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A large portion of the earth's surface is covered with various vegetation classes (i.e. grassland, wetland and agricultural area, forest) of many diverse species and canopy configurations. The ability to assess and to monitor canopy parameters, such as biomass, leaf area index, and vegetation water content, is of vital importance to the study of different agronomic processes. Remote sensing techniques provide a unique capability towards probing different vegetation types and canopy by operating at different bands, observation angle etc. Over the past decades, significant progress has been made in remote sensing techniques of land processes specially vegetation characteristics through development of advanced ground-based, airborne and space-borne microwave sensors, methods and approaches such as theoretical, semi-empirical and empirical models, needed for analyzing the data. These activities have sharply increased in recent years since the launch of different active and passive satellites and sensors. Remote Sensing (RS) science and techniques combined with ground truth data can provide new tools for advanced agricultural crop applications. It has been demonstrated that RS has the ability to estimate biophysical parameters of agricultural crops over time at local, regional, and global scales. In this study, RS images in visible/near infrared (VIS/NIR) domain as well as microwave domain combined with ground truth data were used to assess biophysical parameters of agricultural crop during their whole growing season at Durable Environmental Multidisciplinary Monitoring Information Network (DEMMIN) test site in North East Germany. Ground truth studies were carried out for 31 weeks during 17th April – 13th November 2013 over three crop lands including winter wheat, barley and canola. Landsat 8 OLI, Landsat 7 ETM+ were used for the VIS/NIR studies and TerraSAR-X synthetic aperture radar (SAR) images were used to study biophysical parameters of agricultural crops in microwave part of electromagnetic spectrum. The analysis was conducted by calculating different vegetation indices (VIs) to estimate the biomass (fresh and dry), LAI, and vegetation water content (VWC) of three crops using Landsat 8 OLI and Landsat 7 ETM+ combined with ground truth data. A new concept of Soil Line retrieval from Landsat 8 image was also developed to estimate plant biophysical parameters using soil line related vegetation indices in optical domain of electromagnetic spectrum. Different approaches including univariate, multivariate stepwise regression and semi-empirical water cloud model was also used to estimate the biophysical parameters of agricultural crop using TerraSAR-X data in microwave domain of electromagnetic spectrum. Perhaps the most important conclusion of this study is that the RS approach can provide useful information about estimating agricultural crop parameters over time and local scale, which can therefore provide valuable information to aid the agronomy community.