Special Issue "Urban Morphology and Environment Monitoring"

A special issue of Geomatics (ISSN 2673-7418).

Deadline for manuscript submissions: closed (30 April 2023) | Viewed by 1398

Special Issue Editors

1. Center for Geographic Information System, University of the Punjab, Lahore, Pakistan
2. Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong, China
3. Remote Sensing, GIS and Climatic Research Lab, National Center of GIS and Space Applications, University of the Punjab, Lahore, Pakistan
Interests: spatial data science; digital technologies; smart sensing; earth observation; environmental monitoring; landscape ecology; tropical forest ecology; urban ecology; smart cities; urban climate; climate change; vegetation-climate interaction; land-cover land-use change; drought; cropland; air pollution; water quality; cloud computing; machine learning; big data for SDGs
Special Issues, Collections and Topics in MDPI journals
College of Management, Shenzhen University, Shenzhen 518060, China
Interests: environmental science; environmental economics; resource economics; social policy; clean energy; urban expansion
Special Issues, Collections and Topics in MDPI journals
School of Engineering and Technology, Asian Institute of Technology, Pathum Thani 12120, Thailand
Interests: climate change; environment; location based services; urban development; spatial patterns and processes
Department of Landscape Architecture, Faculty of Architecture and Design, Selcuk University, Konya, Turkey
Interests: landscape architecture; urban planning; landscape ecology; urban sustainability; tourism; environmental science; sustainable development; land use planning; landscape design

Special Issue Information

Dear Colleagues,

Unprecedented urban growth is one of the most critical global challenges. Understanding the urban design, urban sprawl, morphological changes and their association with urban climate and environment can provide critical insight into sustainable urban practices.

During the last five decades, the emergence of Geospatial technologies has transformed methods for urban planning and monitoring associated environmental challenges. Satellite remote sensing data-derived land-use change along with modeling of climate and socio-economic drivers of change are playing a vital role in advancing interdisciplinary research.

The huge amount of data currently produced by modern Earth Observation (EO) missions, the availability of high-performance computing platforms and the implementation of artificial intelligence (AI) provide new opportunities to advance our knowledge.

Considering these advances, this Special Issue invites manuscripts that present new developments and methodologies, best practices, and applications to address the issues related to urban morphology and environment, such as the United Nations’ call for “Sustainable Cities and Communities”.

Dr. Sawaid Abbas
Dr. Ghaffar Ali
Prof. Dr. Nitin Kumar Tripathi
Dr. Sertaç Güngör
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. Geomatics is an international peer-reviewed open access quarterly 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 1000 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.


  • urban sprawl
  • landscape architecture
  • urban planning
  • landscape ecology
  • urban microclimate
  • densification of urban area
  • urban heat island (UHI)
  • solar energy
  • low carbon societies
  • urban ecology
  • land cover land use
  • urban green spaces
  • urban morphology and publica health
  • monitoring change
  • machine learning
  • biophysical and social data integration
  • sustainable development goals monitoring

Published Papers (1 paper)

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Temporal Autocorrelation of Sentinel-1 SAR Imagery for Detecting Settlement Expansion
Geomatics 2023, 3(3), 427-446; https://doi.org/10.3390/geomatics3030023 - 21 Aug 2023
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Urban areas are rapidly expanding globally. The detection of settlement expansion can, however, be challenging due to the rapid rate of expansion, especially for informal settlements. This paper presents a solution in the form of an unsupervised autocorrelation-based approach. Temporal autocorrelation function (ACF) [...] Read more.
Urban areas are rapidly expanding globally. The detection of settlement expansion can, however, be challenging due to the rapid rate of expansion, especially for informal settlements. This paper presents a solution in the form of an unsupervised autocorrelation-based approach. Temporal autocorrelation function (ACF) values derived from hyper-temporal Sentinel-1 imagery were calculated for all time lags using VV backscatter values. Various thresholds were applied to these ACF values in order to create urban change maps. Two different orbital combinations were tested over four informal settlement areas in South Africa. Promising results were achieved in the two of the study areas with mean normalized Matthews Correlation Coefficients (MCCn) of 0.79 and 0.78. A lower performance was obtained in the remaining two areas (mean MCCn of 0.61 and 0.65) due to unfavorable building orientations and low building densities. The first results also indicate that the most stable and optimal ACF-based threshold of 95 was achieved when using images from both relative orbits, thereby incorporating more incidence angles. The results demonstrate the capacity of ACF-based methods for detecting settlement expansion. Practically, this ACF-based method could be used to reduce the time and labor costs of detecting and mapping newly built settlements in developing regions. Full article
(This article belongs to the Special Issue Urban Morphology and Environment Monitoring)
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