Big Data in Urban Land Use Planning and Infrastructure Building

A special issue of Land (ISSN 2073-445X). This special issue belongs to the section "Urban Contexts and Urban-Rural Interactions".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 895

Special Issue Editors


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Guest Editor
Department of Geography, Universidad Nacional de Educación a Distancia, 28008 Madrid, Spain
Interests: geolocated data; transportation; demography; socioeconomic characteristics of the population; infrastructure and land use at different spatial and temporal scales

Special Issue Information

Dear Colleagues,

The increasing availability of new Big Data sources has revolutionized the way urban and metropolitan infrastructure is planned, designed, and managed. This Special Issue explores how Big Data, in its multiple forms (sensor data, social media, mobile phones, transport cards, bank cards, satellite images, open data, etc.), is transforming urban decision-making processes, fostering more efficient and resilient land planning focused on the real needs of the population. The crucial role of urban land planning is highlighted as an integrative framework for guiding the development of sustainable and equitable infrastructure adapted to contemporary challenges such as climate change, territorial inequality, and the energy crisis.

The articles included examine empirical cases and methodological developments in fields such as land-use optimization, spatial suitability analysis, smart transportation, energy management, tactical urbanism, green infrastructure, and territorial planning, highlighting the value of Big Data for modeling complex urban and metropolitan phenomena and anticipating future needs. In this context, aspects such as the relationship between commuter towns and the location of workplaces in a metropolitan area, or the relevance of models such as the 15-Minute City, which promote functional proximity and service decentralization, are analyzed as key strategies for urban sustainability. Attention is also paid to the integration of tools such as geographic information systems (GIS), digital twins, and machine learning algorithms for predictive land-use planning. This Special Issue seeks to foster a critical and transdisciplinary perspective, bringing together contributions from engineering, social sciences, urban geography, and computer science. Together, the papers presented demonstrate the potential of Big Data to redefine the way we conceive and develop more inclusive, smart, and livable cities.

The goal of this Special Issue is to collect papers (original research articles and review papers) to give insights into the use of new geolocated Big Data sources for urban land planning and the development of urban infrastructures.

This Special Issue will welcome manuscripts that link the following themes:

  • Urban land planning.
  • Urban or metropolitan infrastructure planning based on Big Data analytics.
  • Smart mobility and transportation systems.
  • Digital tools for sustainable and inclusive urban development.
  • Urban resilience and climate-adaptive infrastructure.
  • Geospatial technologies and real-time urban monitoring.
  • Proximity-based planning for accessibility to basic services.
  • Ethical, legal, and governance challenges in data-driven urbanism.

We look forward to receiving your original research articles and reviews.

Prof. Dr. Joaquin Osorio Arjona
Prof. Dr. Yang Xiao
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Land is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • urban land use
  • geolocated big data
  • urban infrastructures
  • smart cities
  • spatial planning
  • metropolization
  • sustainability planning models

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Published Papers (1 paper)

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Research

33 pages, 8758 KB  
Article
Unveiling the Spatial Non-Stationarity Between Built Environment and External Relations in Small Towns Using MGWR and Mobile Phone Data: Evidence from the Yangtze River Delta
by Yang Li, Yao Wang, Min Han, Yuli Xia and Yan Ma
Land 2026, 15(4), 659; https://doi.org/10.3390/land15040659 - 16 Apr 2026
Viewed by 496
Abstract
The external relations of small towns are an important dimension in the regional urban system. However, the “metropolitan bias” in existing studies results in a lack of empirical verification of their characteristics, hindering effective regional policymaking. Applying Central Flow Theory (CFT), mobile phone [...] Read more.
The external relations of small towns are an important dimension in the regional urban system. However, the “metropolitan bias” in existing studies results in a lack of empirical verification of their characteristics, hindering effective regional policymaking. Applying Central Flow Theory (CFT), mobile phone data, and a multiscale geographically weighted regression (MGWR) model, this study investigates the spatially non-stationary associations between built environment factors and the “city-ness” and “town-ness” of small towns in the Yangtze River Delta. The results show: (1) Enterprise density in metropolitan shadow areas is positively associated with cross-city jobs–housing separation; in peripheral areas, both enterprise density and housing prices exhibit a strong correlation with intra-municipal jobs–housing separation. (2) Middle schools consistently correlate with localized intra-municipal flows, suggesting a plausible spatial anchoring role; around metropolises, medical and commercial facilities link to recreational flows and commuting town-ness, while in distal small towns, medical facilities coincide with intratown jobs–housing balance, and commercial facilities correlate with localized consumption and cross-town employment mobility. (3) Higher road network density corresponds to a shrinking commuting radius near metropolises and intra-municipal intertown interconnection in distal towns, rather than mere external relation channels. This study empirically supports CFT at the small-town scale, explores plausible mechanisms, and informs differentiated planning strategies. Full article
(This article belongs to the Special Issue Big Data in Urban Land Use Planning and Infrastructure Building)
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