Urban Cold and Heat Island in the City of Bragança (Portugal)

Gonçalves, Artur; Ornellas, Gabriella; Ribeiro, A.C.; Maia, Filipe; Feliciano, Manuel

doi:10.3390/cli6030070

Cited by 27 publications

(33 citation statements)

References 60 publications

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“…The spatial resolution of Landsat-8 (30 m) was high enough to distinguish between the temperature of sites separated by only a few hundred meters and characterized by different types of land use and land cover (LULC) (e.g., green spaces and parking lots). Similar to [95], we found that green spaces were characterized by lower LST compared to paved built surfaces and bare land (the difference between the maximum and minimum LST across the 100 measurement sites was 5.5 • C). This trend was indicated by a high and significant correlation between LST and two spectral indices representing green vegetation (NDVI) and built-up land cover (NDBI) (r = −0.45 and r = 0.6, respectively, p < 0.001 for both).…”

Section: Discussionsupporting

confidence: 78%

Remotely Sensed Derived Land Surface Temperature (LST) as a Proxy for Air Temperature and Thermal Comfort at a Small Geographical Scale

Goldblatt

Addas

Crull

et al. 2021

Land

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Urban Heat Islands (UHIs) and Urban Cool Islands (UCIs) can be measured by means of in situ measurements and interpolation methods, which often require densely distributed networks of sensors and can be time-consuming, expensive and in many cases infeasible. The use of satellite data to estimate Land Surface Temperature (LST) and spectral indices such as the Normalized Difference Vegetation Index (NDVI) has emerged in the last decade as a promising technique to map Surface Urban Heat Islands (SUHIs), primarily at large geographical scales. Furthermore, thermal comfort, the subjective perception and experience of humans of micro-climates, is also an important component of UHIs. It remains unanswered whether LST can be used to predict thermal comfort. The objective of this study is to evaluate the accuracy of remotely sensed data, including a derived LST, at a small geographical scale, in the case study of King Abdulaziz University (KAU) campus (Jeddah, Saudi Arabia) and four surrounding neighborhoods. We evaluate the potential use of LST estimates as proxy for air temperature (Tair) and thermal comfort. We estimate LST based on Landsat-8 measurements, Tair and other climatological parameters by means of in situ measurements and subjective thermal comfort by means of a Physiological Equivalent Temperature (PET) model. We find a significant correlation (r = 0.45, p < 0.001) between LST and mean Tair and the compatibility of LST and Tair as equivalent measures using Bland-Altman analysis. We evaluate several models with LST, NDVI, and Normalized Difference Built-up Index (NDBI) as data inputs to proxy Tair and find that they achieve error rates across metrics that are two orders of magnitude below that of a comparison with LST and Tair alone. We also find that, using only remotely sensed data, including LST, NDVI, and NDBI, random forest classifiers can detect sites with “very hot” classification of thermal comfort nearly as effectively as estimates using in situ data, with one such model attaining an F1 score of 0.65. This study demonstrates the potential use of remotely sensed measurements to infer the Physiological Equivalent Temperature (PET) and subjective thermal comfort at small geographical scales as well as the impacts of land cover and land use characteristics on UHI and UCI. Such insights are fundamental for sustainable urban planning and would contribute enormously to urban planning that considers people’s well-being and comfort.

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Section: Discussionsupporting

confidence: 78%

Remotely Sensed Derived Land Surface Temperature (LST) as a Proxy for Air Temperature and Thermal Comfort at a Small Geographical Scale

Goldblatt

Addas

Crull

et al. 2021

Land

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“…In this sense, the establishment of green spaces may provide an additional role in cities creating urban cooling island (UCI) effects in pocketed regions of cities [ 63 , 64 ]. Buildings themselves can produce UCI effects during certain times of day i.e., mornings; however, green spaces can absorb additional heat during warmer times of the day and year depending on how impervious and vegetation dense such spaces are [ 64 , 65 ].…”

Section: Landscape Featuresmentioning

confidence: 99%

Supporting Bees in Cities: How Bees Are Influenced by Local and Landscape Features

Ayers

Rehan

2021

Insects

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Urbanization is a major anthropogenic driver of decline for ecologically and economically important taxa including bees. Despite their generally negative impact on pollinators, cities can display a surprising degree of biodiversity compared to other landscapes. The pollinating communities found within these environments, however, tend to be filtered by interacting local and landscape features that comprise the urban matrix. Landscape and local features exert variable influence on pollinators within and across taxa, which ultimately affects community composition in such a way that contributes to functional trait homogenization and reduced phylogenetic diversity. Although previous results are not easily generalizable, bees and pollinators displaying functional trait characteristics such as polylectic diet, cavity-nesting behavior, and later emergence appear most abundant across different examined cities. To preserve particularly vulnerable species, most notably specialists that have become underrepresented within city communities, green spaces like parks and urban gardens have been examined as potential refuges. Such spaces are scattered across the urban matrix and vary in pollinator resource availability. Therefore, ensuring such spaces are optimized for pollinators is imperative. This review examines how urban features affect pollinators in addition to ways these green spaces can be manipulated to promote greater pollinator abundance and diversity.

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“…Nowadays, a large air temperature network with sufficient weather stations has overcome the limitations of spatial resolution. For example, a dense meteorological network of 23 locations across 5 y were used to monitor the urban climate in a small Portuguese city and adequate results were obtained [29]. With the advantages of high temporal resolution and accuracy, meteorological observations can provide fine-scale temporal information on UHI.…”

Section: Introductionmentioning

confidence: 99%

Characterizing the Hourly Variation of Urban Heat Islands in a Snowy Climate City during Summer

Yang

Wang

Zhang

et al. 2019

IJERPH

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Temporal variation of urban heat island (UHI) intensity is one of the most important themes in UHI studies. However, fine-scale temporal variability of UHI with explicit spatial information is sparse in the literature. Based on the hourly air temperature from 195 meteorological stations during August 2015 in Changchun, China, hourly spatiotemporal patterns of UHI were mapped to explore the temporal variability and the effects of land use on the thermal environment using time series analysis, air temperature profiling, and spatial analysis. The results showed that: (1) high air temperature does not indicate strong UHI intensity. The nighttime UHI intensity (1.51 °C) was much stronger than that in the daytime (0.49 °C). (2) The urban area was the hottest during most of the day except the period from late morning to around 13:00 when there was about a 40% possibility for an “inverse UHI intensity” to appear. Paddy land was the coolest in the daytime, while woodland had the lowest temperature during the nighttime. (3) The rural area had higher warming and cooling rates than the urban area after sunrise and sunset. It appeared that 23 °C was the threshold at which the thermal characteristics of different land use types changed significantly.

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Urban Cold and Heat Island in the City of Bragança (Portugal)

Cited by 27 publications

References 60 publications

Remotely Sensed Derived Land Surface Temperature (LST) as a Proxy for Air Temperature and Thermal Comfort at a Small Geographical Scale

Remotely Sensed Derived Land Surface Temperature (LST) as a Proxy for Air Temperature and Thermal Comfort at a Small Geographical Scale

Supporting Bees in Cities: How Bees Are Influenced by Local and Landscape Features

Characterizing the Hourly Variation of Urban Heat Islands in a Snowy Climate City during Summer

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