The availability of very high spatial resolution (VHR) remote sensing imagery provides unique opportunities to exploit meaningful change information in detail with object-oriented image analysis. This study investigated land cover (LC) changes in Shahu Lake of Wuhan using multi-temporal VHR aerial images in the years 1978, 1981, 1989, 1995, 2003, and 2011. A multi-resolution segmentation algorithm and CART (classification and regression trees) classifier were employed to perform highly accurate LC classification of the individual images, while a post-classification comparison method was used to detect changes. The experiments demonstrated that significant changes in LC occurred along with the rapid urbanization during 1978–2011. The dominant changes that took place in the study area were lake and vegetation shrinking, replaced by high density buildings and roads. The total area of Shahu Lake decreased from ~7.64 km² to ~3.60 km² during the past 33 years, where 52.91% of its original area was lost. The presented results also indicated that urban expansion and inadequate legislative protection are the main factors in Shahu Lake’s shrinking. The object-oriented change detection schema presented in this manuscript enables us to better understand the specific spatial changes of Shahu Lake, which can be used to make reasonable decisions for lake protection and urban development.

The intense development of urban–rural integration has brought about a constant increase in people’s demand for public culture. In particular, as the equalization of public cultural services is promoted, narrowing the gap between the services offered in urban and rural settings has gradually become the dominant orientation to promote urban–rural integration and enhance the rights and interests of the people. Starting from the principles of the new public service, this research conducted field interviews in Xuling Town, Anhui Province, China. The Zaltman metaphor elicitation technique (ZMET) was used to analyze the interview content, and five inferences about the construction of township public culture were drawn: (1) cultural facilities have a significant impact on township public cultural construction; (2) the role of cultural talents is essential but lack of talent is normal in townships; (3) carrying out cultural activities is the top priority of township public cultural construction; (4) cultural management is an indispensable auxiliary link but the management level is insufficient; (5) and the cultural activities of traditional festivals are particularly important. Moreover, on the basis of these five inferences, the fuzzy-set qualitative comparative analysis (fsQCA) method was used to analyze the survey data and verify the underlying problems around public cultural service effectiveness as well as resource allocation in township areas. Finally, countermeasures are proposed on how to narrow the gap, which are of reference significance for improving the quality of township public cultural services in the context of urban–rural integration and meeting the cultural needs of residents.

Millions of geo-tagged photos are becoming available due to the wide spread of photo-sharing websites, which provide valuable information to mine spatial patterns from human activities. In this study, we present a simple and fast density-based spatial clustering algorithm to detect popular scenic spots using geo-tagged photos collected from Flickr. In this algorithm, Gaussian kernel is applied to estimate local density of data points, and a decision graph is used to obtain cluster centers easily. More than 289,000 geo-tagged photos located in five typical cities of China are downloaded as case studies, and data pre-processing such as duplicate removing is performed to improve the quality of clustering result. Finally, popular tourist attractions of each sample city are successfully detected with this algorithm, and our result is useful for recommending some interesting destinations which might not be on the list of tourist website or mobile guide applications. The proposed solution is robust with respect to different distributions of photos, and it is efficient by comparing with other popular clustering approaches.

This study investigated the influence of cultural industry agglomeration on the energy carbon emission performance (CEP). Based on panel data from 276 cities in China, we used the Super-SBM model to measure the CEP. We then used the Tobit regression model to calculate the influence coefficient of cultural industry agglomeration and eight control variables on the CEP and analyzed the complex effects of cultural industry agglomeration on the CEP. The results showed that there is the phenomenon of “diseconomies of agglomeration” in cultural industry agglomeration, which cannot improve the CEP. For each unit of cultural industry agglomeration increase, the CEP decreases by 0.055; however, this phenomenon is not linear. Further research showed that the effects of cultural industry agglomeration showed a trend from good to inferior in the order of east, central, and west and did not improve with time. Finally, we used the panel quantile regression model and found that as the CEP levels rise, the negative impact of cultural industry agglomeration improves. Our research results show that strengthening the technical level to promote the upgrading of the cultural industry is the best way to achieve sustainable development. Governments at all levels should pay attention to the emission reduction potential of cultural industry agglomeration under high CEP levels and strengthen the benign agglomeration of the cultural industry.

The COVID-19 pandemic, with its risk of repeated fluctuations, has shifted the basis for decisions on tourism spending. Thus, it is crucial for the hospitality industry to understand the factors that influence accommodation consumption. Grounded in signaling theory, our empirical analysis is based on analyzing data from eLong on 7209 Chinese hotels using binary logistic regression and the ordinary least squares method (OLS). The main findings are as follows: (1) completeness of information, online hygiene rating and hygiene recommendation tags have a significant impact on hotel consumption; (2) online hygiene rating has a positively significant moderating effect on the relationship between information completeness and hotel sales; and (3) there is variability in the factors that influence the generation and growth of hotel sales. In addition, we discuss the role of online travel agencies (OTAs) and provide relevant advice for practitioners.