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Source–sink zones refer to aggregated adjacent origins/destinations with homogeneous trip flow characteristics. Current relevant studies mostly detect source–sink zones based on outflow/inflow volumes without considering trip routes. Nevertheless, trip routes detail individuals' journeys on road networks and give rise to relationships among human activities, road network structures, and land-use types. Therefore, this study developed a novel approach to delineate source–sink zones based on trip route aggregation on road networks. We first represented original trajectories using road segment sequences and applied the Latent Dirichlet Allocation (LDA) model to associate trajectories with route semantics. We then ran a hierarchical clustering operation to aggregate trajectories with similar route semantics. Finally, we adopted an adaptive multi-variable agglomeration strategy to associate the trajectory clusters with each traffic analysis zone to delineating source and sink zones, with a trajectory topic entropy defined as an indicator to analyze the dynamic impact between the road network and source–sink zones. We used taxi trajectories in Xiamen, China, to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This study focuses on analyzing the spatial distribution pattern and formation mechanisms of urban industrial clusters and aims to address the mismatch between industrial clusters and resource distribution. Firstly, the spatial distribution pattern of industrial clusters is analyzed using the kernel density estimation approach. Subsequently, a multi-layered model of interactive driving factors is constructed to analyze the functional types within the multi-layered network space. Lastly, a spatial weighted regression analysis model, considering the intensity of flow space, is developed to explore the intrinsic formation mechanisms of industrial agglomeration. The experimental results indicate the following: (1) There is a trend of industrial agglomeration in the Yangtze River Delta region, primarily concentrated in cities such as Shanghai, Nanjing, Hefei, Jinhua, and Taizhou. (2) The impact of spatial interaction factors on industrial agglomeration development is significant, and the analysis of interaction networks reflects the strength of interactive influencing factors to a certain extent. (3) The regression analysis model, which incorporates interactive information considering flow space intensity, better aligns with the study of the actual mechanisms behind industrial agglomeration in physical space. [ABSTRACT FROM AUTHOR]

Integrating a qualification of ecosystem services into a decision-making for conservation of a world heritage site at the landscape level remains a new challenge so far, especially for China that has abundant and valuable heritage sites with the development boom in China’s economy and society. In this paper, we took the Wuyishan Scenery District (WSD), a core part of the cultural and nature world heritage site Mount Wui, as our case study site to explore how a modeling of land use changes and spatial qualification of ecosystem services may facilitate local authorities’ decision-making. Here, a binary logistic regression was performed to quantify the impacts of selected driving factors on the distribution of land uses. Then, we adopted a CLUE-S model to spatially analyze changes in the landscape pattern and ecosystem services by simulating the following three scenarios: a historical trend, non-selective management of tea plantations, and selective management of tea plantations. The seven selected driving factors (elevation, aspect, slope, distance to the nearest road, distance to the closest river, distance to the closest settlement, and distance to the closest parking lot) were found to be associated with high prediction accuracy for all types of land use (ROC ≥ 0.857) other than non-matrix forests (ROC = 0.735) and tea plantations (ROC = 0.638). The results demonstrated that the third scenario entailing selective management of tea plantations offers a potential solution that can effectively mitigate expansion of tea plantations, while addressing serious issues relating to managerial needs at the landscape level. Implementing this measure would facilitate the protection of high quality tea plantations that form a crucial part of the world cultural and natural heritage site of Mount Wuyi. It can further help to restore Pinus massoniana matrix forests in WSD, and potentially increase the value of ecosystem services. Moreover, it could establish base-line conditions for future management and policy making in this site. [ABSTRACT FROM AUTHOR]