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Urban informal settlements (UISs) are densely populated and poorly developed residential areas in urban areas. The mapping of UISs using remote sensing is crucial for urban planning and management. However, the large-scale extraction of UISs is impeded by the labor-intensive task of collecting numerous training samples and the lack of automatic and effective city partition. To overcome these challenges, we proposed a large-scale extraction framework for UISs based on semantic segmentation of highresolution remote sensing images. Utilizing Deeplab V3 Plus as the foundational extraction model, the proposed framework introduces fast sample collection based on GLCM features. Besides, an automatic city partition approach combined with clustering and fine-tuning was proposed to enhance the performance on extracting a specific category of UISs. The results of the case study conducted in 36 major Chinese cities show that the proposed framework achieved good performance, with an overall F1 score of 85.76%. Furthermore, comparative assessments were performed to demonstrate the effectiveness of automatic city partition. The proposed framework offers a practical approach for the largescale extraction of UISs, which holds great significance for sustainable development, poverty estimation, infrastructure construction, and urban planning. [ABSTRACT FROM AUTHOR]

The unprecedented urbanization in China has dramatically changed the urban spatial structure of cities. With the proliferation of individual-level geospatial big data, previous studies have widely used the network abstraction model to reveal the underlying urban spatial structure. However, the construction of network abstraction models primarily focuses on the topology of the road network without considering individual travel flows along with the road networks. Individual travel flows reflect the urban dynamics, which can further help understand the underlying spatial structure. This study therefore aims to reveal the intra-urban hierarchical spatial structure by integrating the road network abstraction model and individual travel flows. To achieve this goal, we 1) quantify the spatial interaction relatedness of road segments based on the Word2Vec model using large volumes of taxi trip data, then 2) characterize the road abstraction network model according to the identified spatial interaction relatedness, and 3) implement a community detection algorithm to reveal sub-regions of a city. Our results reveal three levels of hierarchical spatial structures in the Wuhan metropolitan area. This study provides a data-driven approach to the investigation of urban spatial structure via identifying traffic interaction patterns on the road network, offering insights to urban planning practice and transportation management. [ABSTRACT FROM AUTHOR]

Urban population size dynamic adjustment has been widely studied for a long time; however, the dynamic adjustment at the urban hierarchy level remains unknown. This study utilises China's urban population data to investigate the dynamic adjustment. Specifically, we utilise methods of the Gini coefficient, linear regression, and coefficients of Spearman, and Moran's I to explore the dynamic adjustment tendency, adjustment rate and correlation of urban population size distribution of different urban hierarchies and groups of different urban hierarchies. We find that the urban population size spatial distribution is gradually even within the same urban hierarchy. The adjustment rate to be even of Megacity II is the highest, and Megacity I is the bottom. We also find the population size spatial distribution of the whole urban system is gradually uneven. We explore the dynamic process by sorting urban hierarchies into six groups. Furthermore, we find there is a complex correlation between different urban hierarchies and global spatial correlation among China cities. These results are valuable as references for Chinese policy-makers and practitioners and will enable them to adopt sustainable land use and urban population management measures. The study outcomes will also benefit future studies on spatial population size distribution in international communities. [ABSTRACT FROM AUTHOR]

Based on the technology of RS & GIS and the remote sensing images of Jixi City in 1993, 2003 and 2015, this study analyzes quantitatively the temporal and spatial evolution characters of landscape pattern in the downtown area of Jixi City in China in the past 22 years. The research results show that the area of mine land, farmland and construction land increased greatly from 1993 to 2015. As an important part of the urban natural ecosystem, the area of water area, forest and grassland are also decreasing year by year. In the past 22 years, due to the impact of human activities such as coal resources development, the coal mine land in the central urban area is distributed in the agricultural farming area and the edge zone with different landscape types. On the whole, the fragmentation degree and diversity of regional landscape are increasing, and human activities have a significant impact on the urban landscape pattern of Jixi City. This paper attempts to explore the general law of landscape pattern change under the influence of human activities in mining cities and to provide a reference for urban land use planning and scientific decision-making of relevant government departments. [ABSTRACT FROM AUTHOR]

With the pursuit for global competitiveness and economic growth, Chinese cities have recorded massive urban land expansion. This article examines the effects of development policies and economic restructuring on urban land expansion in China through a case study of Nanjing, representing the rapidly growing and globalizing coastal cities in China. Wei investigate the development process and changing contents of government policies, and analyze development zones and key projects as privileged, trait making, and even path-breaking elements of the development process. We highlight the transition and paradox of the Chinese state in the urban development process, and the broad contexts underlying urban land expansion in Chinese cities. We see urban expansion in China as a process largely responding to top-down policy change and economic transition initiated by the central government. We hold that the role of the state has to be analyzed to understand urban transformation and land expansion, moving beyond local factors of accessibility and feasibility. Development-zone and project fevers, and lagging administrative reforms, however, have made Chinese cities heavy with debt and led to wasteful development, corruption, and social unrest in China. [ABSTRACT FROM AUTHOR]