Social Media Big Data (SMBD) is widely used to serve the economic and social development of human beings. However, as a young research and practice field, the understanding of SMBD in academia is not enough and needs to be supplemented. This paper took Web of Science (WoS) core collection as the data source, and used traditional statistical methods and CiteSpace software to carry out the scientometrics analysis of SMBD, which showed the research status, hotspots and trends in this field. The results showed that: (1) More and more attention has been paid to SMBD research in academia, and the number of journals published has been increased in recent years, mainly in subjects such as Computer Science Engineering and Telecommunications. The results were published primarily in IEEE Access Sustainability and Future Generation Computer Systems the International Journal of eScience and so on; (2) In terms of contributions, China, the United States, the United Kingdom and other countries (regions) have published the most papers in SMBD, high-yield institutions also mainly from these countries (regions). There were already some excellent teams in the field, such as the Wanggen Wan team at Shanghai University and Haoran Xie team from City University of Hong Kong; (3) we studied the hotspots of SMBD in recent years, and realized the summary of the frontier of SMBD based on the keywords and co-citation literature, including the deep excavation and construction of social media technology, the reflection and concerns about the rapid development of social media, and the role of SMBD in solving human social development problems. These studies could provide values and references for SMBD researchers to understand the research status, hotspots and trends in this field.

The accurate identification of urban functional areas is of great significance for optimizing urban spatial structure, rationally allocating spatial elements, and promoting the sustainable development of the city. This paper proposes a method to precisely identify urban functional areas by coupling Open Street Map (OSM) and Point of Interest (POI) data. It takes the central urban area of Hangzhou as a case study to analyze the spatial distribution characteristics of the functional areas. The results show that: (1) The central urban areas of Hangzhou are divided into 21 functional areas (6 single functional areas, 14 mixed functional areas and 1 comprehensive functional area). (2) The single functional areas and the mixed functional areas show the geographical distribution characteristics of the looping stratification, which means “Core-periphery” differentiation is obvious, and the comprehensive functional area is relatively scattered. (3) The mixed degree of regional function with ecological function and production function is low while comprehensive functional areas are usually associated with higher potential and vitality. (4) The identification results are in great agreement with the actual situation of Hangzhou central urban area, and the method is feasible. Therefore, this paper can provide a reference for urban development planning and management.

Rapid urbanization development and construction has seriously threatened the connectivity of habitat patches in cities and hindered the construction of ecological networks in highly urbanized areas. Among them, China is affected by early compressed urbanization, and the broken ecological space in cities and towns has attracted the extensive interest of researchers. To avoid the subjective randomness and single analysis of ecological space in urbanization areas, this paper takes the central urban area of Wuhan as the main research area. It comprehensively evaluates the ecological network space by combining the MSPA-MCR model. The main conclusions are as follows: (1) Identifying the ecological landscape types with important ecological significance in the study area: Core (88.29%), Islet (0.25%), Perf (0.63%), Edge (9.74%), Loop (0.22%), and Bridge (0.14%). Through the dPC landscape index, seven important ecological sources south of the middle reaches of the Yangtze River were identified. (2) According to the comprehensive factors of natural and human factors constructed by the MCR model, the minimum cumulative ecological resistance surface was established, with an average value of 2.65, a maximum value of 4.70, and a minimum value of 1.00, showing a trend that the ecological resistance values in the central and eastern parts are lower than those in the western part. (3) According to the standard deviation ellipse, the distribution direction of NE–SW in ecological sources was analyzed. The ecological sources distributed in the north were less, and the spatial distribution was scattered on the whole. The strong global positive correlation and local spatial aggregation characteristics of ecological resistance surface were evaluated according to spatial autocorrelation. Based on the gravity model, the interaction intensity of ecological corridors between source areas was evaluated, and the importance of ecological corridor protection and restoration was quantitatively analyzed. The research results provide scientific and reasonable references and a basis for ecological planning of Wuhan central city.

Little is known about the seasonal heterogeneity of land surface temperature (LST) and the interaction relationship between potential drivers in Sichuan Basin, China. In this study, based on exploring the spatial heterogeneity of LST in Sichuan Basin, China, multi-source remote sensing data as potential drivers were selected and a Geo-detector model was applied to analyze the main drivers and the interactive relationship between drivers on LST during different seasons. The results showed that the high-temperature areas in Sichuan Basin in different seasons all appeared in the cities near the high mountains on the edge of the basin. This phenomenon was summarized as “sinking heat island” by us. From the driving factors, the biophysical parameters (DEM, SLOPE and NDVI) had the greatest impact on LST in each season, reaching the peak in the transition season. The climate parameters (WIND, HUM, PRE and TEM) and socioeconomic parameters (LIGHT, POP and ROAD) also had a certain impact on LST. The influence of a single landscape parameter (SHDI, PD, LPI, ED and LSI) on LST is limited. From the effect of factor interaction on LST, the interaction of biophysical parameters, climatic parameters and landscape parameters from summer to the transitional season was strengthened obviously, and it showed a downward trend in the winter; in contrast, the socioeconomic parameters showed the opposite characteristics, indicating that the interaction between human activities and other factors affected LST more obviously in the winter. The results of this study are not only valuable for understanding the spatial features of LST but also important for formulating mitigation strategies and sustainable development of urban heat island in Sichuan Basin.