Remote sensing techniques for estimating six crop biophysical and biochemical characteristics—vegetation fraction, fraction of photosynthetically active radiation absorbed by photosynthetically active vegetation, chlorophyll content, nitrogen content, green leaf area index, and gross primary production—are presented in this chapter. All techniques were tested using reflectances acquired from close range (6 meters above the top of the canopy) and TM/ETM+ Landsat, MODIS, and MERIS satellite data. It was shown that the aforementioned characteristics can be estimated accurately using remotely sensed data. Moreover, generic algorithms were developed not requiring parameterization for crops studied. With these techniques, it is now possible to obtain global synoptic estimates of crop biochemical and biophysical characteristics at 20 and 30 m spatial resolution (Sentinel-2, Landsat TM/ETM+) and 250 m/300 m resolution (MODIS and Sentinel-3). The performances of the algorithms were tested for maize, soybean, potato, rice, and wheat. These crops have very different canopy architectures and leaf structures. Still, the techniques developed yielded accurate estimation, which indicates that these techniques are likely applicable to other crops as well.