Identification of Green Space Attributes that Optimally Reduce the Urban Heat Island Effect in Los Angeles

Abstract

The urban heat island (UHI) effect is one of the many challenges facing urban development as climate change and urbanization increase. The UHI effect refers to a phenomenon in which dense concentrations of impermeable building materials absorb and trap solar radiation. The gradual dissipation of heat raises ambient temperatures of urban areas higher than the surrounding non-urban areas. It is anticipated that increases in ambient temperatures and urban density will be a serious threat to public health as it increases the risk of heat-related illnesses and mortalities. Past studies have shown that increasing permeability and reducing density are key to reducing the UHI effect. In urban developments, green spaces fulfill both of those criteria. However, it is important to maximize the cooling effect (CE) and cooling intensity (CI) of green spaces as space in urban developments are at a premium. This study explored the factors for measuring urban density geospatially and identified green space attributes that had the greatest impact on CE and CI in Los Angeles. The green spaces analyzed were predominately parks managed by the City of Los Angeles. The analysis was divided into three primary parts and utilized remote sensing and geospatial information systems (GIS) techniques. First, the land surface temperature (LST), was calculated using raster images captured by the Landsat-8 satellite. Using the product of a thermal imaging satellite allowed for accurate temperature measurements between all of the parks with no temporal variation in between them. Parks were then overlaid on the LST raster to calculate CE and CI. Second, multiple geospatial analysis products were created as inputs for a wholistic land classification of the Los Angeles urban area. The products included: semi-supervised raster classification, normalized difference vegetation index (NDVI), city zoning data, and urban density ratio. The Urban density is defined as a ratio of the total number of inhabitants living within a well-defined footprint of a city. As this project requires analysis of specific areas, the city was discretized into census tracts prior to calculating the urban density. The population of the census tract then was divided by the urban density of the same census tract to produce the Urban Density Ratio. The inclusion of population in this analysis was to account for anthropological effects that are not immediately reflected in solely measuring building density. However, the inclusion of population created potentially specious results for densely built-up areas with low population such as industrial areas; a correlation coefficient was calculated in an attempt to highlight the limitation. Finally, all of the products were combined to create the land classification output. Using the output, categories of land classification were divided into developed and undeveloped land. Then sub-categorized by intensity of development to create the groups: high-intensity development, medium-intensity development, and low-density development. For vegetation density, the groups dense vegetation, sparse vegetation, and open area. According to the results of the comparison between LST and the land classification output, areas that are medium intensity developed have a higher mean temperature than high intensity areas; which is intuitively contradictory. This discrepancy can be explained by the correlation coefficient for each classification. Certain high intensity (heavy industrial) areas have higher LST than medium intensity areas; however, there are other high intensity (downtown Los Angeles) areas that are much cooler than medium intensity areas. The results of the park analysis indicated that medium sized parks performed the best surpassing large parks in both CE and CI. The presence of vegetation had a high correlation with lower CE And CI; however, the type of vegetation had a low correlation. Other results of the analysis found that parks cool best when they’re close to each other and when they are located in low and medium intensity developed areas. Moreover, the results of this project indicate a higher correlation between contiguity brakes in developed areas and lower LST than any one specific attribute of a park.