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Special Issue "Satellite Remote Sensing of Urban Thermal Environment: Progresses, Challenges, and Opportunities"

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

Deadline for manuscript submissions: 31 January 2020.

Special Issue Editors

Guest Editor
Dr. Yuyu Zhou

Dept. of Geological & Atmospheric Sciences, Iowa State University, 3019 Agronomy Hall, Ames, IA 50011, USA
Website | E-Mail
Phone: +1-515-2942842
Interests: urban remote sensing, urbanization, urban heat island, building energy use, vegetation phenology
Guest Editor
Dr. Weiqi Zhou

State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, 18 Shuangqing Road, Haidian District, Beijing, China
E-Mail
Phone: 86-10-62849268
Interests: urban remote sensing, urban ecology, landscape ecology, urban heat island, object-based image analysis
Guest Editor
Dr. Bailang Yu

Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai, China
Website | E-Mail
Phone: +86-21-54341172
Fax: +86-21-5434-1172
Interests: nighttime light remote sensing, urban remote sensing, object-oriented analysis for remotely sensed images, LiDaR (Light Detection and Ranging)
Guest Editor
Dr. Wenfeng Zhan

International Institute for Earth System Science, Nanjing University, Nanjing, Jiangsu 210023, China
Website | E-Mail
Interests: thermal remote sensing, land surface temperature, urban remote sensing, urban heat island, urban climate
Guest Editor
Dr. Decheng Zhou

Jiangsu Key Laboratory of Agricultural Meteorology, Nanjing University of Information Science and Technology, No.219 Ningliu Road, Nanjing 210044, China
E-Mail
Interests: urban heat island, urban ecology, land use and land cover change, satellite remote sensing

Special Issue Information

Dear Colleagues,

In the past several decades, the world has experienced fast urbanization, and this trend is expected to continue for decades to come. Urbanization plays an important role in the Earth system through modifying the terrestrial surfaces and atmospheric composition. Especially, urbanization changes the thermal environment in urban areas by creating the phenomenon of urban heat islands (UHI), with higher temperatures in urban areas compared to their surrounding rural areas. UHI has a significant socioeconomic and environmental impact, such as increasing cooling energy use, altering vegetation phenology, and affecting the health of urban dwellers, from local, to regional, and even global scales. As a result, UHI will pose challenges for environmental sustainability with its significant adverse impacts on human activities and natural processes. There is a growing need, from both the science and policy making communities, for science-based information and knowledge on the urban thermal environment and its drivers and impact from local to global scales. An improved understanding of the urban thermal environment can help us develop better practices in land use planning and management for urban sustainability.

Satellite remote sensing plays an irreplaceable role in understanding our urban thermal environment. With the rapid development of remote sensing technologies and algorithms, this Special Issue invites original manuscripts on the latest research and advancement in the remote sensing of the urban thermal environment. Potential topics include but are not limited to the following:

  • New methods for quantifying surface and air UHI;
  • Improvements in land surface and air temperate data for UHI studies;
  • Relationship between surface and air UHI;
  • Innovative findings on spatial and temporal patterns of UHI;
  • UHI studies in understudied regions or cities;
  • Evaluations of UHI drivers (e.g., urban composition and configuration);
  • Cooling effects of green and blue spaces;
  • Predicting and modelling UHI;
  • The investigation of UHI impacts on human activities (e.g., building energy use and heat related illness);
  • The investigation of UHI impacts on natural processes (e.g., vegetation phenology);
  • Mitigation and adaptation measures of UHI.

Dr. Yuyu Zhou
Dr. Weiqi Zhou
Dr. Bailang Yu
Dr. Wenfeng Zhan
Dr. Decheng Zhou
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 1800 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

  • Urbanization
  • Urban thermal environment
  • Urban heat island
  • Land surface temperature
  • Surface air temperature
  • Thermal remote sensing
  • Drivers and effects
  • Impervious surface area
  • Urban greenspace
  • Urban composition and configuration
  • Building energy use
  • Vegetation phenology
  • Heat-related illnesses
  • Mitigation and adaptation

Published Papers (4 papers)

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Research

Open AccessArticle
Determining the Boundary and Probability of Surface Urban Heat Island Footprint Based on a Logistic Model
Remote Sens. 2019, 11(11), 1368; https://doi.org/10.3390/rs11111368
Received: 17 April 2019 / Revised: 27 May 2019 / Accepted: 3 June 2019 / Published: 6 June 2019
PDF Full-text (6367 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Studies of the spatial extent of surface urban heat island (SUHI or UHISurf) effects require precise determination of the footprint (FP) boundary. Currently available methods overestimate or underestimate the SUHI FP boundary, and can even alter its morphology, due to theoretical [...] Read more.
Studies of the spatial extent of surface urban heat island (SUHI or UHISurf) effects require precise determination of the footprint (FP) boundary. Currently available methods overestimate or underestimate the SUHI FP boundary, and can even alter its morphology, due to theoretical limitations on the ability of their algorithms to accurately determine the impacts of the shape, topography, and landscape heterogeneity of the city. The key to determining the FP boundary is identifying background temperatures in reference rural regions. Due to the instability of remote sensing data, these background temperatures should be determined automatically rather than manually, to eliminate artificial bias. To address this need, we developed an algorithm that adequately represents the decay of land surface temperature (LST) from the urban center to surrounding rural regions, and automatically calculates thresholds for reference rural LSTs in all directions based on a logistic curve. In this study, we applied this algorithm with data from the Aqua Moderate Resolution Imaging Spectroradiometer (Aqua/MODIS) 8-day level 3 (L3) LST global grid product to delineate precise SUHI FPs for the Beijing metropolitan area during the summers of 2004–2018 and determine the interannual and diurnal variations in FP boundaries and their relationship with SUHI intensity. Full article
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Open AccessArticle
Four-band Thermal Mosaicking: A New Method to Process Infrared Thermal Imagery of Urban Landscapes from UAV Flights
Remote Sens. 2019, 11(11), 1365; https://doi.org/10.3390/rs11111365
Received: 21 April 2019 / Revised: 25 May 2019 / Accepted: 4 June 2019 / Published: 6 June 2019
PDF Full-text (3481 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Unmanned aerial vehicles (UAVs) support a large array of technological applications and scientific studies due to their ability to collect high-resolution image data. The processing of UAV data requires the use of mosaicking technology, such as structure-from-motion, which combines multiple photos to form [...] Read more.
Unmanned aerial vehicles (UAVs) support a large array of technological applications and scientific studies due to their ability to collect high-resolution image data. The processing of UAV data requires the use of mosaicking technology, such as structure-from-motion, which combines multiple photos to form a single image mosaic and to construct a 3-D digital model of the measurement target. However, the mosaicking of thermal images is challenging due to low lens resolution and weak contrast in the single thermal band. In this study, a novel method, referred to as four-band thermal mosaicking (FTM), was developed in order to process thermal images. The method stacks the thermal band obtained by a thermal camera onto the RGB bands acquired on the same flight by an RGB camera and mosaics the four bands simultaneously. An object-based calibration method is then used to eliminate inter-band positional errors. A UAV flight over a natural park was carried out in order to test the method. The results demonstrated that with the assistance of the high-resolution RGB bands, the method enabled successful and efficient thermal mosaicking. Transect analysis revealed an inter-band accuracy of 0.39 m or 0.68 times the ground pixel size of the thermal camera. A cluster analysis validated that the thermal mosaic captured the expected contrast of thermal properties between different surfaces within the scene. Full article
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Open AccessArticle
Investigating Surface Urban Heat Islands in South America Based on MODIS Data from 2003–2016
Remote Sens. 2019, 11(10), 1212; https://doi.org/10.3390/rs11101212
Received: 10 May 2019 / Revised: 18 May 2019 / Accepted: 20 May 2019 / Published: 22 May 2019
PDF Full-text (2740 KB) | HTML Full-text | XML Full-text
Abstract
Surface urban heat islands (SUHIs) have been investigated in many regions around the world, but little attention has been given with regard to SUHIs in South America. In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) data was used to [...] Read more.
Surface urban heat islands (SUHIs) have been investigated in many regions around the world, but little attention has been given with regard to SUHIs in South America. In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) data was used to investigate the diurnal, seasonal, and interannual variations in the SUHI intensity (SUHII, the urban LST minus the rural LST) in 44 South American cities in different climate zones and types of rural land. To examine the effects of factors that may influence the SUHII, correlations between the SUHII and the enhanced vegetation index (EVI), urban area, population, altitude, and anthropogenic heat emissions were performed. The results showed that the SUHI effect was obvious in South America. The mean daytime SUHII was higher than the mean night-time SUHII in all areas except for the arid climate zone. In the daytime, the summer displayed a stronger SUHII in the warm temperate climate zone than the other seasons. The night-time SUHII showed less obvious seasonal variations. In addition, the surrounding land cover influenced the SUHII. During the day, the SUHII was therefore stronger in rural areas that were covered by forests than in other types of rural land. Interannually, most cities showed an insignificant temporal trend in the SUHII from 2003 to 2016. The daytime SUHII was significantly and negatively correlated with the ∆EVI (the urban EVI minus the rural EVI) across the 44 cities, but a poor relationship was observed at night. In addition, anthropogenic heat emissions were positively correlated with the night-time SUHII. Urban area, population, and altitude were weakly correlated with the SUHII, which suggested that these factors may not have a significant impact on the spatial variations in the SUHII in South America. Full article
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Graphical abstract

Open AccessArticle
Study of the Seasonal Effect of Building Shadows on Urban Land Surface Temperatures Based on Remote Sensing Data
Remote Sens. 2019, 11(5), 497; https://doi.org/10.3390/rs11050497
Received: 17 January 2019 / Revised: 22 February 2019 / Accepted: 25 February 2019 / Published: 1 March 2019
PDF Full-text (6395 KB) | HTML Full-text | XML Full-text
Abstract
Building shadows (BSs) frequently occur in urban areas, and their area and distribution display strong seasonal variations that significantly influence the urban land surface temperature (LST). However, it remains unclear how BSs affect the LST at the city scale because it is difficult [...] Read more.
Building shadows (BSs) frequently occur in urban areas, and their area and distribution display strong seasonal variations that significantly influence the urban land surface temperature (LST). However, it remains unclear how BSs affect the LST at the city scale because it is difficult to extract the shaded area at the subpixel scale and to connect such areas with the LST at the pixel scale. In this study, we combined the sun angle, building height, building footprint and building occlusion to extract the seasonal spatial distribution of BSs in the central area of Beijing. The effect of BSs on the LST was analyzed using LST retrieved from Landsat-8 thermal infrared sensor data. First, the relationship between the LST patch fragmentation and proportion of BSs in the sample areas was modeled without vegetation. Then, we quantitatively studied the mitigated intensity of the LST in pure impervious surfaces (IS) and vegetation pixels covered by BSs; next, we analyzed the LST sensitivity of these pixels to BSs. The results showed that the existence of BSs influences the fragmentation of the low LST patches strongly from summer to winter. On the other hand, pure IS pixels totally covered by BSs experienced a greater cooling effect, with 3.16 K on 10 July, and the lowest cooling occurred between 14 and 25 December, with a mean of 1.24 K. Without considering the relationship in winter, the LST is nonlinearly correlated to the building shadows ratio (BSR) in pixels, and an approximate 10% increase in the BSR resulted in decreases in the LST of approximately 0.33 K (mean of 16 April and 10 May), 0.37 K (10 July) and 0.24 K (28 September) for pure IS pixels, and 0.18 K, 0.20 K and 0.15 K, respectively, for pure vegetation pixels. Further analysis indicates that the LST of pure IS pixels is more sensitive to BSs than that of vegetation because the self-regulation mechanism of vegetation reduces the cooling effect of BSs. These findings can help urban planners understand the cooling characteristics of BSs and design suitable urban forms to resist urban heat islands (UHIs). Full article
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