results were analyzed and verified using the landscape pattern index and development suitability evaluation. The results showed the following: (1) The coupling coordination degree of the region increased from 0.131 to 0.372, changing from low to moderate coordination. (2) Based on the FLUS model to better capture the uncertainty and stochastic basis of the development in the study area. The kappa coefficient and Figure of Merit (FoM) index of the land-use simulation accuracy verification index were 0.7647 and 0.0508, respectively, and the logistic regression ROC values were above 0.75, thus meeting accuracy requirements. This demonstrated that the simulation model—based on a factor library of the evaluation of resource and environmental carrying capacity and suitability for development and construction—could better reflect future land-use changes. (3) The simulation showed that under the baseline development scenario, the area’s spatial layout is too concentrated in terms of construction land, ignoring P-L-E coordination. Under the ecological optimization scenario, high-quality ecological space is ensured, but other types of spaces are lacking. Under the comprehensive guidance scenario, lagging ecological space is optimized and P-L-E spatial development is enhanced through aggregation, clustering, concentration and integration. This way, the spatial quantity structure and distribution form can meet P-L-E spatial development needs in Feixi County. In this study, on the basis of scientific assessment of the current P-L-E space, the FLUS model was applied to carry out a scenario simulation according to different objectives. Moreover, based on the construction of the coupling system of human–nature system, the driving factors were improved to enhance the prediction accuracy of the FLUS model. This study’s findings can help improve the scientificity, flexibility and management efficiency of Feixi County’s P-L-E spatial layout, thereby supporting its sustainable development.

In the context of the rapid development of China's urbanization economy and the current situation of 'hollow villages' era., how to effectively inherit and protect the Chinese traditional villages as cultural heritage is an important issue for China’s beautiful rural construction. The economic development of villages is based on the reasonable configuration of business, as an important carrier of the layout of the format，the architectural space and street space of the village are linked together for analysis and research, so as to achieve the 'win-win' effect of high-quality business form and the rational use and protection of historical building space.This paper takes Pingshan Village, a famous historical and cultural village in Yi county, China, as the research object, collects data through historical record, on-site investigations and interviews, and uses geographic information technology, point of interest combing and spatial syntax analysis to study the spatial characteristics of the current status of the Pingshan Village’s commercial concentrated water street. Besides, this paper makes quantitative analysis of the number of business forms in JiyangXi water street, spatial analysis of the commercial layout, and fixed-point analysis of the flow of people. With the results above, this paper takes correlation analysis on the results of analyzing spatial characteristics and the layout of business forms, draws up the advantages and disadvantages of the main commercial space layout of Pingshan Village as well as the optimization strategy, thereby reaches the design suggestions on the adjustment of the business forms in different spaces in traditional village planning.