Estimating Ecosystem Respiration from Remotely Sensed Land Surface Temperature

We report the potential of estimating ecosystem respiration (Re) using remotely sensed land surface temperature (LST) data from NASA’s satellite-borne moderate resolution imaging spectroradiometer (MODIS) sensor. Eight years’ of weekly composite LST data were used to simulate the Re of Morgan Monroe State Forest (MMSF) Ameriflux site, a mixed deciduous forest. We employed a modified Arrhenius type “activation energy” temperature response function (Lloyd and Taylor 1994) with nighttime LST to model Re, and compared to nighttime Re measured with eddy covariance (EC) system. Results of this one-parameter semi-empirical model were linearly correlated (adjusted R2 = 0.71) with measured Re across a wide range of values (0.4 to 8 micro mols of carbon dioxide per square meter per second [μ mol CO2 m-2 s-1]). We also computed a series of weekly average temperature of the site from a combination of day and nighttime LST values, simulated the weekly Re values, and compared those with EC-based weekly Re values. These results demonstrate LST from MODIS sensors can be reliably used in a simple one-parameter model to estimate spatially distributed per-pixel Re of an ecosystem. ===================================================== Lloyd, J., & Taylor, J.A. (1994). On the temperature dependence of soil respiration. Functional Ecology, 8, 315-323.