Special Issue "Remote Sensing Based Fine-Scale Urban Thermal Environment"

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

Deadline for manuscript submissions: closed (31 August 2019).

Special Issue Editors

Prof. Dr. Jun Liu
E-Mail Website
Guest Editor
Tourism School, Sichuan University, Sichuan, 610064, China
Interests: sustainable tourism; impact of climate change on vegetation landscape; phenology and tourism; carbon emissions of tourism
Special Issues and Collections in MDPI journals
Dr. Jianhong (Cecilia) Xia
E-Mail Website
Guest Editor
School of Earth and Planetary Sciences, Curtin University, Perth, WA 6845, 92667563, Australia
Interests: Geographic Information Systems; Spatial analysis and modelling; public transport development; driving; spatial navigation and wayfinding; human mobility
Special Issues and Collections in MDPI journals
Dr. Yaohuan Huang
E-Mail Website
Guest Editor
State Key Lab of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
Interests: remote sensing application in urban environment, ecosystem, hydrology; land use and land cover change; GIS application; UAV based remote sensing

Special Issue Information

Dear Colleagues,

As population and the economy increase, world‐wide urbanization is an irreversible trend. Rapid urbanization has improved various aspects of human living conditions. However, global climate change resulting from urbanization has also negatively affected the quality and comfort of urban living. Researchers have explored two broad categories of factors underpinning global climate change: a) spatial factors—the impacts of changes to the spatial aspects of the Earth’s environment (e.g. land use and land cover change) on climate change at the global scale, intercontinental scale, regional scale; and b) temporal factors, that is, how climate factors vary between different temporal scales such as yearly, seasonal, diurnal, and nocturnal.

In addition to global climate change, urban areas seem to be experiencing stronger climate effects, that is, local heat islands resulting from unreasonable urban morphology and planning as a result of urban sprawl, the high density of impervious surfaces as human-made structures replace vegetation, greenery, and water, the modification of air ventilation patterns from the mutation of built-up structures and the spatial layout, as well as waste heat emissions from residential and industrial sources. Furthermore, high air temperatures amplify air pollution and influence the intensity and frequency of rainfall. In summary, an urban microclimate environment is a response to complex energy and water balances, as well as air movement. More importantly, urban areas host more than half of the growing global population and are responsible for 70% of global greenhouse gas emissions. The urban thermal environment, as part of global climate change, shows more dramatic changes and a more pronounced impact on human health. Therefore, the study of the fine-scale urban thermal environment is of more significance to human beings and sustainable development.

Remote sensing technology will play an important role in urban climate change adaptation (UCCA). Compared with traditional thermal infrared remote sensing technology, 3D photogrammetry and light detection and ranging (LiDAR) could be used to monitor three-dimensional building forms, vegetation canopy, and surface temperature. High-resolution remote sensing satellites can extract refined urban surfaces (urban roads, water bodies, etc.) and building management measures (green roofs and white roofs). High time-resolution satellites can monitor the temporal variation of the urban thermal environment and the impact of vegetation on the urban thermal environment due to phenological characteristics. More remote sensing technologies, e.g. unmanned aerial vehicles (UAV), which could reveal spatio-temporal patterns, and the formation mechanisms and control measures of the fine-scale urban thermal environment, are worth developing.

We are requesting papers for a Special Issue of Remote Sensing on remote sensing-based, fine-scale, urban thermal environments. Specific topics include, but are not limited to

  • Novel data. Newly-developed remote sensing datasets, indices, and sensors for monitoring the fine-scale urban thermal environment, especially the three-dimensional thermal environment.
  • New Technologies. New remote sensing technologies for retrieving parameters related to fine-scale urban thermal environment monitoring. Especially UAVs.
  • Applied research. Remote sensing applications for the parameterization of refined urban surfaces in urban climate simulation models.
  • Basic scientific research. New remote sensing methodologies and technologies for temporal and spatial patterns, formation mechanisms and control measures of the fine-scale urban thermal environment.
  • Engineering practice research. Fine-scale engineering practices (green roofs, white roofs, ventilation corridor, etc.) for adapting and mitigating the urban thermal environment based on remote sensing design.
  • Management policy research. Remote sensing-based refined management and control policies of the influence of human activities (urban planning, anthropogenic heat emissions, energy use, population density and structure, transportation, tourism, etc.) on the urban thermal environment.

We especially encourage submissions that combine different methodologies such as remote sensing, geographic information systems, numerical simulations, urban planning and design, etc., to understand the overarching topic.

Prof. Jun Liu
Assoc. Prof. Jianhong (Cecilia) Xia
Dr. Yaohuan Huang
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 papers will be 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 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

  • Fine-Scale Urban Thermal Environments
  • High Temporal and Spatial Resolutions
  • Urban Climate Change Adaptation
  • Management Policy
  • Remote Sensing

Published Papers (2 papers)

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Research

Open AccessArticle
Quantifying the Effects of Urban Form on Land Surface Temperature in Subtropical High-Density Urban Areas Using Machine Learning
Remote Sens. 2019, 11(8), 959; https://doi.org/10.3390/rs11080959 - 22 Apr 2019
Cited by 18 | Viewed by 1679
Abstract
It is widely acknowledged that urban form significantly affects urban thermal environment, which is a key element to adapt and mitigate extreme high temperature weather in high-density urban areas. However, few studies have discussed the impact of physical urban form features on the [...] Read more.
It is widely acknowledged that urban form significantly affects urban thermal environment, which is a key element to adapt and mitigate extreme high temperature weather in high-density urban areas. However, few studies have discussed the impact of physical urban form features on the land surface temperature (LST) from a perspective of comprehensive urban spatial structures. This study used the ordinary least-squares regression (OLS) and random forest regression (RF) to distinguish the relative contributions of urban form metrics on LST at three observation scales. Results of this study indicate that more than 90% of the LST variations were explained by selected urban form metrics using RF. Effects of the magnitude and direction of urban form metrics on LST varied with the changes of seasons and observation scales. Overall, building morphology and urban ecological infrastructure had dominant effects on LST variations in high-density urban centers. Urban green space and water bodies demonstrated stronger cooling effects, especially in summer. Building density (BD) exhibited significant positive effects on LST, whereas the floor area ratio (FAR) showed a negative influence on LST. The results can be applied to investigate and implement urban thermal environment mitigation planning for city managers and planners. Full article
(This article belongs to the Special Issue Remote Sensing Based Fine-Scale Urban Thermal Environment)
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Open AccessArticle
Estimation of Cargo Handling Capacity of Coastal Ports in China Based on Panel Model and DMSP-OLS Nighttime Light Data
Remote Sens. 2019, 11(5), 582; https://doi.org/10.3390/rs11050582 - 10 Mar 2019
Cited by 3 | Viewed by 1671
Abstract
The cargo handling capacity of a port is the most basic and important indicator of port size. Based on the Defense Meteorological Satellite Program-Operational Linescan System (DMSP-OLS) nighttime light data and panel model, this study attempts to estimate the cargo handling capacity of [...] Read more.
The cargo handling capacity of a port is the most basic and important indicator of port size. Based on the Defense Meteorological Satellite Program-Operational Linescan System (DMSP-OLS) nighttime light data and panel model, this study attempts to estimate the cargo handling capacity of 28 coastal ports in China using satellite remote sensing. The study confirmed that there is a very close correlation between DMSP-OLS nighttime light data and the cargo handling capacity of the ports. Based on this correlation, the panel data model was established for remote sensing-based estimation of cargo handling capacity at the port and port group scales. The test results confirm that the nighttime light data can be used to accurately estimate the cargo handling capacity of Chinese ports, especially for the Yangtze River Delta Port Group, Pearl River Delta Port Group, Southeast Coastal Port Group, and Southwest Coastal Port Group that possess huge cargo handling capacities. The high accuracy of the model reveals that the remote sensing analysis method can make up for the lack of statistical data to a certain extent, which helps to scientifically analyze the spatiotemporal dynamic changes of coastal ports, provides a strong basis for decision-making regarding port development, and more importantly provides a convenient estimation method for areas that have long lacked statistical data on cargo handling capacity. Full article
(This article belongs to the Special Issue Remote Sensing Based Fine-Scale Urban Thermal Environment)
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