The Effect of Urban Density and Vegetation Cover on the Heat Island of a Subtropical City

AbstractThe urban heat island (UHI) has a negative impact on the health of urban residents by increasing average temperatures. The intensity of the UHI effect is influenced by urban geometry and the amount of vegetation cover. This study investigated the impact of urban growth and loss of vegetation cover on the UHI in a subtropical city (Brisbane, Australia) during average and extreme conditions using the Conformal Cubic Atmospheric Model, run at a 1-km spatial resolution for 10 years. The average nighttime temperature increase was 0.7°C for the “Medium Density” urban growth scenario and 1.8°C for the “No Vegetation” scenario. During two widespread extreme heat events, the mean maximum increase in urban temperatures above the Control was between 2.2° and 3.8°C in the No Vegetation scenario and between 0.3° and 1.6°C in the Medium Density urban growth scenario. The results are similar to previous findings for temperate cities, with the intensity of the UHI effect higher at night and during winter than during the day and summer. Vegetation cover had the strongest impact on temperatures, more so than building height and height/width ratio. Maintaining and restoring vegetation, therefore, is a key consideration in mitigating the urban heat island. The large temperature increases found in this study, particularly during extreme heat events, shows the importance of reducing the UHI for protecting the health of urban residents, and this should be a priority in urban landscape planning and design.

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Forecasting the New York City Urban Heat Island and Sea Breeze during Extreme Heat Events

Weather and Forecasting ◽

10.1175/waf-d-13-00012.1 ◽

2013 ◽

Vol 28 (6) ◽

pp. 1460-1477 ◽

Cited By ~ 42

Author(s):

Talmor Meir ◽

Philip M. Orton ◽

Julie Pullen ◽

Teddy Holt ◽

William T. Thompson ◽

...

Keyword(s):

New York ◽

New York City ◽

Urban Heat Island ◽

York City ◽

Sea Breeze ◽

Extreme Heat ◽

Heat Island ◽

Extreme Heat Events ◽

Urban Heat ◽

Heat Events

Abstract Two extreme heat events impacting the New York City (NYC), New York, metropolitan region during 7–10 June and 21–24 July 2011 are examined in detail using a combination of models and observations. The U.S. Navy's Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) produces real-time forecasts across the region on a 1-km resolution grid and employs an urban canopy parameterization to account for the influence of the city on the atmosphere. Forecasts from the National Weather Service's 12-km resolution North American Mesoscale (NAM) implementation of the Weather Research and Forecasting (WRF) model are also examined. The accuracy of the forecasts is evaluated using a land- and coastline-based observation network. Observed temperatures reached 39°C or more at central urban sites over several days and remained high overnight due to urban heat island (UHI) effects, with a typical nighttime urban–rural temperature difference of 4°–5°C. Examining model performance broadly over both heat events and 27 sites, COAMPS has temperature RMS errors averaging 1.9°C, while NAM has RMSEs of 2.5°C. COAMPS high-resolution wind and temperature predictions captured key features of the observations. For example, during the early summer June heat event, the Long Island south shore coastline experienced a more pronounced sea breeze than was observed for the July heat wave.

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Multi-Scale 3D Geovisualization of Urban Heat Island Data for Planning Dialogue in Toronto

Advances in Civil and Industrial Engineering - Emerging Issues, Challenges, and Opportunities in Urban E-Planning ◽

10.4018/978-1-4666-8150-7.ch008 ◽

2015 ◽

pp. 166-187

Author(s):

John Danahy ◽

Jacob Mitchell ◽

Robert Wright ◽

Rodney Hoinkes ◽

Rob Feick

Keyword(s):

Urban Heat Island ◽

Analytical Models ◽

Heat Island ◽

Climate Change Effects ◽

Multi Scale ◽

Extreme Heat Events ◽

Urban Models ◽

Planning Decision ◽

Urban Heat ◽

Policies And Programs

This e-planning visualization case study in the Toronto region investigated the use of 3D urban models as a visualization reference against which analytical models were visualized to identify micro-scale mitigation scenarios of urban heat island effects. The case studies were directed to processes of planning decision making. The Toronto region faces problems of urban heat island impacts due to the increasing frequency of extreme heat events (Bass, Krayenhoff, & Martilli, 2002). The City of Toronto and the Toronto and Region Conservation Authority (TRCA) have each implemented policies and programmes aimed at mitigating urban heat island and climate change effects (City of Toronto, 2006). This research explored ways of visualizing remote sensing heat island data to assist with the targeted application of planning policies and programs.

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Multi-Scale 3D Geovisualization of Urban Heat Island Data for Planning Dialogue in Toronto

Natural Resources Management ◽

10.4018/978-1-5225-0803-8.ch026 ◽

2017 ◽

pp. 570-591

Author(s):

John Danahy ◽

Jacob Mitchell ◽

Robert Wright ◽

Rodney Hoinkes ◽

Rob Feick

Keyword(s):

Urban Heat Island ◽

Analytical Models ◽

Heat Island ◽

Climate Change Effects ◽

Multi Scale ◽

Extreme Heat Events ◽

Urban Models ◽

Planning Decision ◽

Urban Heat ◽

Policies And Programs

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Black widows on an urban heat island: extreme heat affects spider development and behaviour from egg to adulthood

Animal Behaviour ◽

10.1016/j.anbehav.2020.07.005 ◽

2020 ◽

Vol 167 ◽

pp. 77-84

Author(s):

J. Chadwick Johnson ◽

Emily Garver ◽

Taylor Martin

Keyword(s):

Urban Heat Island ◽

Extreme Heat ◽

Heat Island ◽

Urban Heat

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Investigation of Urban Air Temperature and Humidity Patterns during Extreme Heat Conditions Using Satellite-Derived Data

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-15-0051.1 ◽

2015 ◽

Vol 54 (11) ◽

pp. 2245-2259 ◽

Cited By ~ 5

Author(s):

Leiqiu Hu ◽

Andrew J. Monaghan ◽

Nathaniel A. Brunsell

Keyword(s):

Urban Heat Island ◽

Air Temperature ◽

Urban Land Use ◽

Extreme Heat ◽

Heat Island ◽

Near Surface ◽

Vegetation Fraction ◽

Dewpoint Temperature ◽

Temperature And Humidity ◽

Urban Heat

AbstractExtreme heat is a leading cause of weather-related human mortality. The urban heat island (UHI) can magnify heat exposure in metropolitan areas. This study investigates the ability of a new MODIS-retrieved near-surface air temperature and humidity dataset to depict urban heat patterns over metropolitan Chicago, Illinois, during June–August 2003–13 under clear-sky conditions. A self-organizing mapping (SOM) technique is used to cluster air temperature data into six predominant patterns. The hottest heat patterns from the SOM analysis are compared with the 11-summer median conditions using the urban heat island curve (UHIC). The UHIC shows the relationship between air temperature (and dewpoint temperature) and urban land-use fraction. It is found that during these hottest events 1) the air temperature and dewpoint temperature over the study area increase most during nighttime, by at least 4 K relative to the median conditions; 2) the urban–rural temperature/humidity gradient is decreased as a result of larger temperature and humidity increases over the areas with greater vegetation fraction than over those with greater urban fraction; and 3) heat patterns grow more rapidly leading up to the events, followed by a slower return to normal conditions afterward. This research provides an alternate way to investigate the spatiotemporal characteristics of the UHI, using a satellite remote sensing perspective on air temperature and humidity. The technique has potential to be applied to cities globally and provides a climatological perspective on extreme heat that complements the many case studies of individual events.

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Atlanta’s urban heat island under extreme heat conditions and potential mitigation strategies

Natural Hazards ◽

10.1007/s11069-009-9406-z ◽

2009 ◽

Vol 52 (3) ◽

pp. 639-668 ◽

Cited By ~ 113

Author(s):

Yan Zhou ◽

J. Marshall Shepherd

Keyword(s):

Urban Heat Island ◽

Extreme Heat ◽

Mitigation Strategies ◽

Heat Island ◽

Urban Heat

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Mapping and Analyzing the Park Cooling Effect on Urban Heat Island in an Expanding City: A Case Study in Zhengzhou City, China

Land ◽

10.3390/land9020057 ◽

2020 ◽

Vol 9 (2) ◽

pp. 57 ◽

Cited By ~ 4

Author(s):

Huawei Li ◽

Guifang Wang ◽

Guohang Tian ◽

Sándor Jombach

Keyword(s):

Urban Heat Island ◽

Vegetation Cover ◽

Landscape Planning ◽

Impervious Surface ◽

Google Earth ◽

Cooling Effect ◽

Landsat 8 ◽

Heat Island ◽

Urban Heat ◽

The Impact

The Urban Heat Island (UHI) effect has been extensively studied as a global issue. The urbanization process has been proved to be the main reason for this phenomenon. Over the past 20 years, the built-up area of Zhengzhou city has grown five times larger, and the UHI effect has become increasingly pressing for the city’s inhabitants. Therefore, mitigating the UHI effect is an important research focus of the expanding capital city of the Henan province. In this study, the Landsat 8 image of July 2019 was selected from Landsat collection to obtain Land Surface Temperature (LST) by using Radiative Transfer Equation (RTE) method, and present land cover information by using spectral indices. Additionally, high-resolution Google Earth images were used to select 123 parks, grouped in five categories, to explore the impact factors on park cooling effect. Park Cooling Intensity (PCI) has been chosen as an indicator of the park cooling effect which will quantify its relation to park patch metrics. The results show that: (1) Among the five studied park types, the theme park category has the largest cooling effect while the linear park category has the lowest cooling effect; (2) The mean park LST and PCI of the samples are positively correlated with the Fractional Vegetation Cover (FVC) and with Normalized Difference Water Index (NDWI), but these are negatively correlated with the Normalized Difference Impervious Surface Index (NDISI). We can suppose that the increase of vegetation cover rate within water areas as well as the decrease of impervious surface in landscape planning and design will make future parks colder. (3) There is a correlation between the PCI and the park characteristics. The UHI effect could be mitigated by increasing of park size and reducing park fractal dimension (Frac_Dim) and perimeter-area ratio (Patario). (4) The PCI is influenced by the park itself and its surrounding area. These results will provide an important reference for future urban planning and urban park design to mitigate the urban heat island effect.

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