Abstract
For the remotely sensed input parameters, such parameters as the maximum or minimum surface temperature, diurnal variation of the surface soil temperature, daily maximum soil minus air temperature and thermal inertia were examined in some approaches previously proposed for estimating soil moisture with thermal infrared data.
In this paper the author discussed a new parameter which was the normalized rising rate of surface radiant temperature on the basis of experimental results and the soil moisture estimation models by means of multivariate analyses after clarifying the correlation between the surface radiant temperature and soil moisture from the point of view of the surface energy balance and soil physics.
The results in table 2, 3 showed the best correlation for the samples obtained from the Kanto loamy soil especially in the summer, in comparison with other of the samples or samples of paddy soil, and the correlation result for the soil moisture 5 cm in depth showed better correlation coefficient than that of 10 cm in depth within a same soil.
According to linear regression analyses carried out to relate soil moisture in both depth to surface temperature or its rising rate, the model was best fitted to the samples of the Kanto loamy soil in summer, though the regression coefficients of the models fluctuated in the other seasons.
In consequence, future analyses under certain limiting conditions, such as suitable sites and periods of observations would lead to the feasibility of quantitative estimation of soil moisture with the rising rate of surface radiant temperature.
