Actors and network in the marketization of rural collectively-owned commercial construction land (RCOCCL) in China: A pilot case of Langfa, Beijing

Zhao

et al. 2022

Land

Self Cite

Understanding land use change patterns of rural town settlements (RTSs) is crucial for rural and small-town planning; however, few studies have explored pattern mining approaches to RTS trajectory analysis. In this study, we adopted a novel method by building sequence alignment method (SAM) to detect representative trajectory clusters of land use change of 1158 RTSs in seven waves from 1980 to 2015 in Guangdong, China. The results suggest that there are 10 clusters of RTSs with varying trajectories of land use change, implying their differences in the development processes and underlying socioeconomic, demographical, and institutional factors. A spatial distribution map of RTSs shows that stable cultivated ecological and stable ecologically dominant RTSs are distributed in the northern, eastern, and western parts of Guangdong, whereas stable rural construction and stable mixed construction RTSs are mostly located around the provincial boundary. Notably, 73% of the RTSs that have undergone changes in land use types are located in the Pearl River Delta (PRD), including urbanized and agricultural upgraded RTSs. The analysis presented here summarizes the driving forces of the spatial evolution of RTSs, including the location, landforms, industries, and policy factors. This study provides dynamic policy implications to understand longitudinal and sequential spatial restructuring and regional coordinated development in the fast-growing PRD area.

Section: Discussion: Driving Forces Formulating Land Use Sequences Of...supporting

confidence: 91%

Extracting Land Use Change Patterns of Rural Town Settlements with Sequence Alignment Method

Xie

Zhao

et al. 2022

Land

Self Cite

“…While most existing studies neglect comparison of the mesoscale structures in WCNs, our findings demonstrate the importance of discussing mesoscale properties in comparative WCN studies because the mesoscale analysis can deepen our understanding on the characteristics of WCNs that are not easily observed in the microscale or macroscale analysis [14]. Moreover, the results demonstrate the advantage of the WSBM approach, in contrast to traditional city clustering methods, such as principal component analysis, hierarchical clustering, and community detection methods [19,[21][22][23][24][54][55][56]. WSBMs can avoid the trap of methodological determinism and extract multiple configurations of core-periphery or hybrid structures in different WCNs, the structure of which are difficult to be detected in other clustering methods.…”

Section: Discussionmentioning

confidence: 55%

Comparing World City Networks by Language: A Complex-Network Approach

Zhu

Zhao

2021

IJGI

Self Cite

City networks are multiplex and diverse rather than being regarded as part of a single universal model that is valid worldwide. This study contributes to the debate on multiple globalizations by distinguishing multiscale structures of world city networks (WCNs) reflected in the Internet webpage content in English, German, and French. Using big data sets from web crawling, we adopted a complex-network approach with both macroscale and mesoscale analyses to compare global and grouping properties in varying WCNs, by using novel methods such as the weighted stochastic block model (WSBM). The results suggest that at the macro scale, the rankings of city centralities vary across languages due to the uneven geographic distribution of languages and the variant levels of globalization of cities perceived in different languages. At the meso scale, the WSBMs infer different grouping patterns in the WCNs by language, and the specific roles of many world cities vary with language. The probability-based comparative analyses reveal that the English WCN looks more globalized, while the French and German worlds appear more territorial. Using the mesoscale structure detected in the English WCN to comprehend the city networks in other languages may be biased. These findings demonstrate the importance of scrutinizing multiplex WCNs in different cultures and languages as well as discussing mesoscale structures in comparative WCN studies.

“…Previous studies have shown that the occurrence of illegal land use is closely related to economic and social level or land marketization in China [35], but which economic activity has the greatest impact on economic activities? Which social activities have had the greatest impact?…”

Section: Data Descriptionmentioning

confidence: 99%

Spatial–Temporal Characteristics of Illegal Land Use and Its Driving Factors in China from 2004 to 2017

Wang

Yang

et al. 2021

IJERPH

The scientific analysis of spatial-temporal differentiation characteristics and driving factors of illegal land use is of great significance for the formulation and optimization of policies to control the emergence of illegal land use. This paper establishes two variable systems of illegal land use and its driving factors, defined the multidimensional characteristic variables of illegal land use and analyzes the relationships among them by the Pearson’s correlation coefficient; In addition, the spatial–temporal characteristics of each variable of illegal land use from 2004 to 2017 are described by the spatial autocorrelation analysis; Finally, based on the geographical detectors, the influence direction and degree of the factors of economic structure, social structure and land market behavior on the characteristics of different illegal land use are studied. The results show that the spatial agglomeration of different characteristics of illegal land use had been weakening from 2004 to 2017, but the rate of weakening was different, and L-L agglomeration changed between Xinjiang and other central-western provinces, H-H agglomeration changed in the coastal regions of the central-eastern of China, the level and ability of the central government and local governments to govern illegal land use is constantly improving on the whole; the compositional factors of economic development structure, social development structure, and land market behavior of driving factors had different influence in the degree, the location or the direction of different characteristics of illegal land use. According to the spatial–temporal characteristics and the differences of driving factors, managers can formulate differentiated illegal land use control policies, which will help to control the occurrence of illegal land use and help the settlement of illegal land use cases, and ultimately achieve sustainable development.