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Remote Sensing-Based Urban Morphology Analysis

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

Deadline for manuscript submissions: closed (30 September 2022) | Viewed by 15159

Special Issue Editors


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Guest Editor
School of Architecture and Built Environment, Faculty of Engineering, Computer and Mathematical Sciences, The University of Adelaide, Adelaide, SA 5005, Australia
Interests: urban ecology; remote sensing; numerical modelling and simulation; spatial data science; GIS

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Guest Editor
Faculty of Built Environment, University of New South Wales, Sydney, NSW 2052, Australia
Interests: urban morphology; building/urban metabolism; ecosystem services; green infrastructure; urban climatology; architectural/urban ambience
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Urban morphology has been described as “the study of the city as human habitat” (Moudon 1997). It embraces a diversity of methods and techniques, from town planning analysis to space syntax and geographic information systems. Remote sensing technologies have become an increasingly important element of the urban morphologist’s toolkit, used to map, model, monitor and assess the physical conditions of urban areas worldwide. Cities are the physical expression of myriad interacting economic and social processes, often described as urban metabolism. Accordingly, different properties, compositions and arrangements of buildings, artificial surfaces and open space can influence the urban microclimate, greenspace provision, traffic congestion, anthropogenic heat, air and water quality and surface runoff, both separately and concurrently. These conditions are highly dynamic and heterogenous; they vary in time, space, scale and intensity.

In today’s circumstances of rapid urbanisation, better understanding and addressing of the environmental, social and economic effects of the formation and transformation of urban form are urgently required, necessitating new multi-disciplinary and multi-faceted approaches. This could help to solve pressing local and global environmental issues, and facilitate the better planning and design of our “human habitat”. In this Special Issue, we encourage submissions applying remote sensing approaches to analyse the complex, dynamic and multi-temporal interactions between urban morphology and the metabolic aspects of the built environment. Contributions should emphasise quantitative and empirical studies and may focus on one or more of the following aspects:

  • Multi-disciplinary, multi-temporal and multi-scale methods and approaches to better understand the interactions between changes in urban morphology and carbon emissions, energy efficiency, urban overheating, pollution (air quality), anthropogenic heat production, water quality and runoff, mortality and morbidity, and more.
  • Novel methods and technologies combining remotely sensed and image processing data (i.e., LiDAR, spectral and thermal imagery) to map, model, monitor, and analyse urban morphology more rapidly, efficiently and accurately.
  • Application of three-dimensional (3D) approaches, including vertical and horizontal surfaces, for modelling urban morphology conditions and analysing its impact on the outdoor environment.
  • Novel indicators, parameters and spatial metrics for the performance-based analysis of urban morphology.
  • Implications of spatial, temporal, spectral and radiometric resolution on the characterisation of urban morphology and its impacts on the environmental conditions of urban areas.
  • Remote sensing approaches describing urban land cover/land use as continuum phenomena and their implications on heat island and cool island formation.

Reference

Moudon, A.V., 1997. Urban morphology as an emerging interdisciplinary field. Urban morphology, 1(1), pp. 3-10.

Dr. Carlos Bartesaghi Koc
Dr. Paul Osmond
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

  • Urban form
  • Dynamic performance-based analysis
  • Spatio-temporal change-detection
  • LiDAR
  • Spectral and thermal imagery
  • 3D urban morphology
  • Multi-disciplinary assessment

Published Papers (4 papers)

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Research

34 pages, 7553 KiB  
Article
Potential of Using Night-Time Light to Proxy Social Indicators for Sustainable Development
by Ana Andries, Stephen Morse, Richard J. Murphy, Jhuma Sadhukhan, Elias Martinez-Hernandez, Myriam A. Amezcua-Allieri and Jorge Aburto
Remote Sens. 2023, 15(5), 1209; https://0-doi-org.brum.beds.ac.uk/10.3390/rs15051209 - 22 Feb 2023
Cited by 3 | Viewed by 3193
Abstract
Satellite-observed night-time light (NTL) data provide a measure of the lighting brightness seen from space at different times and spatial and temporal resolutions, thus offering opportunities to explore them in many applications at different spatial locations (global, regional, local). However, most applications to [...] Read more.
Satellite-observed night-time light (NTL) data provide a measure of the lighting brightness seen from space at different times and spatial and temporal resolutions, thus offering opportunities to explore them in many applications at different spatial locations (global, regional, local). However, most applications to date have been at relatively large spatial scales, despite the need to measure indicators at a local level. This paper sets out an analysis of the potential of NTL data for populating indicators at more local (neighbourhood, street) scales. We first reviewed the overall potential of NTL data for social indicators at different spatial scales by using a systematic search of the literature and applying the Maturity Matrix Framework (MMF). We also explored a case study (Durango State, Mexico) using Visible Infrared Imaging Radiometer Suite (VIIRS) imageries, other geospatial data, and the social gap index (SGI) to identify social gaps at the local scale. The literature review showed that NTL can play a role in supporting 49 out of 192 sustainable development goal (SDG) indicators having a focus on social issues, but most of these have been explored at the global or country scales. In the case study, we found that low radiance is indeed associated with higher SGI levels (i.e., more social deprivation) and vice versa. However, more research is needed from other contexts to support a link between NTL radiance levels and social indicators at local scales. Full article
(This article belongs to the Special Issue Remote Sensing-Based Urban Morphology Analysis)
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14 pages, 3082 KiB  
Article
Differences in Urban Morphology between 77 Cities in China and Europe
by Fengxiang Guo, Uwe Schlink, Wanben Wu and Abdelrhman Mohamdeen
Remote Sens. 2022, 14(21), 5462; https://doi.org/10.3390/rs14215462 - 30 Oct 2022
Cited by 5 | Viewed by 2233
Abstract
Urban morphology refers to the physical form of a city that is constantly transformed and updated in the process of urbanization. A valuable source of data on ‘built forms’ is modern remote sensing technology, which provides a variety of products on building footprints [...] Read more.
Urban morphology refers to the physical form of a city that is constantly transformed and updated in the process of urbanization. A valuable source of data on ‘built forms’ is modern remote sensing technology, which provides a variety of products on building footprints and heights at national, continental, and global levels. A large-scale comparison of urban morphologies is important for assessing urban development as well as its influence on urban ecology; however, this has not been well documented so far. This study includes 41 cities in China and 36 in Europe with various city sizes, population densities, and climate features. We applied 3D landscape metrics and principal component analysis (PCA) to compare the spatial aspects of the urban morphology of these cities. We found: (1) measurements of the building height, surface fluctuation, and texture directionality of urban building layouts in China are higher than those of European cities, while the latter are high-density and compact built landscapes; (2) a significant clustering phenomenon for Chinese and European cities revealed by PCA, with the former showing a much more aggregated pattern, indicating a relatively uniform morphology of urban buildings in China; (3) distinctions between cities in China and Europe are suggested by the first principal component, to which building height, surface fluctuation, building complexity, and spatial distance among buildings contribute significantly; and (4) the second principal component (mainly represented by maximum building height, surface area, volume, and shape metrics) can separate large metropolitan cities and provincial capitals from cities with lower urban population, smaller size, and slower economic development. Our results demonstrate the potential of 3D landscape metrics for measuring urban morphology. Together with a temporal analysis, these metrics are useful for quantifying how urban morphology varies in space and time on a large scale, as well as evaluating the process of urbanization. Full article
(This article belongs to the Special Issue Remote Sensing-Based Urban Morphology Analysis)
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19 pages, 8751 KiB  
Article
Characterizing Spatiotemporal Variations in the Urban Thermal Environment Related to Land Cover Changes in Karachi, Pakistan, from 2000 to 2020
by Muhammad Fahad Baqa, Linlin Lu, Fang Chen, Syed Nawaz-ul-Huda, Luyang Pan, Aqil Tariq, Salman Qureshi, Bin Li and Qingting Li
Remote Sens. 2022, 14(9), 2164; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14092164 - 30 Apr 2022
Cited by 34 | Viewed by 3806
Abstract
Understanding the spatiotemporal patterns of urban heat islands and the factors that influence this phenomenon can help to alleviate the heat stress exacerbated by urban warming and strengthen heat-related urban resilience, thereby contributing to the achievement of the United Nations Sustainable Development Goals. [...] Read more.
Understanding the spatiotemporal patterns of urban heat islands and the factors that influence this phenomenon can help to alleviate the heat stress exacerbated by urban warming and strengthen heat-related urban resilience, thereby contributing to the achievement of the United Nations Sustainable Development Goals. The association between surface urban heat island (SUHI) effects and land use/land cover features has been studied extensively, but the situation in tropical cities is not well-understood due to the lack of consistent data. This study aimed to explore land use/land cover (LULC) changes and their impact on the urban thermal environment in a tropical megacity—Karachi, Pakistan. Land cover maps were produced, and the land surface temperature (LST) was estimated using Landsat images from five different years over the period 2000–2020. The surface urban heat island intensity (SUHII) was then quantified based on the LST data. Statistical analyses, including geographically weighted regression (GWR) and correlation analyses, were performed in order to analyze the relationship between the land cover composition and LST. The results indicated that the built-up area of Karachi increased from 97.6 km² to 325.33 km² during the period 2000–2020. Among the different land cover types, the areas classified as built-up or bare land exhibited the highest LST, and a change from vegetation to bare land led to an increase in LST. The correlation analysis indicated that the correlation coefficients between the normalized difference built-up index (NDBI) and LST ranged from 0.14 to 0.18 between 2000 and 2020 and that NDBI plays a dominant role in influencing the LST. The GWR analysis revealed the spatial variation in the association between the land cover composition and the SUHII. Parks with large areas of medium- and high-density vegetation play a significant role in regulating the thermal environment, whereas the scattered vegetation patches in the urban core do not have a significant relationship with the LST. These findings can be used to inform adaptive land use planning that aims to mitigate the effects of the UHI and aid efforts to achieve sustainable urban growth. Full article
(This article belongs to the Special Issue Remote Sensing-Based Urban Morphology Analysis)
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26 pages, 9531 KiB  
Article
Remote Sensing-Based Urban Sprawl Modeling Using Multilayer Perceptron Neural Network Markov Chain in Baghdad, Iraq
by Wafaa Majeed Mutashar Al-Hameedi, Jie Chen, Cheechouyang Faichia, Bazel Al-Shaibah, Biswajit Nath, Abdulla-Al Kafy, Gao Hu and Ali Al-Aizari
Remote Sens. 2021, 13(20), 4034; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13204034 - 09 Oct 2021
Cited by 20 | Viewed by 4194
Abstract
The global and regional land use/cover changes (LUCCs) are experiencing widespread changes, particularly in Baghdad City, the oldest city of Iraq, where it lacks ecological restoration and environmental management actions at present. To date, multiple land uses are experiencing urban construction-related land expansion, [...] Read more.
The global and regional land use/cover changes (LUCCs) are experiencing widespread changes, particularly in Baghdad City, the oldest city of Iraq, where it lacks ecological restoration and environmental management actions at present. To date, multiple land uses are experiencing urban construction-related land expansion, population increase, and socioeconomic development. Comprehensive evaluation and understanding of the effect of urban sprawl and its rapid LUCC are of great importance to managing land surface resources for sustainable development. The present research applied remote sensing data, such as Landsat-5 Thematic Mapper and Landsat-8 Operation Land Imager, on selected images between July and August from 1985 to 2020 with the use of multiple types of software to explore, classify, and analyze the historical and future LUCCs in Baghdad City. Three historical LUCC maps from 1985, 2000, and 2020 were created and analyzed. The result shows that urban construction land expands quickly, and agricultural land and natural vegetation have had a large loss of coverage during the last 35 years. The change analysis derived from previous land use was used as a change direction for future simulation, where natural and anthropogenic factors were selected as the drivers’ variables in the process of multilayer perceptron neural network Markov chain model. The future land use/cover change (FLUCC) modeling results from 2030 to 2050 show that agriculture is the only land use type with a massive decreasing trend from 1985 to 2050 compared with other categories. The entire change in urban sprawl derived from historical and FLUCC in each period shows that urban construction land increases the fastest between 2020 and 2030. The rapid urbanization along with unplanned urban growth and rising population migration from rural to urban is the main driver of all transformation in land use. These findings facilitate sustainable ecological development in Baghdad City and theoretically support environmental decision making. Full article
(This article belongs to the Special Issue Remote Sensing-Based Urban Morphology Analysis)
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