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

2019 ◽  
Vol 16 (14) ◽  
pp. 2467 ◽  
Author(s):  
Chaobin Yang ◽  
Ranghu Wang ◽  
Shuwen Zhang ◽  
Caoxiang Ji ◽  
Xie Fu
Keyword(s):  
Land Use ◽  
Urban Area ◽  
Air Temperature ◽  
Temporal Variability ◽  
Spatial Information ◽  
Thermal Environment ◽  
Thermal Characteristics ◽  
Urban Heat Islands ◽  
Heat Islands ◽  
Urban Heat

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.

scholarly journals A spatially-explicit approach to simulate urban heat islands in complex urban landscapes

2020 ◽  
Author(s):  
Martí Bosch ◽  
Maxence Locatelli ◽  
Perrine Hamel ◽  
Roy P. Remme ◽  
Jérôme Chenal ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Air Temperature ◽  
Urban Areas ◽  
Heat Waves ◽  
Urban Heat Islands ◽  
Land Use Land Cover ◽  
Heat Islands ◽  
Urban Heat ◽  
Cooling Model

Abstract. Mitigating urban heat islands has become an important objective for many cities experiencing heat waves. Despite notable progress, the spatial relationship between land use/land cover patterns and the distribution of air temperature remains poorly understood. This article presents a reusable computational workflow to simulate the spatial distribution of air temperature in urban areas from their land use/land cover data. The approach employs the InVEST urban cooling model, which estimates the cooling capacity of the urban fabric based on three biophysical mechanisms, i.e., tree shade, evapotranspiration and albedo. An automated procedure is proposed to calibrate the parameters of the model to best fit air temperature observations from monitoring stations. In a case study in Lausanne, Switzerland, spatial estimates of air temperature obtained with the calibrated model show that the urban cooling model outperforms spatial regressions based on satellite data. This represents two major advances in urban heat island modeling. First, unlike in black-box approaches, the calibrated parameters of the urban cooling model can be interpreted in terms of the physical mechanisms that they represent and can therefore help understanding how urban heat islands emerge in a particular context. Second, the urban cooling model requires only land use/land cover and reference temperature data and can therefore be used to evaluate synthetic scenarios such as master plans, urbanization prospects, and climate scenarios. The proposed approach provides valuable insights into the emergence of urban heat islands which can serve to inform urban planning and assist the design of heat mitigation policies.

scholarly journals A spatially explicit approach to simulate urban heat mitigation with InVEST (v3.8.0)

2021 ◽  
Vol 14 (6) ◽  
pp. 3521-3537
Author(s):  
Martí Bosch ◽  
Maxence Locatelli ◽  
Perrine Hamel ◽  
Roy P. Remme ◽  
Jérôme Chenal ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Air Temperature ◽  
Urban Areas ◽  
Heat Waves ◽  
Spatial Relationship ◽  
Urban Heat Islands ◽  
Heat Islands ◽  
Urban Heat ◽  
Cooling Model

Abstract. Mitigating urban heat islands has become an important objective for many cities experiencing heat waves. Despite notable progress, the spatial relationship between land use and/or land cover patterns and the distribution of air temperature remains poorly understood. This article presents a reusable computational workflow to simulate the spatial distribution of air temperature in urban areas from their land use and/or land cover data. The approach employs the InVEST urban cooling model, which estimates the cooling capacity of the urban fabric based on three biophysical mechanisms: tree shade, evapotranspiration and albedo. An automated procedure is proposed to calibrate the parameters of the model to best fit air temperature observations from monitoring stations. In a case study in Lausanne, Switzerland, spatial estimates of air temperature obtained with the calibrated model show that the urban cooling model outperforms spatial regressions based on satellite data. This represents two major advances in urban heat island modeling. First, unlike in black-box approaches, the calibrated parameters of the urban cooling model can be interpreted in terms of the physical mechanisms that they represent; therefore, they can help promote an understanding of how urban heat islands emerge in a particular context. Second, the urban cooling model requires only land use and/or land cover and reference temperature data and can, therefore, be used to evaluate synthetic scenarios such as master plans, urbanization prospects and climate scenarios. The proposed approach provides valuable insights into the emergence of urban heat islands which can serve to inform urban planning and assist the design of heat mitigation policies.

scholarly journals Impact of spatiotemporal land-use and land-cover changes on surface urban heat islands in a semiarid region using Landsat data

2020 ◽  
pp. 1-21
Author(s):  
Ehsan Kamali Maskooni ◽  
Hossein Hashemi ◽  
Ronny Berndtsson ◽  
Peyman Daneshkar Arasteh ◽  
Mohammad Kazemi
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Heat Islands ◽  
Semiarid Region ◽  
Land Cover Changes ◽  
Landsat Data ◽  
Heat Islands ◽  
Urban Heat

Impacts of land use changes from the Hanoi Master Plan 2030 on urban heat islands: Part 2. Influence of global warming

2017 ◽  
Vol 31 ◽  
pp. 95-108 ◽  
Author(s):  
Han Soo Lee ◽  
Andhang Rakhmat Trihamdani ◽  
Tetsu Kubota ◽  
Satoru Iizuka ◽  
Tran Thi Thu Phuong
Keyword(s):  
Land Use ◽  
Global Warming ◽  
Land Use Changes ◽  
Urban Heat Islands ◽  
Master Plan ◽  
Heat Islands ◽  
Urban Heat

scholarly journals Impacts of Land use Changes on Urban Heat Islands in Hanoi, Vietnam: Scenario Analysis

2017 ◽  
Vol 198 ◽  
pp. 525-529 ◽  
Author(s):  
Andhang Rakhmat Trihamdani ◽  
Tetsu Kubota ◽  
Han Soo Lee ◽  
Kento Sumida ◽  
Tran Thi Thu Phuong
Keyword(s):  
Land Use ◽  
Scenario Analysis ◽  
Land Use Changes ◽  
Urban Heat Islands ◽  
Heat Islands ◽  
Urban Heat

scholarly journals A Comparative Study of various Indices for extraction urban impervious surface of Landsat 8 OLI

2019 ◽  
Vol 33 (2) ◽  
pp. 162-172
Author(s):  
Iswari Nur Hidayati ◽  
R Suharyadi
Keyword(s):  
Land Use ◽  
Urban Areas ◽  
Spectral Characteristics ◽  
Impervious Surface ◽  
Urban Heat Islands ◽  
Landsat 8 ◽  
Impervious Surfaces ◽  
Landsat 8 Oli ◽  
Heat Islands ◽  
Urban Heat

Impervious surface is one of the major land cover types of urban and suburban environment. Conversion of rural landscapes and vegetation area to urban and suburban land use is directly related to the increase of the impervious surface area. The impervious surface expansion is straight-lined with decreasing green spaces in urban areas. Impervious surface is one of indicator for detecting urban heat islands. This study compares various indices for mapping impervious surfaces using Landsat 8 OLI imagery by optimizing the different spectral characteristics of Landsat 8 OLI imagery. The research objectives are (1) to apply various indices for impervious surface mapping and (2) identifies impervious surfaces in urban areas based on multiple indices and provide recommendations and find the best index for mapping impervious surface in urban areas. In addition to utilizing the index, land use supervised classification method, maximum likelihood classification used for extracting built-up, and non-built-up areas. Accuracy assessment of this research used field data collection as primary data for calculating kappa coefficient, producer accuracy, and user accuracy. The study can also be extended to find the land surface temperature and correlate the impervious surface extraction data with urban heat islands.

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