Synergy Of Optical And Microwave Remote Sensing With Respect To Agricultural Crops Illustrated With MAC Europe Campaign 1991

Abstract

Remote sensing techniques in agriculture have evolved to more or less operational tools for the estimation of characteristics of the studied object. These tools consist of forward modeling, which represents a (physical) description of the measurement situation, and of inverse modeling, which consists of mathematical techniques to invert the interaction models. In the visible and the microwave region of the spectrum, complementary information of the studied object can be derived with inversion of these remote sensing models. In this paper simple models have been used to illustrate the methodology. Inversion can be accomplished by using linearization techniques and sensitivity analysis of the RS model in study, in order to derive simple linear equations. With help of singular value decomposition these linear equations can be solved which will lead to a set of possible parameter combinat ions. A priori knowledge as the type of vegetation, conditions, time of the year, variations in sensortype, etc. is vital to narrow the solution space. Therefore crop growth models will contribute to a better insight of the inversion problem. Errors in estimation of these parameters can be expressed in confidence limits. The European Multi-Aircraft Campaign (MAC’91) combined a wide spectrum of sensors deployed in the growing season June, July and August 1991. For the first time identical microwave and optical sensors were flown over test sites in The Netherlands, Germany, UK, France and Italy. To illustrate the methodology we use the data sets of the AGRISCATT’88 campaign with its extensive grounddata survey and the Mac-Europe 1991 campaign