Aggregation and Disaggregation Techniques Applied on Remotely Sensed Data to Obtain Optimum Resolution for Surface Energy Fluxes Estimation Academic Article uri icon

abstract

  • Continuous monitoring of surface energy fluxes provides an important tool for precision agriculture management. It is, therefore, desirable to obtain these fluxes at agricultural field size (length scale~ 10-100 m). To date, land surface temperature (LST), a fundamental input required for flux computations, is usually available at a nominal resolution of 1 km, which disables field-scale monitoring. Disaggregating LST data into field-scale sub-pixels was found to be possible, with deterioration in temperature accuracy as sub-pixel size is reduced. In contrast to LST, land use and fractional vegetation cover (LU and FC, additional key inputs) are available at high spatial resolution (eg, 30 m). Aggregation of LU and FC to meet the lower resolution LST data introduces errors when aggregating to larger pixel sizes. The objective of this research is to find the optimum resolution that will minimize the errors …

publication date

  • January 1, 2006