This algorithm was developed by Peng Fu.
Email address of primary contact: firstname.lastname@example.org.
Language of computer code: MATLAB (R2012 or higher preferred)
Does standalone executable software exist for the algorithm? : No
Input data: Two MODIS images at time t1 and t2 and one Landsat image at t1.
Output: one fine-resolution (Landsat-like) satellite image at t2.
Descriptions of the computer code by the author:
The SADFAT algorithm is designed for predicting land surface temperatures at high temporal frequency and at the medium spatial resolution (120 m) using the combined datasets of MODIS and Landsat (more generally, the combined datasets of MODIS-like and Landsat-like images). SADFAT presented several improvements over its precedents: (1) the incorporation of an ATC model to characterize the annual variations of land surface temperature and to compute conversion coefficient, and (2) the inclusion of linear spectral mixture analysis to address the issue of thermal landscape heterogeneity.
Weng, Q., Fu, P. and F. Gao. 2014. Generating daily land surface temperature at Landsat resolution by fusing Landsat and MODIS data. Remote Sensing of Environment, 145, 55-67.
Remote sensor the algorithm is primarily applied to:
Coarse spatial resolution (> 100 m) optical sensor
Medium spatial resolution (10-100 m) optical sensor
Thermal infrared sensor
Atmosphere and climate
Land cover and land use
Geography and land information