Study of Temporal Behaviour of Homogeneity Maps for Estimating Representative Area of a Ground Sample Using Remote Sensing

Abstract

Modelling and prediction of hydro-meteorological variables over land and atmosphere involve ground sampling at selected locations over the study area. Optimally selecting the number and location of sampling points is important for making reliable predictions without escalating project costs. This study proposes an approach for selecting sampling locations by considering inter-dependency of predictor variables and the prediction variable using remote sensing data. A homogeneity map, i.e., a thematic map representing areas with the same expected value of the prediction variable, with a given level of uncertainty and spatial resolution, is generated. The homogeneity maps can be different at different times for the same location. Thus, along with the spatial variability of the prediction variable, its temporal variability is also obtained. Depending on the obtained variability, a decision on the number and location of sampling points can be taken prudently. In this paper, the proposed methodology is demonstrated by considering soil moisture over an experimental watershed as the prediction variable.