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The modernization of territory spatial governance plays an essential role in realizing Chinese modernization. Towards the goal of high-quality development, promoting subject systems and professional learning provides fundamental and strategic support for the modernization of territory spatial governance. This paper focuses on the construction of the subject system of territory spatial governance from three aspects of the subject framework, the professional learning mode, and the team establishment strategy. We propose a life-cycle strategy for establishing the subject system of territory spatial governance in terms of the unified survey, spatial planning, utilization controlling, approval supervision, and construction of laws and regulations. We build a systematic talent training mode with the goal of generous theoretical foundation, method synthesis and excellent practical ability, and design a multi-field team construction strategy for territory spatial governance. In order to guarantee the modernization of land and space governance, the future works should focus on the synergetic development of subject development, talent training and team building. [ABSTRACT FROM AUTHOR]

The optimal allocation of land‐use is an important technical means to solve the contradiction be‐ tween supply and demand of land resources and to coordinate social and economic development with eco‐ logical protection, and it is also one of the key issues that need to be solved for the sustainable use of land resources. With the development of spatial simulation and intelligent optimization technology, the theoretical basis and methodological system of land‐use optimization are constantly updated. Based on bibliometrics analysis, this paper systematically summarized the driving theories and methodology of land‐use optimal al‐ location at home and abroad, focused on the application of spatial simulation models and intelligent optimization models in land‐use optimization problems, discussed and prospected the challenges and the future development of optimal land‐use allocation, and put forward that: The coupling drive of natural and human processes, spatial collaboration of multiple models, embedding big data knowledge mining methods, and the support of digital twin technology, should be the research direction of the next stage in the field of optimal land‐use allocation. [ABSTRACT FROM AUTHOR]

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Copyright of Geomatics & Information Science of Wuhan University is the property of Geomatics & Information Science of Wuhan University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Sustainable territorial spatial development faces severe challenges globally, especially the threats from rapid urbanization. It is important for territorial spatial planning in the new era to explore the principles, methodology and models for the territorial spatial optimization aiming sustainable urbanization from global and national perspectives. This paper rethink the spatial optimization for sustainable development by reviewing the literature on urbanization, spatial optimization and sustainable development. The results show that there is no readymade path for sustainable territorial spatial development, and sustainability should be the fundamental objective of territorial spatial optimization. Cases from the globe and China show that urban sprawl tends to make cities disperse, decline population density, and fall in a path dependency. Cities should be laid at the core of territorial spatial optimization. Chinese sustainable urbanization should be characterized by compact development, high-density, livable urban development, and low carbon. The concepts of sustainable urbanization oriented territorial spatial optimization include ecological protection, resource saving, intensive development, and green development, which forms the path of sustainable territorial spatial development. The modeling of territorial spatial optimization can be reconstructed from index system and quantification, setting of objectives, and constraint rules in a multi-objective collaborative optimization model. In this paper, we conclude that China has to build her own way of sustainable spatial development in accordance with the conditions of the nation, promoted by territorial spatial optimization with sustainable urbanization as a core. [ABSTRACT FROM AUTHOR]

With the development of China’s rail transit system, the transfer problem directly affects the convenience of hundreds of thousands of passengers day after day, and has become an important factor which affects the operation of public transportation systems. The problem of public transportation transfer should be “people-oriented” and analyzed from the time and space mode of passengers' transfer. Based on the smart card data (SCD) of Wuhan City in March 2015, this paper studies the time-space characteristics of passenger transfer, analyzes the current situation of rail transit development, and summarizes the transfor travel mode. The research results are as follows:① In the process of the development of rail transit in Wuhan, the imbalance of rail transit services has arisen and a single-center urban structure has emerged. ② The geographical characteristics of transfer behavior are related to the city’s own geographical pattern, and three factors which influence the transfer behavior are proposed. ③ Using intelligent bus card data, it can effectively identify the social behavior of passengers (transfer behavior) and the time and space mode of passengers traveling. This paper analyzes the spatiotemporal patterns of travel behaviors such as transfer behavior and urban planning and urban space utilization from the perspective of “people-oriented” based on the analysis of big data. [ABSTRACT FROM AUTHOR]

Community detection is an important topic in spatial network researches. It can discover interesting spatial patterns, which help understand the spatial structures hidden in the networks. However, community detection in spatial networks is more difficult than traditional networks. Since it has to consider some other spatial correlations, e.g., spatial contiguity, geographic distance. This paper proposes a new spatial community detection algorithm-geographial weighted central node distance based Louvain method (GND-Louvain). It uses a geographical and network dual-constrain to measure the distance and to calculate the distances decay effects between spatial nodes and meta-communities. It also extends the famous fast unfolding community detection algorithm-Louvain, by using the distance-modularity. In addition, a merge order is defined during the GND-Louvain's optimization process to get high quality and stable community results. Comparative experiments are designed on five different community detection methods based on five different spatial constraints, which are ① no distance constraint, ② spatial contiguity edge constraint, ③ geometry median center distance, ④ degree center distance, and ⑤ degree weighted geometry median center distance. The experimental data comes from the Chinese railway lines. And results prove that the newly defined GND-Louvain algorithm can produce more accurate spatial communities than others. And the merge orders also ensure the high quality and stable results. [ABSTRACT FROM AUTHOR]

Human mobility is a cross-disciplinary research hotspot which reflects the complex man-land relationship. Understandings of the intra-urban employment population flow, as an important part of urban group mobility, are crucial for urban planning and traffic forecasting. The common use of location-awareness devices such as mobile phones enables to capture human behavioral data for analyzing intra-urban employment flow. In this paper, we attempt to characterize the employment flow and interpret its formation mechanism using mobile phone data recorded during 30 days (from June 1, 2016 to June 30, 2016) in Wuhan. Considering the spatial distribution of cellular base stations, we divide our study area into grids sized 250 m×250 m. We then adopt approaches to extract daily individual mobility information by identifying positon and duration of stagnations. Next, we propose several rules to infer in which grids people work and reside from individual mobility information we extracted and estimate the job/housing distribution as well as the employment flows between sub-districts. We then build the employment flows network, and methods such as network centrality analysis, network density analysis and community detection are applied to discover the pattern and characteristic of employment flows. Finally, we examine the influence of employment potential, traffic accessibility, spatial proximity, cultural difference and major industry on the size of employment flow between sub-districts and interpret its formation mechanism using logistic regression. The results firstly show that the number of intra-urban employment flow in Wuhan is unevenly distributed as large amounts of employment flow are concentrated in a few sub-districts. Secondly, the employment flows mainly occur in the sub-districts with good spatial proximity. It shows the distribution of the outflow employments decrease gradually as distance and accessibility time increase, and forms several employment communities (such as Hanyang, Wuchang North, Wuchang South, et al.) in the influence of geographical barriers and cultural differences. Thirdly, the employment potential measured by the resident population of the origin sub-districts and the working population of the destination sub-districts is the most important factor to increase the size of employment flow. Rather, cultural differences and poor accessibility hinder employment flow. The result also verifies that differences in major industries affect the employment flow, that commerce and education have a negative effect on the outflow of employments, but the industry attracts employments. [ABSTRACT FROM AUTHOR]