An Improved Method for Anthropogenic Heat Flux Estimation Using Remotely Sensed Data

Urban anthropogenic heat flux (AHF) has been widely noted as a source to urban heat island effect in cities. Developing reliable methods using accessible data to estimate the spatial and temporal distribution of AHF is an on-going research topic in urban climate studies. This study proposed an improved method by using surface energy balance model and satellite observations to quantify the AHF spatially at very high spatial resolution. Taking New York City as an example, we separated the anthropogenically emitted heat as the residual term and calculated grid-specific net radiation, ground heat flux, sensible heat flux and latent heat flux. Key parameters were modelled on a 300m×300m scale or finer, as opposed to previously parameterizations based on land-use types. It is shown that this RS-based method produces comparable results on magnitude in contrast to commonly used inventory methods and containing geospatial information of AHF at a fine spatial scale. Most importantly, this approach only requires easily accessible input data and has a low implementation cost. Currently, we developed this methodology using data from Landsat 8 but it can be extended for other satellites. Overall, the study offers a promising means to reconstruct the AHF of cities globally at different temporal and spatial scales by fusing flexible thermal observations, ground measurements and urban metadata to better constrain the spatial and temporal variability of AHF.