A sampling strategy for satellite sensor-based assessments of the urban heat-island bias

A data sampling strategy was developed for the use of a satellite sensor-based methodology to estimate the urban heat-island temperature bias associated with climate observation stations. NOAA-AVHRR observations at a grid scale of 1 km x 1 km were analysed on a local (3 km x 3 km) and regional (41 km x 41 km) basis centred on the climate observation stations of interest. The grid cells of the regional sample were evaluated and only those designated as rural were used in further analysis. Local and regional differences in the normalized difference vegetation index and radiant surface temperature were used to estimate the urban heat-island bias associated with the climate observation stations. These values were compared to a population-based methodology and a satellite sensor should read satellite sensor/station-derived methodology that required locations of known rural observation stations associated with the local observation station of interest. Generally, the heat-island bias estimates provided by the methodology that relied solely on satellite sensor data were similar to the other methodologies. The datasets used to identify the regional grid cells as rural are available on a global basis as are the vegetation index and radiant surface temperature data. Thus, the satellite sensor-based methodology developed may be uniformly applicable on a global basis.