Impact of sensor footprint on measurement of directional brightness temperature of row crop canopies

A sensorʹs footprint determines the target that is observed by the sensor, and influences the angular features of the targetʹs directional brightness temperature (DBT) at the field site. This paper describes a new radiative transfer model (FovMod) to simulate the DBT of the row crop canopy by considering the sensorʹs footprint in the ground measurements. The FovMod firstly divides the sensorʹs circular or elliptical footprint into a few small cells, and then estimates the componentsʹ fractions (e.g., leaves, sunlit soil and shaded soil) in each cell based on the gap probability theory. The canopyʹs DBT is finally obtained by weighting the componentsʹ brightness temperatures and their fractions using a Gaussian point spreading function (PSF) of the sensorʹs response. Simulation results indicate that a small footprint causes the distribution of the DBT to be strongly dominated by the row direction and a single componentʹs temperature but little influenced by the solar position. On the contrary, a large footprint smoothes the row-space effect and causes the DBT to distribute as a uniform, continuous canopy. Comparison with a previous parallel model shows that if the diameter of the sensorʹs circular footprint extends to 1.5–2.0 times as large as the total width of the row crop canopy, the footprint effect is minimized, and the ground measured DBT can, theoretically, be used to evaluate the parallel model with negligible error. Finally, validations with a maize canopy demonstrated that the new model performed more accurately than the parallel model to simulate the DBT. Moreover, the FovMod also provides an opportunity to assess the measurement uncertainty caused by some unexpected changes in the sensorʹs footprint.