Mapping spatiotemporal variability of the urban heat island across an urban gradient in Worcester, Massachusetts using in-situ Thermochrons and Landsat-8 Thermal Infrared Sensor (TIRS) data

Elmes, Arthur; Healy, Marc; Geron, Nicholas; Andrews, Michelle; Rogan, John; Martin, Deborah; Sangermano, Florencia; Williams, C. A.; Weil, Benjamin

doi:10.1080/15481603.2020.1818950

Cited by 18 publications

(6 citation statements)

References 81 publications

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“…Nevertheless, the relationship between LST and air temperature is not straightforward: at large-scale and medium resolution, good correlations are found in the night with minimum air temperature, at a minor level also during the day with air temperature maxima (Chung et al 2020), while some authors do not consider viable to obtain air temperatures from satellite data (Xiong and Chen 2017). Moreover, in urban areas, the relationship is further complicated by enhanced surface heterogeneity, which gives rise to relevant and variable horizontal gradients in surface properties and affects the offset between in situ air temperature measurements and satellitederived LST (Elmes et al 2020;Sun et al 2020). Anyway, for this research and considering the availability of the dedicated and enhanced urban surface network described above, the first attempt was to investigate this relationship specifically for the Milan area.…”

Section: Methodsmentioning

confidence: 99%

High-resolution climatic characterization of air temperature in the urban canopy layer

Montoli¹,

Frustaci²,

Lavecchia³

et al. 2021

Bull. of Atmos. Sci.& Technol.

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Urbanized environments are of greater relevance because of the high and still rapidly increasing percentage of the world population living in and around cities and as the preferred location of human activities of every type. For this reason, much attention is paid to the urban climate worldwide. Among the UN 2030 17 Sustainable Development Goals, at least one concerns resilient cities and climate action. The WMO supports these goals promoting safe, healthy, and resilient cities by developing specially tailored integrated urban weather, climate, and environmental services. An unavoidable basis for that is an improved observational capability of urban weather and climate, as well as high-resolution modeling. For both the former and the latter, and of primary importance for the latter, urban meteorological surface networks are undoubtedly a very useful basis. Nevertheless, they are often unfit for detailed urban climatological studies and they are generally unable to describe the air temperature field in the urban canopy layer (UCL) with a spatial resolution which is sufficient to satisfy the requirements set by several professional activities and especially for local adaptation measures to climate change. On the other hand, remote sensing data from space offer a much higher spatial resolution of the surface characteristics, although the frequency is still relatively lower. A useful climatological variable from space is, for instance, the land surface temperature (LST), one of the WMO Essential Climate Variables (ECV). So often used to describe the Surface Urban Heat Islands (S-UHI), LST has no simple correlation with UCL air temperature, which is the most crucial variable for planning and management purposes in cities. In this work, after a review of correlation and interpolation methods and some experimentation, the cokriging methodology to obtain surface air temperature is proposed. The implemented methodology uses high quality but under-sampled in situ measurements of air temperature at the top of UCL, obtained by using a dedicated urban network, and satellite-derived LST. The satellite data used are taken at medium (1 × 1 km 2 ) resolution from Copernicus Sentinel 3 and at high resolution (30 × 30 m 2 ) from NASA-USGS Landsat 8. This fully exportable cokriging-based methodology, which also provides a quantitative measure of the related uncertainties, was tested and used to obtain medium to high spatial resolution air temperature maps of Milan (Italy) and the larger, much populated, but also partly rural, surrounding area of about 6000 km 2 . Instantaneous as well as long period mean fields of fine spatially resolved air temperature obtained by this method for selected weather types and different Urban Heat Island configurations represent an important knowledge improvement for the climatology of the urban Extended author information available on the last page of the article Bulletin of Atmospheric Science and Technology 1 3 and peri-urban area of Milan. It finds application not only in more detailed urban climat...

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Section: Methodsmentioning

confidence: 99%

High-resolution climatic characterization of air temperature in the urban canopy layer

Montoli¹,

Frustaci²,

Lavecchia³

et al. 2021

Bull. of Atmos. Sci.& Technol.

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“…Polar-orbiting satellites such as MODIS [14][15][16][17] or the Landsat series [2,12,18] are extensively used for detailed urban LST estimates due to their high spatial resolution (up to 60 m). However, their primary limitation is that they are designed with a fixed return timethat they revisit the same region on Earth at fixed hour of the day-restricting continuous LST monitoring or diurnal cycle analysis.…”

Section: Introductionmentioning

confidence: 99%

Urban Land Surface Temperature Downscaling in Chicago: Addressing Ethnic Inequality and Gentrification

Lee,

Berkelhammer,

Wilson

et al. 2024

Remote Sensing

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In this study, we developed a XGBoost-based algorithm to downscale 2 km-resolution land surface temperature (LST) data from the GOES satellite to a finer 70 m resolution, using ancillary variables including NDVI, NDBI, and DEM. This method demonstrated a superior performance over the conventional TsHARP technique, achieving a reduced RMSE of 1.90 °C, compared to 2.51 °C with TsHARP. Our approach utilizes the geostationary GOES satellite data alongside high-resolution ECOSTRESS data, enabling hourly LST downscaling to 70 m—a significant advancement over previous methodologies that typically measure LST only once daily. Applying these high-resolution LST data, we examined the hottest days in Chicago and their correlation with ethnic inequality. Our analysis indicated that Hispanic/Latino communities endure the highest LSTs, with a maximum LST that is 1.5 °C higher in blocks predominantly inhabited by Hispanic/Latino residents compared to those predominantly occupied by White residents. This study highlights the intersection of urban development, ethnic inequality, and environmental inequities, emphasizing the need for targeted urban planning to mitigate these disparities. The enhanced spatial and temporal resolution of our LST data provides deeper insights into diurnal temperature variations, crucial for understanding and addressing the urban heat distribution and its impact on vulnerable communities.

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“…Typically, under the same meteorological conditions, surface and ground air temperatures do not coincide, as the remote sensor captures the longwave radiation from the surface rather than the air temperature recorded by thermometers, which forms the thermal environment in the inhabitable atmospheric layer (urban canopy layer, UCL). Because of the differences in the processes shaping the energy budgets of the two environments, LSTs vary over a much wider range than air temperature [31][32][33][34].…”

Section: Introductionmentioning

confidence: 99%

UAS-Based Thermal Photogrammetry for Microscale Surface Urban Heat Island Intensity Assessment in Support of Sustainable Urban Development (A Case Study of Lyulin Housing Complex, Sofia City, Bulgaria)

Dimitrov,

Iliev,

Borisova

et al. 2024

Sustainability

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The urban heat island (UHI) and its intensity is one of the phenomena that are of determining importance for the comfort of living in cities and their sustainable development in the face of deepening climate change. The study is objectively difficult due to the large dynamics like land cover and the considerable diversity of land use patterns in urban areas. Most of the frequently used research practice approaches provide information with problematic spatial and temporal resolution, making them difficult to apply for sustainable urban planning purposes. This paper proposes to calculate SUHI intensity as the difference between the temperature of a given point within a city and the average minimum temperature of the land cover class with the lowest surface temperatures within the same urban area. The study presents the results of the application of thermal photogrammetry based on the use of unmanned aerial systems (UAS), combined with geographic information systems (GIS), in the study of surface urban heat island intensity (SUHI), at the local level for the largest housing complex in Bulgaria–Lyulin district of the capital of Sofia city. The studies were carried out during a heat wave in July 2023. A difference of 16.5 °C was found between locations with SUHI occurrence and of the peripheral non-build and natural land cover types within the urbanized area. The information benefits of locally addressed data and their direct applicability are discussed to support decision-making processes in the planning and management of urban areas, including their climate adaptation and sustainable development.

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Mapping spatiotemporal variability of the urban heat island across an urban gradient in Worcester, Massachusetts using in-situ Thermochrons and Landsat-8 Thermal Infrared Sensor (TIRS) data

Cited by 18 publications

References 81 publications

High-resolution climatic characterization of air temperature in the urban canopy layer

High-resolution climatic characterization of air temperature in the urban canopy layer

Urban Land Surface Temperature Downscaling in Chicago: Addressing Ethnic Inequality and Gentrification

UAS-Based Thermal Photogrammetry for Microscale Surface Urban Heat Island Intensity Assessment in Support of Sustainable Urban Development (A Case Study of Lyulin Housing Complex, Sofia City, Bulgaria)

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