The availability of high spatial and temporal resolution optical remote sensing data allows the estimation of biophysical parameters for a wide territorial coverage. The present studies analysed the use of physically based approaches for the quantification of the Leaf Area Index (LAI) and other important vegetation characteristics. Comparisons with traditional empirical models, using vegetation indices, are performed. Furthermore, the relevance of canopy reflectance models for precision farming applications, such as the detection of drought stress zones, monitoring of vegetation growth and dynamic and energy balance modelling, is highlighted. The models were validated and moreover, the physiological reaction of plants to drought stress and recovery was analysed by means of optical leaf reflectance field and laboratory measurements. Additionally, the configuration of the forthcoming ESA Sentinel-2 mission was tested in an operative perspective. Summarizing the results of all studies, it could be shown that optical remote sensing is a valuable tool rather for estimating structural changes of the canopy (such as LAI) than for an early drought stress detection. The physically based estimation of surface parameters could be performed for a wide range of conditions, i. e. for different geographical locations, sensors and vegetation types, and in a satisfyingly accurate way using turbid medium modelling schemes. The method is therefore recommended for an operational quantification of biophysical products or for the determination of medium or longer term drought stress in agricultural and forestry applications.