ABSTRACT
Land surface temperature (LST) is a key parameter in heat hazard monitoring. The trade-off between spatial and temporal resolutions of currently available thermal infrared (TIR) images and the need for obtaining TIR have been discussed (Agam et al. 2007; Kustas et al. 2003; Schmugge et al. 1998; Weng 2009). The sensors on polar orbiting satellites, such as Landsat sensors and the Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER), can provide TIR data with relatively high spatial resolution. However, their low temporal resolutions are not sufficient for monitoring the diurnal change of LST. Although the Moderate-Resolution Imaging Spectroradiometer (MODIS) and the Advanced Very High Resolution Radiometer (AVHRR) produce one to two images per day for the same area, cloud
11.1 Introduction .................................................................................................. 211 11.2 Methodology ................................................................................................. 213
11.2.1 Study Area ........................................................................................ 213 11.2.2 Data Sets ........................................................................................... 215
11.2.2.1 Data for Linear Spectral Mixture Analysis ....................... 215 11.2.2.2 Data for Downscaling TIR Images .................................... 215 11.2.2.3 Data for ET Estimation ...................................................... 216
11.2.3 Data Processing ................................................................................ 216 11.2.3.1 Data Preparation and Preprocessing .................................. 217 11.2.3.2 Vegetation-Impervious Surface-Soil Model .................... 217 11.2.3.3 Downscaling LST .............................................................. 217 11.2.3.4 The Land Surface Moisture Model .................................... 218
11.3 Results ...........................................................................................................220 11.3.1 Pure Impervious Surfaces, Soil, and Vegetation Cover Pixels .........220 11.3.2 The Changes of Spatial Distribution of Daily and Hourly LST ....... 222 11.3.3 Instantaneous LST and Latent Flux over Pure Impervious
Surfaces, Soil, and Vegetation Cover with an Hour or Day Interval .... 222 11.4 Conclusions ...................................................................................................226 References .............................................................................................................. 227
coverage reduces the usage of the image data and thus increases the time between two image acquisitions. The Geostationary Operational Environmental Satellite (GOES) imager on the geostationary satellite has a much higher frequency of observation, which is every 15 min, but with a much coarser spatial resolution of 4 km. Therefore, a common solution for characterizing heat waves is to downscale GOES images from 4 to 1 km while keeping its temporal resolution.
