Spatial Data Analysis and Geographic Information Systems for Urban Land Use

Dear Colleagues,

In the process of global urbanisation, some regions are experiencing rapid urban expansion, while others face the challenges of urban shrinkage, and, in this context, the precise quantification and scientific regulation of urban land use structures have become crucial in terms of enhancing the quality of life of residents and promoting sustainable spatial development. Traditional planning models often struggle to address the complex and dynamic demands of contemporary cities, hence spatial data analysis and geographic information systems (GISs), with their efficiency in dynamic monitoring and management, have become key research topics. Furthermore, the integration of GIS methods with emerging technological tools, such as large language models (LLMs) and machine/deep learning, provides cutting-edge support for detailed land use quantification and long-term change tracking. These advancements facilitate the rational allocation of land resources, improved urban environments, enhanced ecological protection, and ultimately, better living standards for residents.

This Special Issue aims to focus on cutting-edge research that uses spatial data analysis and GIS technology for the in-depth quantification and regulation of urban land use structures across diverse geographic contexts. The objective is to drive a paradigm shift in urban land use planning and spatial data processing, fostering an organic synthesis of land use theory and advanced technological methodologies. We particularly encourage studies that leverage state-of-the-art technological solutions such as high-resolution remote sensing imagery, multi-source data fusion techniques, and LLMs. These approaches can help uncover land use change patterns, optimise urban spatial structures, and inform evidence-based land use policymaking. Such research not only demands proficiency in new technological tools but also calls for refinements in land use policy frameworks and theoretical models.

We invite submissions on the follow themes: high-resolution remote sensing data analysis, spatial data fusion and multi-source GIS applications, land use change monitoring and modelling, urban ecological model development, and AI-driven urban data processing (e.g., machine learning, deep learning, and LLMs).

We also welcome theoretical discussions, methodological innovations, case studies, and interdisciplinary analyses that offer fresh perspectives and empirical insights into urban land use research.

Dr. Jin Rui
Dr. Mengqiu Cao
Guest Editors

Manuscript Submission Information

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• urban land use
• spatial data analysis
• geographic information systems (GISs)
• remote sensing imagery
• machine learning
• large language models (LLMs)
• big data
• data-driven
• urban planning
• sustainable cities