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Applications of GIS and 3D City Modelling for Sustainable Urban Planning—from Remote Sensing Perspective

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Urban Remote Sensing".

Deadline for manuscript submissions: 8 April 2025 | Viewed by 5684

Special Issue Editors

Dr. Iván Puente-Luna

E-Mail Website1 Website2
Guest Editor
Defense University Center, Spanish Naval Academy, Plaza de España, s/n, 36920 Marín, Spain
Interests: photogrammetry; laser scanning; multi-sensing imaging; geoinformation; spatial analysis
Special Issues, Collections and Topics in MDPI journals
Dr. Xavier Núñez-Nieto

E-Mail Website1 Website2
Guest Editor
Defense University Center, Spanish Naval Academy, Plaza de España, s/n, 36920 Marín, Spain
Interests: computer-aided design; building information modeling; 3D reconstruction; timeliner simulation; virtual reality
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This is the second Special Issue concerning the contributions of remote sensing to the ‘Applications of Geographic Information System and 3D City Modelling for Sustainable Urban Planning’. 

Rapid urban development has resulted in environmental problems linked to unsustainable transport, housing, waste, energy, and land use management. These crises draw attention to the development of strategies and solutions that ensure self-sustaining and healthier communities, with longer life expectancies for all. They may incorporate, amongst other attributes, green buildings and housing, walkability, greenways and open spaces, alternative energy sources such as solar and wind and good sustainable land use and transportation options.

The challenge of attaining these goals has made geographic information systems (GIS) useful to urban planners. By processing two-dimensional and three-dimensional geospatial data from satellite imaging, aerial photography, and remote sensors, in combination  with environmental and socioeconomic variables, GIS technology offers the means to input, manage, and synthesize information rapidly. It also provides a detailed perspective on land and infrastructure, thereby improving the base of decision making for practitioners and other participants in the processes of urban planning.

We encourage you to submit original research papers and technical or review articles to this Special Issue, placing particular emphasis on the applications of GIS and 3D city models in urban development strategies towards sustainability in order to generate new solutions to urban issues while improving quality of life and urban resilience.

Dr. Iván Puente-Luna
Dr. Xavier Núñez-Nieto
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. Remote Sensing 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 2700 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

  • GIS
  • sustainability
  • 3D city models
  • sensor data integration
  • urban planning
  • geospatial analysis

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Related Special Issue

Published Papers (3 papers)

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Research

25 pages, 8923 KiB  
Article
Open Data-Driven 3D Building Models for Micro-Population Mapping in a Data-Limited Setting
by Kittisak Maneepong, Ryota Yamanotera, Yuki Akiyama, Hiroyuki Miyazaki, Satoshi Miyazawa and Chiaki Mizutani Akiyama
Remote Sens. 2024, 16(21), 3922; https://doi.org/10.3390/rs16213922 - 22 Oct 2024
Viewed by 919
Abstract
Urban planning and management increasingly depend on accurate building and population data. However, many regions lack sufficient resources to acquire and maintain these data, creating challenges in data availability. Our methodology integrates multiple data sources, including aerial imagery, Points of Interest (POIs), and [...] Read more.
Urban planning and management increasingly depend on accurate building and population data. However, many regions lack sufficient resources to acquire and maintain these data, creating challenges in data availability. Our methodology integrates multiple data sources, including aerial imagery, Points of Interest (POIs), and digital elevation models, employing Light Gradient Boosting Machine (LightGBM) and Gradient Boosting Decision Tree (GBDT) to classify building uses and morphological filtration to estimate heights. This research contributes to bridging the gap between data needs and availability in resource-constrained urban environments, offering a scalable solution for global application in urban planning and population mapping. Full article
(This article belongs to the Special Issue Applications of GIS and 3D City Modelling for Sustainable Urban Planning—from Remote Sensing Perspective)
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14 pages, 2219 KiB  
Article
Surveillance Video Georeference Method Based on Real Scene Model with Geometry Priors
by Zhongxian Zhou, Jianchen Liu, Miaomiao Feng and Yuwei Cong
Remote Sens. 2023, 15(17), 4217; https://doi.org/10.3390/rs15174217 - 28 Aug 2023
Viewed by 1222
Abstract
With the comprehensive promotion of digital construction in China, cameras scattered throughout the country are of great significance in obtaining first-hand data. However, their potential role is limited due to the lack of georeference information on current surveillance cameras. Provided surveillance camera images [...] Read more.
With the comprehensive promotion of digital construction in China, cameras scattered throughout the country are of great significance in obtaining first-hand data. However, their potential role is limited due to the lack of georeference information on current surveillance cameras. Provided surveillance camera images and real scenes are combined and given georeference information, this problem can be solved, allowing cameras to generate significant social benefits. This article proposed an accurate registration method based on misalignment calibration and least squares matching between real scene and surveillance camera images to address this issue. Firstly, it is necessary to convert the navigation coordinate system from which cameras obtain data to the photogrammetric coordinate system and then solve for the misalignment and internal orientation elements of the camera. Then, accurate registration is achieved using the least squares matching on pyramid images. The experiment obtained surrounding image data of two common scenes with lens pitch angles of 45°, 55°, 65°, 75°, and 85° using the surveillance camera and obtained a 3D real scene model of each scene using a low-altitude aircraft. The experiment results show that the proposed method in this paper can achieve the expected goals of accurately matching real scene and surveillance camera images and assigning georeference information. Through extensive data analysis, the success rate and accuracy rate of registration are 98.1% and 97.06%, respectively. Full article
(This article belongs to the Special Issue Applications of GIS and 3D City Modelling for Sustainable Urban Planning—from Remote Sensing Perspective)
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26 pages, 12317 KiB  
Article
Landfill Site Selection Using Multi-Criteria Decision Analysis, Remote Sensing Data, and Geographic Information System Tools in Najran City, Saudi Arabia
by Ismail Elkhrachy, Ali Alhamami and Saleh H. Alyami
Remote Sens. 2023, 15(15), 3754; https://doi.org/10.3390/rs15153754 - 28 Jul 2023
Cited by 10 | Viewed by 2869
Abstract
Many practical issues arise when dealing with solid waste management, and there are also environmental effects to be considered. Selecting landfill sites requires extra care with respect to many factors such as the environment, health hazards for people, and the cost of transportation. [...] Read more.
Many practical issues arise when dealing with solid waste management, and there are also environmental effects to be considered. Selecting landfill sites requires extra care with respect to many factors such as the environment, health hazards for people, and the cost of transportation. Furthermore, cities have their own rules, methods, and practices for managing and selecting the best locations for collecting solid waste. In this research, multi-criteria decision analysis (MCDA) was presented and used to evaluate the appropriateness of and suggest the best locations for landfill sites in Najran, KSA. Some remote sensing data and the ArcGIS software were used to prepare nine thematic layers, including drainage density, groundwater depth, land use, soil type, road network, surface elevation, surface slope, distance from residential areas, and distance from protected areas. To evaluate the layer weightings, a questionnaire with pairwise comparisons was distributed among experts and analyzed using the analytical hierarchy process (AHP) and fuzzy set technique. The one-factor-at-a-time (OFAT) sensitivity test was conducted to test the sensitivity of the evaluated weightings. A landfill suitability index (LSI) map was created using raster calculator tools and divided into five classes: limited suitability (LSI value 1.39–2.49), least suitable (2.50–3.03), relatively suitable (3.04–3.48), suitable (3.49–3.91), and most suitable (3.92–4.66). According to the statistical analysis, 18.0% and 18.2% of the total area were within the most suitable and suitable landfill regions, while 21.2%, 14.9%, and 9.5% accounted for relatively suitable, least suitable, and limited suitability areas, respectively. The employed technique and its findings can provide an appropriate guideline to assist the municipality of Najran city, regional planners, and decision-makers in selecting an optimal landfill site in the future. This study also presented some recommendations to enhance the suitability map of landfill sites in Najran city. Full article
(This article belongs to the Special Issue Applications of GIS and 3D City Modelling for Sustainable Urban Planning—from Remote Sensing Perspective)
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