Due to concerns about consequences to public health, the ecosystem, the natural landscape etc., the planning and construction of waste incineration plants always gives rise to a reaction and even protests from local communities. This study aims to investigate the determinants affecting public acceptance of waste incinerators. We contribute to the existing knowledge in the following ways: (1) this study undertook a qualitative analysis on community acceptance of nimby facilities in the context of China for the first time; (2) through qualitative interview analysis, we emphasize the impact of interactions among multiple factors regarding the acceptance of waste incinerators; (3) we finally construct a framework to systematically explain the formation mechanism of community acceptance of waste incineration plants. Employing in-depth interviews with 22 representative residents, the results indicate that from the perspective of externality, risk perception has a significant negative impact, whereas the effects of benefit perception are positive. In terms of interaction between government and citizen, both justice perception and political efficacy are positive. Social situational factors positively promote community acceptance. Lastly, the impact of individual cognition is mixed. This study has the potential to make a significant difference in better community governance and environment-friendly cities.

In this study, we create a high-resolution (1 km x 1 km) carbon emission spatially gridded dataset in Shanghai for 2010 to 2015 to help researchers understand the spatial pattern of urban CO₂ emissions and facilitate exploration of their driving forces. First, we conclude that high spatial agglomeration, CO₂ emissions centralized along the river and coastline, and a structure with three circular layers are the three notable temporal–spatial characteristics of Shanghai fossil fuel CO₂ emissions. Second, we find that large point sources are the leading factors that shaped the temporal–spatial characteristics of Shanghai CO₂ emission distributions. The changes of CO₂ emissions in each grid during 2010–2015 indicate that the energy-controlling policies of large point emission sources have had positive effects on CO₂ reduction since 2012. The changes suggest that targeted policies can have a disproportionate impact on urban emissions. Third, area sources bring more uncertainties to the forecasting of carbon emissions. We use the Geographical Detector method to identify these leading factors that influence CO₂ emissions emitted from area sources. We find that Shanghai’s circular layer structure, population density, and population activity intensity are the leading factors. This result implied that urban planning has a large impact on the distribution of urban CO₂ emissions. At last, we find that unbalanced development within the city will lead to different leading impact factors for each circular layer. Factors such as urban development intensity, traffic land, and industrial land have stronger power to determine CO₂ emissions in the areas outside the Outer Ring, while factors such as population density and population activity intensity have stronger impacts in the other two inner areas. This research demonstrates the potential utility of high-resolution carbon emission data to advance the integration of urban planning for the reduction of urban CO₂ emissions and provide information for policymakers to make targeted policies across different areas within the city.

China’s distinct rural revitalization process has attracted global attention due to its impressive speed, massive scale, and policy interventions. A relatively limited amount of research has been conducted on how rural transition characteristics and policy mechanisms are interrelated at the micro level. To fill this research gap, following the main research thread of dividing rural development stages, revealing transition characteristics and exploring policy mechanisms, this paper utilizes a participatory rural appraisal, a landscape metrics analysis, and in-depth interviews to analyze the spatial transition laws of Dayu Village. First, the results show that the village experienced three stages from 1990 to 2020: strict homestead control, village relocation, and land consolidation. Second, the village exhibits multidimensional transition characteristics. With a reduced rural settlement area, regular patch formation, and a dense interior subdivision of rural houses, the land use layout changed from homogeneous to multiple nests. As the industrial structure became more diversified, the villagers’ livelihoods became more differentiated. Inflows of tourists and migrants changed the population structure, causing social relations to become defamiliarized. Moreover, mechanism research finds that policy can promote rural settlement transition by allocating land resources and regulating village behavior. The policy’s scope expanded from a single settlement to the whole village, optimizing external forces, with village behavior effects acting as an internal force. The degree of matching between policy formulation and villagers’ needs is the key to promoting the transition of rural settlements. This research deepens the understanding of the transition laws of suburban villages in megacities in developing countries at the micro scale and provides a reference for land policies in similar villages.

This manuscript mainly focuses on the correlation between the spatial distribution of convenience stores and the distribution of urban spatial functions. We took 1217 FamilyMart convenience stores within the Shanghai outer ring area as the research objects and used the calculation method of kernel density estimation. The results show that the distribution of Shanghai FamilyMart stores is centered on the three central urban areas of Huangpu District, Jing’an District, and Xuhui District; the high-density areas of convenience stores partially overlap with the city’s main center, and some do not. The research shows that in areas with a high distribution density of convenience stores, the establishment of the convenience stores has a strong correlation with urban spatial functions, and these continence stores have formalized a network deeply integrated with the community. We believe that, in the future, with the development of small retail businesses, these can be transformed into public activity spaces through space transformation and design, which promotes the sustainable development of community interaction and traditional retail business, stimulating the sustainability of community vitality. The results of this study show that this concept has a feasible spatial basis, and the research method can also be applied to the study of other small retail commercial spaces.

Communities in urban space are the most basic living units. Community visual features directly reflect the local living quality and influence the perception of residents and visitors. The evaluation of the community visual features is of great significance to the space design under the guidance of urban landscape recognition and urban space perception. Based on the street view image data, this paper analyzes the composition of visual features in the community space scale by using the geographically weighted principal components analysis. GWPCA can not only reflect the global characteristics, but also analyze the local components, thus describing the visual features of the community in a comprehensive manner. The results show that: (1) community visual features have significant spatial heterogeneity at different statistical scales, and the spatial heterogeneity of community visual features can provide a basis for urban landscape planning and design; (2) the combination mode of dominant visual elements can reflect different community landscapes. The analysis of this paper further illustrates the effectiveness and application prospect of street view images in identifying the landscape composition mode of urban space from the medium-micro perspective. This conclusion is helpful for planners to learn the dominant visual features of the community through street view images, and, further, use the classification of elements of street view images to guide the planning and design of cityscape.