Exploratory Analysis of Urban Climate Using a Gap Filled Landsat 8 Land Surface Temperature Data Set
The Landsat 8 satellites have retrieved land surface temperature (LST) resampled at a 30 m spatial resolution since 2013, but the urban climate studies frequently use a limited number of images due to the problems related to missing data over the city of interest. This paper endorses a procedure for building a long term gap free LST data set in an urban area using the high resolution Landsat 8 imagery. The study is applied on 94 images available through 2013 2018 over Bucharest (Romania) The raw images containing between 1.1% and 58.4% missing LST data were filled in using the Data INterpolating Empirical Orthogonal Functions (DINEOF) algorithm implemented in the sinkr R packages. The resulting high spatial resolution gap filled land surface temperature data set was used to explore the LST climatology over Bucharest (Romania) an urban area, at a monthly, seasonal, and annual scale. The performance of the gap filling method was checked using a cross validation procedure, and the results pledge for the development of an LST based urban climatology.
Sensors