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

Deadline for manuscript submissions: closed (28 February 2023) | Viewed by 25803

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Special Issue Editors

Dr. Christiane Weber

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Guest Editor

DR CNRS, TETIS Research Unit, AgroParisTech, CIRAD, CNRS, Irstea, Maison de la Télédétection, 500 rue Jean-François Breton, 34000 Montpellier, France
Interests: urban environment; urban multifunctionality; remote sensing
Special Issues, Collections and Topics in MDPI journals

Dr. Jingxia Wang

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Guest Editor

1. Department of Urban Studies and Planning, The University of Sheffield, Western Bank, Sheffield S10 2TN, UK
2. Institute of Geography, Ruhr University Bochum, 44801 Bochum, Germany
Interests: landscape and urban ecology; land resources management; landscape planning and management; social-ecological systems research
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Remote sensing associated with urban NTIC innovations have strongly changed urban planning practices and tools.

Imagery has reinforced the importance of representation and location identification, largely supported by GIS capacities and development.

From the late 70s until now, tremendous imagery enhancing has lead to changes in practices, tools and norms. From inventory to global comparison products, imagery has pushed towards usable and homogeneous products that are valuable at various scales (EU or global products). If remote sensing products are variably disseminated in urban and planning offices, their impact is not negligeable.

Actual challenges regarding climate change and biodiversity conservation favor the importance of images in various evaluation directives and plans. Vegetation, water, sealed surfaces, and soils are resources that could be monitored regularly with the help of RS imagery. As such, products might be introduced in urban heat surface or local climatic zone identification, nature based solutions design, urban ecological infrastructures, or urban health projects management. RS is a strong asset for urban complexity management.

Multispectral, superspectral, and hyperspectral sensors have diversified observation capacities and offered a large panel of applications: from cartography, to prospective modelling promoting urban elements monitoring, at various scales from regional to local, and introducing imagery in urban planning practices and citizen applications.

Actual trends turn to integrated developments mixing massive information capacities, modelling, visualization capacities and collaborative assessments. Citizen sciences emerge, stressing the crucial role of spatial technologies for a large part of population in daily life, and consequently the role of these spatial technologies for planning developments.

Spatial imagery development has promoted the use and the benefit of RS products in planning technologies for sustainable cities development and crises management. However, some difficulties might compel the introduction of RS products in planning rules, laws or territorial directives. As such, it might also be interesting to identify bottlenecks and practical problems that halt these potential disseminations.

Numerous applications can illustrated the interest of imagery in urban planning practices, and several tools or applications can be described in various contexts. This Special Issue might be the opportunity to share experiences, at various scales (urban project to metropolitan planning issue), and to confront both contextual positions, methodological choices and developments, and results for various countries or regions.

Suggested themes and article types for submissions:

Artificial and sealed surfaces monitoring;
Urban disaster management;
Subsidence monitoring;
Biodiversity monitoring;
Urban Vegetation monitoring;
HUI and SHUI determination and monitoring;
Urban Ecological infrastructure;
Nature-based solution;
Citizen sciences;
Sensors capacities and future development;
Enhanced methodologies: like deep learning, spectral fusion, time-series analysis;
Data mining;
Data analyses;
Urban indicators.

Dr. Christiane Weber
Dr. Jingxia Wang
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 challenges
urban monitoring
urban imagery
urban practices and tools
urban spatial technologies
news urban sensors issues

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Published Papers (7 papers)

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Research

24 pages, 12069 KiB

Open AccessArticle

Exploring the Use of Orthophotos in Google Earth Engine for Very High-Resolution Mapping of Impervious Surfaces: A Data Fusion Approach in Wuppertal, Germany

by Jan-Philipp Langenkamp and Andreas Rienow

Remote Sens. 2023, 15(7), 1818; https://doi.org/10.3390/rs15071818 - 29 Mar 2023

Cited by 5 | Viewed by 2758

Abstract

Germany aims to reduce soil sealing to under 30 hectares per day by 2030 to address negative environmental impacts from the expansion of impervious surfaces. As cities adapt to climate change, spatially explicit very high-resolution information about the distribution of impervious surfaces is becoming increasingly important for urban planning and decision-making. This study proposes a method for mapping impervious surfaces in Google Earth Engine (GEE) using a data fusion approach of 0.9 m colour-infrared true orthophotos, digital elevation models, and vector data. We conducted a pixel-based random forest (RF) classification utilizing spectral indices, Grey-Level Co-occurrence Matrix texture features, and topographic features. Impervious surfaces were mapped with 0.9 m precision resulting in an Overall Accuracy of 92.31% and Kappa-Coefficient of 84.62%. To address challenges posed by high-resolution imagery, we superimposed the RF classification results with land use data from Germany’s Authoritative Real Estate Cadastre Information System (ALKIS). The results show that 25.26% of the city of Wuppertal is covered by impervious surfaces coinciding with a government-funded study from 2020 based on Sentinel-2 Copernicus data that defined a proportion of 25.22% as built-up area. This demonstrates the effectiveness of our method for semi-automated mapping of impervious surfaces in GEE to support urban planning on a local to regional scale. Full article

(This article belongs to the Special Issue Urban Planning Supported by Remote Sensing Technology)

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28 pages, 6416 KiB

Open AccessArticle

Urbanization Trends Analysis Using Hybrid Modeling of Fuzzy Analytical Hierarchical Process-Cellular Automata-Markov Chain and Investigating Its Impact on Land Surface Temperature over Gharbia City, Egypt

by Eman Mostafa, Xuxiang Li and Mohammed Sadek

Remote Sens. 2023, 15(3), 843; https://doi.org/10.3390/rs15030843 - 2 Feb 2023

Cited by 18 | Viewed by 2424

Abstract

Quick population increase and the desire for urbanization are the main drivers for accelerating urban expansion on agricultural lands in Egypt. This issue is obvious in governorates with no desert backyards. This study aims to (1) explore the trend of Land Use Land Cover Change (LULCC) through the period of 1991–2018; (2) upgrade the reliability of predicting LULCC by integrating the Cellular Automata (CA)-Markov chain and fuzzy analytical hierarchy process (FAHP); and (3) perform analysis of urbanization risk on LST trends over the Gharbia governorate for the decision makers to implement effective strategies for sustainable land use. Multi-temporal Landsat images were used to monitor LULCC dynamics from 1991 to 2018 and then simulate LULCC in 2033 and 2048. Two comparable models were adopted for the simulation of spatiotemporal dynamics of land use in the study area: CA-Markov chain and FAHP-CA-Markov chain hybrid models. The second model upgrades the potential of the CA-Markov chain for prediction by its integration with FAHP, which can determine the locations of high potential to be urbanized. The outcomes stated a significant LULCC in Gharbia during the study period—specifically, urban sprawl on agricultural land, and this trend is predicted to carry on. The agricultural sector represented 91.2% in 1991 and reduced to 83.7% in 2018. The built-up area is almost doubled by 2048 with respect to 2018. The regression analysis revealed the LST increase due to urbanization, causing an urban heat island phenomenon. Criteria-based analysis reveals the district’s vulnerability to rapid urbanization, which is efficient for data-gap zones. The simulation results make sense since the FAHP-CA-Markov simulated the LULCC in a thoughtful way, considering the driving forces of LULCC, while the CA-Markov chain results were relatively random. Therefore, the FAHP-CA-Markov chain is the pioneer to be relied upon for future projection. The findings of this work provide a better understanding of LULCC trends over the years supporting decision makers toward sustainable land use. Thus, further urbanization should be planned to avert the loss of agricultural land and uninterrupted increasing temperatures. Full article

(This article belongs to the Special Issue Urban Planning Supported by Remote Sensing Technology)

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18 pages, 11862 KiB

Open AccessArticle

Thermal Contribution of the Local Climate Zone and Its Spatial Distribution Effect on Land Surface Temperature in Different Macroclimate Cities

by Ninglv Li, Bin Wang, Yang Yao, Liding Chen and Zhiming Zhang

Remote Sens. 2022, 14(16), 4029; https://doi.org/10.3390/rs14164029 - 18 Aug 2022

Cited by 4 | Viewed by 4026

Abstract

Local climate zones (LCZs) provide a comprehensive framework to examine surface urban heat islands (SUHIs), but information is lacking on their thermal contributions and spatial effects in different macroclimate cities. A standard framework for distinguishing between the cooling effect and heating effect and spatial effect analysis based on the LCZ scheme was conducted in five distinct macroclimate cities, i.e., Yuanjiang (arid climate), Jinghong (tropical climate), Kunming (subtropical climate), Zhaotong (temperate climate), and Shangri-La (alpine climate). The results indicated that (1) built-up zones presented heating effects in Jinghong and Shangri-La, but opposite results were observed in Yuanjiang and Zhaotong. (2) The thermal contributions of natural zones with dense trees (LCZAs) and waterbodies (LCZGs) showed cooling effects in the five cities regardless of season. (3) The spatial effect of heating LCZs on land surface temperature (LST) was more significant than that of cooling LCZs in Jinghong and Shangri-La, but the opposite results occurred in Yuanjiang and Kunming. Moreover, the spatial effect was lower in Zhaotong than in other cities. (4) Lower LST differences between natural zones and built-up zones in winter than in summer decreased the spatial effects. In summary, the thermal contributions of LCZs and their spatial heating/cooling effects were different among five distinct climate backgrounds, which implies that targeted measures must be used in different macroclimates. Full article

(This article belongs to the Special Issue Urban Planning Supported by Remote Sensing Technology)

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26 pages, 9282 KiB

Open AccessArticle

A European-Chinese Exploration: Part 2—Urban Ecosystem Service Patterns, Processes, and Contributions to Environmental Equity under Different Scenarios

by Wanben Wu, Xiangyu Luo, Julius Knopp, Laurence Jones and Ellen Banzhaf

Remote Sens. 2022, 14(14), 3488; https://doi.org/10.3390/rs14143488 - 21 Jul 2022

Cited by 6 | Viewed by 2615

Abstract

Urban expansion and ecological restoration policies can simultaneously affect land-cover changes and further affect ecosystem services (ES). However, it is unclear whether and to what extent the distribution and equity of urban ES are influenced by the stage of urban development and government policies. This study aims to assess the quantity and equity of ES under different scenarios in cites of China and Europe. Firstly, we used the Conversion of Land Use and its Effects at Small regional extent (CLUE-S) model to simulate future land cover under three scenarios: business-as-usual (BAU), a market-liberal scenario (MLS), and an ecological protection scenario (EPS). Then using ecosystem service model approaches and the landscape analysis, the dynamics of green infrastructure (GI) fraction and connectivity, carbon sequestration, and PM_2.5 removal were further evaluated. The results show that: (1) over the past 20 years, Chinese cities have experienced dramatic changes in land cover and ES relative to European cities. (2) Two metropolises in China, Shanghai and Beijing have experienced an increase in the fraction and connectivity of GI and ES in the long-term built-up areas between 2010 and 2020. (3) EPS scenarios are not only effective in increasing the quantity of ES but also in improving the equity of ES distribution. The proposed framework as well as the results may provide important guidance for future urban planning and sustainable city development. Full article

(This article belongs to the Special Issue Urban Planning Supported by Remote Sensing Technology)

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24 pages, 14287 KiB

Open AccessArticle

Ha Long—Cam Pha Cities Evolution Analysis Utilizing Remote Sensing Data

by Giang Cong Nguyen, Khac Vu Dang, Tuan Anh Vu, Anh Khac Nguyen and Christiane Weber

Remote Sens. 2022, 14(5), 1241; https://doi.org/10.3390/rs14051241 - 3 Mar 2022

Cited by 3 | Viewed by 3839

Abstract

Socio-economic development has promoted the modification of land cover patterns in the coastal area of Ha Long, Cam Pha cities since the 1990s. The urban growth, together with intensive coal mining activities, has improved the life quality of residents. However, it has also caused many environmental problems in this region. Change detection techniques based on post-classification comparison were applied for monitoring the spatial and temporal evolution of land covers. The confusion matrix for 2001 and 2019 showed high overall accuracy (97.99%, 94.95%) and Kappa coefficient (0.97, 0.92), respectively. Statistics from classified images have revealed that man-made features increased by about 15.32%, while natural features, mangrove jungles, and water bodies decreased 10.64%, 1.96%, 2.72%, respectively, and urban evolution presents various dynamics, soft in the first period (1991–2001), but stronger in the second period (2001–2019) with different characteristics. The study also expresses the constraint of topographic and geologic resources, which have prevented the urban development in this coastal area. Such obtained results are very important for understanding interactions and relations between natural and human phenomena and they may help authorities by providing indicators and maps able to highlight necessary actions for sustainable development. Full article

(This article belongs to the Special Issue Urban Planning Supported by Remote Sensing Technology)

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19 pages, 10874 KiB

Open AccessArticle

Spatiotemporal Patterns and Driving Force of Urbanization and Its Impact on Urban Ecology

by Meng Zhang, Huaqiang Du, Guomo Zhou, Fangjie Mao, Xuejian Li, Lv Zhou, Di’en Zhu, Yanxin Xu and Zihao Huang

Remote Sens. 2022, 14(5), 1160; https://doi.org/10.3390/rs14051160 - 26 Feb 2022

Cited by 20 | Viewed by 3138

Abstract

Urbanization inevitably poses a threat to urban ecology by altering its external structure and internal attributes. Nighttime light (NTL) has become increasingly extensive and practical, offering a special perspective on the world in revealing urbanization. In this study, we applied the Normalized Impervious Surface Index (NISI) constructed by NTL and MODIS NDVI to examine the urbanization process in the Yangtze River Delta (YRD). Geographical detectors combined with factors involving human and natural influences were utilized to investigate the drive mechanism. Urban ecology stress was evaluated based on changes in urban morphological patterns and fractional vegetation cover (FVC). The results showed that the NISI can largely overcome the obstacle of directly coupling NTL data in performing urbanization and has efficient applicability in the long-term pixel scale. Built-up areas in the YRD increased by 2.83 times during the past two decades, from 2053.5 to 7872.5 km². Urbanization intensity has saturated the city center and is spilling over into the suburbs, which show a “cold to hot” spatial clustering distribution. Economic factors are the primary forces driving urbanization, and road network density is becoming essential as factor that reflects urban infrastructure. Urban geometry pattern changes in fractal dimension (FD) and compactness revealed the ecological stress from changing urban external structure, and internal ecological stress was clear from the negative effect on 63.4% FVC. This impact gradually increased in urban expanded area and synchronously decreased when urbanization saturated the core area. An analysis of ecological stress caused by urbanization from changing physical structure and social attributes can provide evidence for urban management and coordinated development. Full article

(This article belongs to the Special Issue Urban Planning Supported by Remote Sensing Technology)

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25 pages, 9156 KiB

Open AccessArticle

Monitoring and Forecasting of Urban Expansion Using Machine Learning-Based Techniques and Remotely Sensed Data: A Case Study of Gharbia Governorate, Egypt

by Eman Mostafa, Xuxiang Li, Mohammed Sadek and Jacqueline Fifame Dossou

Remote Sens. 2021, 13(22), 4498; https://doi.org/10.3390/rs13224498 - 9 Nov 2021

Cited by 15 | Viewed by 4737

Abstract

Rapid population growth is the main driver of the accelerating urban sprawl into agricultural lands in Egypt. This is particularly obvious in governorates where there is no desert backyard (e.g., Gharbia) for urban expansion. This work presents an overview of machine learning-based and state-of-the-art remote sensing products and methodologies to address the issue of random urban expansion, which negatively impacts environmental sustainability. The study aims (1) to investigate the land-use/land-cover (LULC) changes over the past 27 years, and to simulate the future LULC dynamics over Gharbia; and (2) to produce an Urbanization Risk Map in order for the decision-makers to be informed of the districts with priority for sustainable planning. Time-series Landsat images were utilized to analyze the historical LULC change between 1991 and 2018, and to predict the LULC change by 2033 and 2048 based on a logistic regression–Markov chain model. The results show that there is a rapid urbanization trend corresponding to a diminution of the agricultural land. The agricultural sector represented 91.2% of the total land area in 1991, which was reduced to 83.7% in 2018. The built-up area exhibited a similar (but reversed) pattern. The results further reveal that the observed LULC dynamics will continue in a like manner in the future, confirming a remarkable urban sprawl over the agricultural land from 2018 to 2048. The cultivated land changes have a strong negative correlation with the built-up cover changes (the R² were 0.73 in 1991–2003, and 0.99 in 2003–2018, respectively). Based on the Fuzzy TOPSIS technique, Mahalla Kubra and Tanta are the districts which were most susceptible to the undesirable environmental and socioeconomic impacts of the persistent urbanization. Such an unplanned loss of the fertile agricultural lands of the Nile Delta could negatively influence the production of premium agricultural crops for the local market and export. This study is substantial for the understanding of future trends of LULC changes, and for the proposal of alternative policies to reduce urban sprawl on fertile agricultural lands. Full article

(This article belongs to the Special Issue Urban Planning Supported by Remote Sensing Technology)

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