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Applied Sciences
Special Issues
Remote Sensing for Lands and Sustainable Cities
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Remote Sensing for Lands and Sustainable Cities

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

Deadline for manuscript submissions: closed (20 March 2023) | Viewed by 10999

Special Issue Editors

Dr. Zhongchang Sun

E-Mail Website
Guest Editor
Key Laboratory of Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
Interests: cities; Sustainable Development Goals; city planning
Special Issues, Collections and Topics in MDPI journals
Dr. Mingquan Wu

E-Mail Website
Guest Editor
State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Science, Beijing 100101, China
Interests: industrial park; infrastructure; urban pollution monitoring; Sustainable Development Goals
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues, 

We are inviting submissions to a Special Issue on Remote Sensing for Lands and Sustainable Cities.

“Big city disease” is one of the main problems faced in the process of urban development. To this end, the United Nations' 2030 Sustainable Development Goals include sustainable urbanization as one of the main goals. Remote sensing and other spatial information technologies are playing an increasingly important role in sustainable urbanization. The main research fields include the remote-sensing extraction of urban elements such as urban area, slum distribution, green space and land use information; urban spatial planning and layout assisted by remote sensing monitoring of urban land use; remote sensing assessment of urban disasters and emergency relief; urban development time series remote sensing analysis; and urban pollution monitoring. 

In this Special Issue, we invite submissions exploring cutting-edge research and recent advances in the fields of Remote Sensing for Lands and Sustainable Cities. Research on SDG 11 of the UN's 2030 Sustainable Development Goals is particularly welcome.

Dr. Zhongchang Sun
Dr. Mingquan Wu
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

  • cities
  • Sustainable Development Goals
  • city planning
  • urban disaster
  • industrial parks
  • infrastructure
  • urban pollution monitoring

Published Papers (6 papers)

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Research

15 pages, 1329 KiB  
Article
The Impact of Polycentric Structure on CO2 Emissions: Evidence from China
by Jing Wen, Xin Zhang, Wenjie Du, Xiaoying Ouyang and Zhongchang Sun
Appl. Sci. 2023, 13(10), 5928; https://doi.org/10.3390/app13105928 - 11 May 2023
Viewed by 1092
Abstract
Driven by the 2030 Agenda for Sustainable Development, the importance of sustainable urbanization has taken center stage. In this study, we investigate the impact of polycentric structures on CO2 emissions using data from 279 Chinese cities and employing two-way fixed effects complemented [...] Read more.
Driven by the 2030 Agenda for Sustainable Development, the importance of sustainable urbanization has taken center stage. In this study, we investigate the impact of polycentric structures on CO2 emissions using data from 279 Chinese cities and employing two-way fixed effects complemented by instrumental variables. Our findings indicate that polycentric structures effectively alleviate CO2 emissions. We identify two key pathways through which polycentric structures contribute to CO2 reduction: promoting green technology and curbing energy consumption. Additionally, we discover that these relationships are influenced by market integration levels and resource dependency. This research offers valuable insights into the future development of sustainable urban spatial structures, paving the way for more eco-friendly cities around the globe. Full article
(This article belongs to the Special Issue Remote Sensing for Lands and Sustainable Cities)
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15 pages, 19179 KiB  
Article
Modeling and Predicting Urban Expansion in South Korea Using Explainable Artificial Intelligence (XAI) Model
by Minjun Kim and Geunhan Kim
Appl. Sci. 2022, 12(18), 9169; https://doi.org/10.3390/app12189169 - 13 Sep 2022
Cited by 4 | Viewed by 2001
Abstract
Over the past few decades, most cities worldwide have experienced a rapid expansion with unprecedented population growth and industrialization. Currently, half of the world’s population is living in urban areas, which only account for less than 1% of the Earth. A rapid and [...] Read more.
Over the past few decades, most cities worldwide have experienced a rapid expansion with unprecedented population growth and industrialization. Currently, half of the world’s population is living in urban areas, which only account for less than 1% of the Earth. A rapid and unplanned urban expansion, however, has also resulted in serious challenges to sustainable development of the cities, such as traffic congestion and loss of natural environment and open spaces. This study aims at modeling and predicting the expansion of urban areas in South Korea by utilizing an explainable artificial intelligence (XAI) model. To this end, the study utilized the land-cover maps in 2007 and 2019, as well as several socioeconomic, physical, and environmental attributes. The findings of this study suggest that the urban expansion tends to be promoted when a certain area is close to economically developed area with gentle topography. In addition, the existence of mountainous area and legislative regulations on land use were found to significantly reduce the possibility of urban expansion. Compared to previous studies, this study is novel in that it captures the relative importance of various influencing factors in predicting the urban expansion by integrating the XGBoost model and SHAP values. Full article
(This article belongs to the Special Issue Remote Sensing for Lands and Sustainable Cities)
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15 pages, 2816 KiB  
Article
Incorporating Ecological Constraints into the Simulations of Tropical Urban Growth Boundaries: A Case Study of Sanya City on Hainan Island, China
by Nianlong Han, Ke Hu, Miao Yu, Peihong Jia and Yiqing Zhang
Appl. Sci. 2022, 12(13), 6409; https://doi.org/10.3390/app12136409 - 23 Jun 2022
Cited by 11 | Viewed by 2058
Abstract
The rapid expansion of cities in tropical regions has triggered a series of problems such as the destruction of rare natural resources and decreases in the environmental resource carrying capacity and ecological security, which seriously threaten the sustainable development of tropical cities. In [...] Read more.
The rapid expansion of cities in tropical regions has triggered a series of problems such as the destruction of rare natural resources and decreases in the environmental resource carrying capacity and ecological security, which seriously threaten the sustainable development of tropical cities. In this study, the city of Sanya, Hainan, China, is taken as an example. A bottom-line ecological security pattern is constructed based on the remote sensing ecological index (RSEI) and the patch-generating land use simulation (PLUS) for urban growth boundary (UGB) delineation. The results show that Sanya has a good ecological background, but the overall ecological quality decreased from 2014 to 2018 due to the expansion of construction in hot spot areas. Under the natural growth scenario, the urban built-up area in Sanya in 2030 will be 73.81% greater than in 2018, mainly occupying a large amount of agricultural and ecological space, and urban expansion will not be effectively suppressed. Delineation of the UGBs combined with the ecological constraints can effectively protect the regional ecological security and control the urban sprawl, which is relatively consistent with the current planning. The results of this study demonstrate that the RSEI-PLUS-based UGB delineation perspective has a high scientific and applicability, and they provide a reference for the coordinated ecological–economic sustainable development of ecologically fragile cities in tropical areas. Full article
(This article belongs to the Special Issue Remote Sensing for Lands and Sustainable Cities)
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19 pages, 13103 KiB  
Article
The Transformation and Development Strategy of Waterside Villages through Transport System Reconstruction: A Case Study of Anxin County, Hebei Province, China
by Chaoqun Wang and Jie He
Appl. Sci. 2022, 12(12), 6142; https://doi.org/10.3390/app12126142 - 16 Jun 2022
Cited by 1 | Viewed by 1751
Abstract
The main method of transportation of waterside villages has changed from water to land transportation because of water conservation policies, dried-up rivers, or other reasons around the Baiyangdian Lake area. To guide waterside villages around Baiyangdian Lake to adapt to modern transport systems [...] Read more.
The main method of transportation of waterside villages has changed from water to land transportation because of water conservation policies, dried-up rivers, or other reasons around the Baiyangdian Lake area. To guide waterside villages around Baiyangdian Lake to adapt to modern transport systems and deal with the urbanization waves in China, this study first measured temporal accessibility and potential change under land transportation by spatial centrality indices at three different points in time (1964, 1996, and 2008) from the historical road system we reconstructed. Then, based on these indices, we proposed a village structure for decision-making support. The results show that (1) the connectivity between the road network and water in Anxin County was weakened from 1964–2008. (2) Villages with high accessibility have changed from relying on water to clustering, homogeneity, and following main highways. (3) Villages with high potential have changed from meeting the previous conditions of being close to water or main highways to having both main roads and a cluster of other villages in the vicinity. (4) Anxin County′s waterside villages can be divided into core villages, sub-core villages, connectivity villages, and sub-villages. The spatial structure formed by these four types is not only adapted to the modern transport system but also can serve the purpose of land consolidation or residential mobility focused by local government. Full article
(This article belongs to the Special Issue Remote Sensing for Lands and Sustainable Cities)
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16 pages, 14843 KiB  
Article
Urban Expansion Monitoring Based on the Digital Surface Model—A Case Study of the Beijing–Tianjin–Hebei Plain
by Yanping Wang, Pinliang Dong, Shunbao Liao, Yueqin Zhu, Da Zhang and Na Yin
Appl. Sci. 2022, 12(11), 5312; https://doi.org/10.3390/app12115312 - 24 May 2022
Cited by 4 | Viewed by 1323
Abstract
Although urban expansion statistics have been widely carried out, large-scale and rapid monitoring is still worth doing in order to improve the efficiency of statistics, as well as make up for the omissions and deficiencies of construction expansion statistics with multi-year intervals. This [...] Read more.
Although urban expansion statistics have been widely carried out, large-scale and rapid monitoring is still worth doing in order to improve the efficiency of statistics, as well as make up for the omissions and deficiencies of construction expansion statistics with multi-year intervals. This paper presents a study of urban expansion in the Beijing–Tianjin–Hebei plain based on ALOS Global Digital Surface Model “ALOS World 3D-30 m” (AW3D30 DSM), Shuttle Radar Topography Mission (SRTM) DSM, and Landsat 7 ETM+ images. Through the evaluation of errors and the elimination of non-building changes, a relatively objective result is derived. The neighborhood block statistics of the construction height expansion reveal that from 2000 to 2009, the largest centralized construction expansion mainly occurred between the Second Ring Road and the Fifth Ring Road of Beijing, followed by Yizhuang, Shunyi, Tianjin Central City, and Langfang. Zonal statistics also show a significant imbalance in the expansion of construction in the counties of the Beijing–Tianjin–Hebei plain. For example, Chaoyang, Dongcheng, Xicheng, Xuanwu, Chongwen, Nankai, Heping, and Hexi have a larger construction expansion; however, other counties present a relatively slow rate of building expansion. Furthermore, the correlation coefficient between the statistical average building height expansion per unit area (ABHE, by our method) and the actual average completed building floor space per unit area (ACBFS) derived from the Beijing Statistical Yearbook (BSY) is 0.9436, which proves that this method is feasible. With the continuous improvement of DSM data quality in the future, the method proposed in this paper can provide rapid and large-scale statistics to study more urban construction expansion in the world. Full article
(This article belongs to the Special Issue Remote Sensing for Lands and Sustainable Cities)
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15 pages, 1861 KiB  
Article
Modelling Electricity Consumption in Cambodia Based on Remote Sensing Night-Light Images
by Xumiao Gao, Mingquan Wu, Ju Gao, Li Han, Zheng Niu and Fang Chen
Appl. Sci. 2022, 12(8), 3971; https://doi.org/10.3390/app12083971 - 14 Apr 2022
Cited by 6 | Viewed by 2037
Abstract
The accurate estimation of electricity consumption and its spatial distribution are important in electricity infrastructural planning and the achievement of the United Nations Sustainable Development Goal 7 (SDG7). Electricity consumption can be estimated based on its correlation with nighttime lights observed using remote [...] Read more.
The accurate estimation of electricity consumption and its spatial distribution are important in electricity infrastructural planning and the achievement of the United Nations Sustainable Development Goal 7 (SDG7). Electricity consumption can be estimated based on its correlation with nighttime lights observed using remote sensing imagery. Since night-light images are easily affected by cloud cover, few previous studies have estimated electricity consumption in cloudy areas. Taking Cambodia as an example, the present study proposes a method for denoising night-light images in cloudy areas and estimating electricity consumption. The results show that an exponential model is superior to linear and power function models for modelling the relationship between total night-light data and electricity consumption in Cambodia. The month-specific substitution method is best for annual night-light image synthesis in cloudy areas. Cambodia’s greatest electricity consumption occurs in its four most economically developed cities. Electricity consumption spreads outwards from these cities along the main transport routes to a large number of unelectrified areas. Full article
(This article belongs to the Special Issue Remote Sensing for Lands and Sustainable Cities)
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