Evaluation of the correlation between remotely sensing-based and GIS-based anthropogenic heat discharge in Los Angeles County, USA

Anthropogenic heat is an important component of the urban energy budget and a major contributor to urban heat island (UHI) formation. This study estimated the anthropogenic heat discharge in Los Angeles County, USA, using remote sensing-based energy balance approach and GIS-based approach, respectively. Both approaches simulated the anthropogenic heat in workday and non-workday. Spatial patterns of the anthropogenic heat estimated from two approaches with workday and non-workday profiles were compared to see the degree of consistency. The major objective is to evaluate the result of remote sensing-based approach, using GIS modeling approach as a reference. For remote sensing-based approach, two Landsat Thematic Mapper (TM) images were obtained including both of the workday image and non-workday image, and meteorological data collected from multiple weather stations within the study area were interpolated to create continues layers for parameters used in the algorithm to improve accuracy of the estimation. The GIS model approach simulated the anthropogenic heat by summing up the building energy consumption and traffic emission, which calculated using the building footprint, County Assessor's parcel data, and annual average daily traffic (AADT) count data. The differentiation of workday and non-workday GIS anthropogenic heat estimation was designed by setting zero energy consumption to some types of buildings, which considered to be closed, in the non-workday profile. The moderate correlation can be observed between remote sensing estimated results and GIS estimated results: 0.525 for non-workday and 0.573 for workday. This correlation is higher than the correlation between remote sensing estimated anthropogenic heat and GIS estimated building energy consumption, which indicates adding the traffic emission into the GIS model can increase the level of consistency. However, no obvious effect can be observed when consider workday/non-workday difference in this study.