Utilizing a Sky View Factor Mapping Algorithm to Predict Intra-Urban Variation of Exposure of Heat Hazard
Heat waves, or extreme heat events, cause more deaths in the United States than any other natural hazards with at least 1,200 deaths between 2002 and 2011 estimates. Over 700 died in Chicago alone during a 1995 heat wave. Devastating heat lead to over 70,000 deaths across Europe in 2003 and over 50,000 deaths across Russia in 2010.
Two global drivers will work to increase the threats from heat hazards. First, increased concentrations of atmospheric greenhouse gases and associated climate change will increase the frequency and intensity of extreme heat events throughout the century. Second, the proportion of the world’s population living in cities is expected to increase which will exacerbate the contribution of the urban heat island effect to heat hazards while simultaneously placing more people within the areal extent of future heat hazards.
Given the current impact of heat hazards on human health, better methods to predict intra-urban exposure to heat would be useful in targeting strategies to cope and mitigate the negative impacts. When the potential impacts of future heat hazards are considered, it becomes imperative to do so.
Four main factors contribute to the urban heat island: albedo, moisture, anthropogenic heat emissions and sky view factor. This research looks at one of these factors, sky view factor(the proportion of unobstructed sky above a location), with the goal of using sky view factor maps to contribute to the planning of heat hazard responses.