AbstractsGeography &GIS

Assimilation of multi-scale thermal remote sensing data using spatio-temporal cokriging method

by Bo Yang

Institution: University of Cincinnati
Department: Arts and Sciences: Geography
Degree: MA
Year: 2013
Keywords: Geography; cokriging; image fusion; North Alaska; Thermal remotesensing
Record ID: 2012939
Full text PDF: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1377868463


About 20% of the Arctic Coastal Plain (ACP) is covered with lakes >10 ha in size, with thousands of smaller water bodies that significantly expand and contract through short Arctic summers. Thermal infrared (TIR) remote sensing provides an effective tool for mapping water surface temperature. Unfortunately, no single satellite system provides temporally frequent thermal measurements at high spatial resolution. This research developed a spatio-temporal cokriging method to assimilate thermal observations from multiple satellite platforms with different revisit frequency and different spatial resolutions. This technique has been applied to assimilate daily MODIS thermal images (1 km) with 120 m spatial resolution Landsat TM thermal images over the Arctic Coastal Plain of northern Alaska. The assimilation results are useful for detecting and investigating subtle spatial patterns and seasonal trends/variability of surface water temperature in the thermokarst lakes and land surface temperature of the Arctic tundra. The agreement between satellite-derived and in situ measured near-surface lake temperature and cross-validation with additional Landsat image suggests that this approach yields viable results.