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Urban Geospatial Analytics Based on Big Data
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Urban Geospatial Analytics Based on Big Data

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Environmental Sciences".

Deadline for manuscript submissions: closed (20 May 2025) | Viewed by 1921

Special Issue Editors

Dr. Anna Kochanek

E-Mail Website
Guest Editor
Institute of Engineering, State University of Applied Sciences in Nowy Sącz, Zamenhofa 1A, 33-300 Nowy Sącz, Poland
Interests: spatial analysis; spatial information systems; GIS; spatial relationships
Prof. Dr. Agnieszka Generowicz

E-Mail Website
Guest Editor
Department of Environmental Technologies, Faculty of Environmental Engineering and Energy, Cracow University of Technology, Warszawska 24, 31-155 Kraków, Poland
Interests: waste management; recycling; reuse; recovery; materials from waste; circular economy; sustainable development
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue on “Urban Geospatial Analytics Based on Big Data” invites submission of recent research papers on this promising area of geospatial analytics applications. The call is open to a wide range of thematic articles covering the latest applications of big data and applied geographic information systems in various fields such as urban planning, real estate management, transportation and logistics management, and agriculture, among others. A very important aspect is crisis management and civil protection in natural disasters through rapid analysis of unfolding events and their ongoing monitoring. Another area of application of geo-information systems is the management of public health and health care availability. Yet another important group of applications is the processing of information at the location of various phenomena, especially those with high variability over time. Geographic information systems are an effective tool for monitoring pollution levels, which is crucial in engineering and environmental protection and in with regard to sustainable development.

This Special Issue aims to offer readers knowledge on expanding the application of spatial information systems, multi-criteria spatial analysis, and statistical models for decision support at various levels in many fundamental applications.

Dr. Anna Kochanek
Prof. Dr. Agnieszka Generowicz
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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. Applied Sciences is an international peer-reviewed open access semimonthly 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 2400 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

  • geospatial data
  • databases
  • spatial analysis
  • spatial information systems
  • GIS
  • spatial relationships
  • big data

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Published Papers (2 papers)

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19 pages, 12433 KiB  
Article
Identification of Inequities in Green Visibility and Ways to Increase Greenery in Neighborhoods: A Case Study of Wuhan, China
by Xiaohua Guo, Chang Liu, Shibo Bi and Yuling Tang
Appl. Sci. 2025, 15(2), 742; https://doi.org/10.3390/app15020742 - 13 Jan 2025
Viewed by 887
Abstract
The rapid increase in urban population density driven by urban development has intensified inequity in urban green space distribution. Identifying the causes of changes in green equity and developing strategies to improve urban greening are crucial for optimizing resource allocation and alleviating social [...] Read more.
The rapid increase in urban population density driven by urban development has intensified inequity in urban green space distribution. Identifying the causes of changes in green equity and developing strategies to improve urban greening are crucial for optimizing resource allocation and alleviating social inequalities. However, the long-term spatio-temporal evolution of green visibility and equity remains underexplored. This study utilized the “Time Machine” feature to capture street view images from 2014, 2017, and 2021, analyzing changes in green visibility and its equity across residential communities in Wuhan. Deep learning techniques and statistical methods, including the Gini coefficient and location quotient (LQ), were employed to assess the distribution and spatial equity of street-level greenery. The results showed that overall green visibility in Wuhan increased by 4.18% between 2014 and 2021. However, this improvement did not translate into better spatial equity, as the Gini coefficient consistently ranged between 0.4 and 0.5. Among the seven municipal districts, only the Jiang’an District demonstrated relatively equitable green visibility in 2017 and 2021. Despite a gradual reduction in disparities in green visibility, a spatial mismatch persisted between UGS growth and population distribution, leading to uneven patterns in UGS equity. This study explores the factors driving inequities in green visibility and proposes strategies to enhance urban greening. Key recommendations include integrating the green visibility equity evaluation framework into urban planning to guide fair green space allocation, prioritizing greenery in low-income neighborhoods, and reducing hardscapes to support the planting and maintenance of tall canopy trees. These measures aim to enhance accessible and visible green resources and promote equitable access across communities. Full article
(This article belongs to the Special Issue Urban Geospatial Analytics Based on Big Data)
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19 pages, 6391 KiB  
Article
Automated Tree Detection Using Image Processing and Multisource Data
by Grzegorz Dziczkowski, Barbara Probierz, Przemysław Juszczuk, Piotr Stefański, Tomasz Jach, Szymon Głowania and Jan Kozak
Appl. Sci. 2025, 15(2), 667; https://doi.org/10.3390/app15020667 - 11 Jan 2025
Viewed by 738
Abstract
This paper presents a method for the automatic detection and assessment of trees and tree-covered areas in Katowice, the capital of the Upper Silesian Industrial Region in southern Poland. The proposed approach utilizes satellite imagery and height maps, employing image-processing techniques and integrating [...] Read more.
This paper presents a method for the automatic detection and assessment of trees and tree-covered areas in Katowice, the capital of the Upper Silesian Industrial Region in southern Poland. The proposed approach utilizes satellite imagery and height maps, employing image-processing techniques and integrating data from various sources. We developed a data pipeline for gathering and pre-processing information, including vegetation data and numerical land-cover models, which were used to derive a new method for tree detection. Our findings confirm that automatic tree detection can significantly enhance the efficiency of urban tree management processes, contributing to the creation of greener and more resident-friendly cities. Full article
(This article belongs to the Special Issue Urban Geospatial Analytics Based on Big Data)
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