Spatiotemporal multiresolution modeling to infill missing areal data and enhance the temporal frequency of infrared satellite images

• DOI: 10.1002/env.2466
• Publication Date: 2017-09-06T02:58:40Z
• Authors: G. Q. Collins; M. J. Heaton; L. Hu; A. J. Monaghan
• Keywords: Moderate-resolution imaging spectroradiometer; Temporal resolution; Earth observation

High‐resolution environmental observations from satellite remote sensing are useful for gaining insight into climate variability over large regions of the earth. However, data products derived infrared can have amounts missing due to periodic cloud cover obscuring earth's surface. In addition, these commonly instruments aboard polar‐orbiting satellites, which make relatively infrequent passes each region planet, leaving blocks that in time. The goal this research is overcome issues by spatially and temporally infilling temperature using observations. To accomplish this, we propose novel statistical modeling techniques account dissonance between areal spatial support continuous temporal domain. develop a multiresolution approach accommodates dimensionality high‐resolution images. result our work computationally efficient methodology provides means infill both temporally. demonstrated land surface fields Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard NASA's Terra Aqua Harris County, Texas, USA.