Urbanization and Land Surface Temperature in Pinellas County, Florida

Since the early 1800\u27s, many studies have recognized increased heat in urban areas, known as the urban heat island (UHI) effect, as one of the results of human modification to the natural landscape. UHI is related to differences in land surface temperature (LST) between rural areas and urban areas where factors of the built environment such as the thermodynamic capacities of materials, structural geometry, and heat generating activities cause increased storage and re-radiation of heat to the atmosphere. This thesis examines the correlation between factors of urbanization and differences in land surface temperature (LST) in the subtropical climate of Pinellas County, Florida using remote sensing techniques. It describes the spatial pattern of LST, analyzes its relationship to factors of urbanization relative to NDVI, percentage of impervious surface, and land use land cover in the study area. It also assesses the effectiveness of remote sensing as an efficient method of identifying LST patterns at the local and neighborhood level for mitigation strategies. Landsat TM thermal band imagery for three dates; April 1986, 2001 and 2009 was processed using Qin\u27s mono-window algorithm (MWA) technique to derive LST levels. This data was compared to in-situ readings, then normalized and statistically analyzed for correlation with vegetation ratio (NDVI) and imperviousness percentages derived using linear spectral mixing/unmixing, and also with land use/land cover classification. The resulting LST spatial pattern is a gradient across the peninsular landscape, from cooler water and wetland areas to a generally warmer interior, interspersed with micro-urban heat islands (MUHIs), corresponding to urban structures and cool-islands of parkland and lakes. Correspondence between LST pattern and urban structures and land use demonstrates the suitability of medium resolution remote sensing data and techniques for identifying micro-urban heat islands (MUHIs) for possible mitigation. Mitigation could include relatively low-cost measures like replacement of inefficient asphalt roofs with more reflective and emissive cool roofs, placement of street trees to enhance shade, and replacement of impervious pavements by permeable surfaces. The thesis concludes that Landsat TM imagery processed with the MWA provides an efficient, relatively low-cost method for locating MUHIs. Satellite remote sensing, combined with aerial photography can facilitate neighborhood level analysis for the implementation of low-cost mitigation techniques. Previous studies have demonstrated that these are successful ways to mitigate the UHI effect at the micro-scale level; lowering urban heat and saving energy, and also facilitating the reintegration of natural elements into the urban environment