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27 pages, 14211 KiB

Open AccessArticle

Synergising Machine Learning and Remote Sensing for Urban Heat Island Dynamics: A Comprehensive Modelling Approach

by Guglielmina Mutani, Alessandro Scalise, Xhoana Sufa and Stefania Grasso

Atmosphere 2024, 15(12), 1435; https://doi.org/10.3390/atmos15121435 - 29 Nov 2024

Viewed by 284

Abstract

This study evaluates the effectiveness of sustainable urban regeneration projects in mitigating Urban Heat Island (UHI) effects through a place-based approach. Geographic Information Systems (GIS) and satellite imagery were integrated with machine learning (ML) models to analyse the urban environment, human activities, and [...] Read more.

This study evaluates the effectiveness of sustainable urban regeneration projects in mitigating Urban Heat Island (UHI) effects through a place-based approach. Geographic Information Systems (GIS) and satellite imagery were integrated with machine learning (ML) models to analyse the urban environment, human activities, and climate data in Turin, Italy. A detailed analysis of the ex-industrial Teksid area revealed a significant reduction in Surface Urban Heat Island Intensity (SUHII), with decreases of −0.94 in summer and −0.54 in winter following regeneration interventions. Using 17 variables in the Random Forest model, key determinants influencing SUHII were identified, including building density, vegetation cover, and surface albedo. This study quantitatively highlights the impact of increasing green spaces and enhancing surface materials to improve solar reflectivity, with findings showing a 19.46% increase in vegetation and a 3.09% rise in albedo after mitigation efforts. Furthermore, the results demonstrate that integrating Local Climate Zones (LCZs) into urban planning, alongside interventions targeting these key variables, can further optimise UHI mitigation and assess changes. This comprehensive approach provides policymakers with a robust tool to enhance urban resilience and guide sustainable planning strategies in response to climate change. Full article

(This article belongs to the Special Issue UHI Analysis and Evaluation with Remote Sensing Data)

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17 pages, 6013 KiB

Open AccessArticle

Remote Sensing Monitoring and Multidimensional Impact Factor Analysis of Urban Heat Island Effect in Zhengzhou City

by Xiangjun Zhang, Guoqing Li, Haikun Yu, Guangxu Gao and Zhengfang Lou

Atmosphere 2024, 15(9), 1097; https://doi.org/10.3390/atmos15091097 - 9 Sep 2024

Viewed by 726

Abstract

In the 21st century, the rapid urbanization process has led to increasingly severe urban heat island effects and other urban thermal environment issues, posing significant challenges to urban planning and environmental management. This study focuses on Zhengzhou, China, utilizing Landsat remote sensing imagery [...] Read more.

In the 21st century, the rapid urbanization process has led to increasingly severe urban heat island effects and other urban thermal environment issues, posing significant challenges to urban planning and environmental management. This study focuses on Zhengzhou, China, utilizing Landsat remote sensing imagery data from five key years between 2000 and 2020. By applying atmospheric correction methods, we accurately retrieved the land surface temperature (LST). The study employed a gravity center migration model to track the spatial changes of heat island patches and used the geographical detector method to quantitatively analyze the combined impact of surface characteristics, meteorological conditions, and socio-economic factors on the urban heat island effect. Results show that the LST in Zhengzhou exhibits a fluctuating growth trend, closely related to the expansion of built-up areas and urban planning. High-temperature zones are mainly concentrated in built-up areas, while low-temperature zones are primarily found in areas covered by water bodies and vegetation. Notably, the Normalized Difference Built-up Index (NDBI) and the Normalized Difference Vegetation Index (NDVI) are the two most significant factors influencing the spatial distribution of land surface temperature, with explanatory power reaching 42.7% and 41.3%, respectively. As urban development enters a stable stage, government environmental management measures have played a positive role in mitigating the urban heat island effect. This study not only provides a scientific basis for understanding the spatiotemporal changes in land surface temperature in Zhengzhou but also offers new technical support for urban planning and management, helping to alleviate the urban heat island effect and improve the living environment quality for urban residents. Full article

(This article belongs to the Special Issue UHI Analysis and Evaluation with Remote Sensing Data)

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23 pages, 6750 KiB

Open AccessArticle

Assessing Satellite Data’s Role in Substituting Ground Measurements for Urban Surfaces Characterization: A Step towards UHI Mitigation

by Davide Parmeggiani, Francesca Despini, Sofia Costanzini, Malvina Silvestri, Federico Rabuffi, Sergio Teggi and Grazia Ghermandi

Atmosphere 2024, 15(5), 551; https://doi.org/10.3390/atmos15050551 - 29 Apr 2024

Viewed by 963

Abstract

Urban surfaces play a crucial role in shaping the Urban Heat Island (UHI) effect by absorbing and retaining significant solar radiation. This paper explores the potential of high-resolution satellite imagery as an alternative method for characterizing urban surfaces to support UHI mitigation strategies [...] Read more.

Urban surfaces play a crucial role in shaping the Urban Heat Island (UHI) effect by absorbing and retaining significant solar radiation. This paper explores the potential of high-resolution satellite imagery as an alternative method for characterizing urban surfaces to support UHI mitigation strategies in urban redevelopment plans. We utilized Landsat images spanning the past 40 years to analyze trends in Land Surface Temperature (LST). Additionally, WorldView-3 (WV3) imagery was acquired for surface characterization, and the results were compared with ground truth measurements using the ASD FieldSpec 4 spectroradiometer. Our findings revealed a strong correlation between satellite-derived surface reflectance and ground truth measurements across various urban surfaces, with Root Mean Square Error (RMSE) values ranging from 0.01 to 0.14. Optimal characterization was observed for surfaces such as bituminous membranes and parking with cobblestones (RMSE < 0.03), although higher RMSE values were noted for tiled roofs, likely due to aging effects. Regarding surface albedo, the differences between satellite-derived data and ground measurements consistently remained below 12% for all surfaces, with the lowest values observed in high heat-absorbing surfaces like bituminous membranes. Despite challenges on certain surfaces, our study highlights the reliability of satellite-derived data for urban surface characterization, thus providing valuable support for UHI mitigation efforts. Full article

(This article belongs to the Special Issue UHI Analysis and Evaluation with Remote Sensing Data)

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20 pages, 10323 KiB

Open AccessArticle

Satellite Time-Series Analysis for Thermal Anomaly Detection in the Naples Urban Area, Italy

by Alessia Scalabrini, Massimo Musacchio, Malvina Silvestri, Federico Rabuffi, Maria Fabrizia Buongiorno and Francesco Salvini

Atmosphere 2024, 15(5), 523; https://doi.org/10.3390/atmos15050523 - 25 Apr 2024

Viewed by 1289

Abstract

Naples is the most densely populated Italian city (7744 inhabitants per km²). It is located in a particular geological context: the presence of Mt Vesuvius characterizes the eastern part, and the western part is characterized by the presence of the Phlegrean [...] Read more.

Naples is the most densely populated Italian city (7744 inhabitants per km²). It is located in a particular geological context: the presence of Mt Vesuvius characterizes the eastern part, and the western part is characterized by the presence of the Phlegrean Fields, making Naples a high-geothermal-gradient region. This endogenous heat, combined with the anthropogenic heat due to intense urbanization, has defined Naples as an ideal location for Surface Urban Heat Island (SUHI) analysis. SUHI analysis was effectuated by acquiring the Land Surface Temperature (LST) over Naples municipality by processing Landsat 8 (L8) Thermal Infrared Sensor (TIRS) images in the 2013–2023 time series by employing Google Earth Engine (GEE). In GEE, two different approaches have been followed to analyze thermal images, starting from the Statistical Mono Window (SMW) algorithm, which computes the LST based on the brightness temperature (Tb), the emissivity value, and the atmospheric correction coefficients. The first one is used for the LST retrieval from daytime images; here, the emissivity component is derived using, firstly, the Normalized Difference Vegetation Index (NDVI) and then the Vegetation Cover Method (VCM), defining the Land Surface Emissivity (LSɛ), which considers solar radiation as the main source of energy. The second approach is used for the LST retrieval from nighttime images, where the emissivity is directly estimated from the Advance Spaceborne Thermal Emission Radiometer database (ASTER-GED), as, during nighttime without solar radiation, the main source of energy is the energy emitted by the Earth’s surface. From these two different algorithms, 123 usable daytime and nighttime LST images were downloaded from GEE and analyzed in Quantum GIS (QGIS). The results show that the SUHI is more concentrated in the eastern part, characterized by intense urbanization, as shown by the Corine Land Cover (CLC). At the same time, lower SUHI intensity is detected in the western part, defined by the Land Cover (LC) vegetated class. Also, in the analysis, we highlighted 40 spots (10 hotspots and 10 coldspots, both for daytime and nighttime collection) that present positive or negative temperature peaks for all the time series. Due to the huge amount of data, this work considered only the five representative spots that were most representative for SUHI analysis and determination of thermal anomalies in the urban environment. Full article

(This article belongs to the Special Issue UHI Analysis and Evaluation with Remote Sensing Data)

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37 pages, 86294 KiB

Open AccessArticle

Make Way for the Wind—Promoting Urban Wind Corridor Planning by Integrating RS, GIS, and CFD in Urban Planning and Design to Mitigate the Heat Island Effect

by Kang-Li Wu and Liang Shan

Atmosphere 2024, 15(3), 257; https://doi.org/10.3390/atmos15030257 - 21 Feb 2024

Cited by 1 | Viewed by 2241 | Correction

Abstract

Under the trend in climate change, global warming, and the increasingly serious urban heat island effect, promoting urban wind corridor planning to reduce urban temperature and mitigate the effect of urban heat islands has received widespread attention in many cities. With emerging awareness [...] Read more.

Under the trend in climate change, global warming, and the increasingly serious urban heat island effect, promoting urban wind corridor planning to reduce urban temperature and mitigate the effect of urban heat islands has received widespread attention in many cities. With emerging awareness of the need to explicitly incorporate climate considerations into urban planning and design, integrating current spatial analysis and simulation tools to enhance urban wind corridor planning to obtain the best urban ventilation effect has become an increasingly important research topic in green city development. However, how to systematically carry out urban wind corridor planning by employing related technology and simulation tools is a topic that needs to be explored urgently in both theory and practice. Taking Zhumadian City in China as an example, this study proposes a method and planning approach that uses remote sensing (RS), geographic information system (GIS), and computational fluid dynamics (CFD) in an integrated way to understand urban landscape and to conduct urban wind corridor planning. The research results reveal that the urban form of Zhumadian City favors the development of urban wind corridors, and that the railway lines and some major roads in the city have the potential to be developed as the city’s main wind corridors. However, there are still ventilation barriers resulting from the existing land use model and building layout patterns that need to be adjusted. In terms of local-level analysis, the CFD simulation analysis also reveals that some common building layout patterns may result in environments with poor ventilation. Finally, based on the results of our empirical analysis and local planning environment, specific suggestions are provided on how to develop appropriate strategies for urban wind corridor planning and adjustments related to land use planning and building layout patterns in order to mitigate the impact of the urban heat island effect. Full article

(This article belongs to the Special Issue UHI Analysis and Evaluation with Remote Sensing Data)

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21 pages, 23955 KiB

Open AccessArticle

Assessing the Impact of Spatiotemporal Land Cover Changes on the Urban Heat Islands in Developing Cities with Landsat Data: A Case Study in Zhanjiang

by Yutian Hu, Hongye Li, Muhammad Amir Siddique and Dongyun Liu

Atmosphere 2023, 14(12), 1716; https://doi.org/10.3390/atmos14121716 - 22 Nov 2023

Cited by 2 | Viewed by 1984

Abstract

Land cover changes (LCCs) due to urbanization cause urban heat islands (UHIs), significantly affecting land surface temperature (LST) through spatiotemporal changes in compositions, parameters, and patterns. Land cover and LST have been studied in various cities; however, indicative research into heterogeneous LCC’s impact [...] Read more.

Land cover changes (LCCs) due to urbanization cause urban heat islands (UHIs), significantly affecting land surface temperature (LST) through spatiotemporal changes in compositions, parameters, and patterns. Land cover and LST have been studied in various cities; however, indicative research into heterogeneous LCC’s impact on LST in less-developed cities remains incomplete. This study analyzed new Landsat images of Zhanjiang, taken from 2004 to 2022, to determine the impact of three LCC indicators (compositions, parameters, and patterns) on LSTs. The urban thermal field variance index (UTFVI) was used to describe the distribution and variation in LST. We also quantified the cooling or warming benefits of various LCCs. The results indicate that the average temperature in the land urban heat island (SUHI) area rose to 30.6 °C. The average temperature of the SUHI was 3.32 °C higher than that of the non-SUHI area, showing the characteristic of shifting to counties and multi-core development. The LST increases by 0.37–0.67 °C with an increase of 0.1 in the normalized difference building index (NDBI), which is greater than the cooling benefit of the normalized difference of vegetation index (NDVI). The impact of landscape pattern indices on impervious surfaces and water is higher than that on vegetation and cropland, with a rising influence on impervious surfaces and a decreasing impact on water. The predominant cooling patches are vegetation and water, while large areas of impervious surface and cropland aggravate UHIs for industrial and agricultural activities. These findings are intended to guide future urban layouts and planning in less-developed cities, with thermal climate mitigation as a guiding principle. Full article

(This article belongs to the Special Issue UHI Analysis and Evaluation with Remote Sensing Data)

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Review

Jump to: Research, Other

20 pages, 6180 KiB

Open AccessReview

Spatiotemporal Patterns of the Application of Surface Urban Heat Island Intensity Calculation Methods

by Jiyuan Zhang, Lili Tu and Biao Shi

Atmosphere 2023, 14(10), 1580; https://doi.org/10.3390/atmos14101580 - 19 Oct 2023

Cited by 5 | Viewed by 1840

Abstract

Using the China National Knowledge Infrastructure (CNKI) and Web of Science (WoS) databases, 487 articles that used remote sensing methods to study the intensity of surface urban heat islands (SUHIs) over the past 20 years were obtained using keyword searches. A multidimensional analysis [...] Read more.

Using the China National Knowledge Infrastructure (CNKI) and Web of Science (WoS) databases, 487 articles that used remote sensing methods to study the intensity of surface urban heat islands (SUHIs) over the past 20 years were obtained using keyword searches. A multidimensional analysis was conducted on these articles from the perspectives of the research methods used, spatiotemporal distribution characteristics of the research area, research development trends, and main challenges. The research found that (1) the growth trend of the various SUHI research methods over the years was similar to the overall trend in the number of publications, which has rapidly increased since 2009. (2) Among the SUHI research methods, temperature dichotomy is the most widely used worldwide; however, defining urban and rural areas is a main challenge. The Gaussian surface and local climate zoning methods have gradually emerged in recent years; however, owing to the limitations of the different urban development levels and scales, these methods require further improvement. (3) There are certain differences in the application of SUHI research methods between China and other countries. Full article

(This article belongs to the Special Issue UHI Analysis and Evaluation with Remote Sensing Data)

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