We constructed mathematical models of passive earth observation sensors common between optical imagers and microwave radiometers based on generic interpretation along with a sequence of functional blocks, namely the signal chain. These mathematical models were used to estimate the performance of main sensors, particularly such factors as spatial resolution and the signal-to-noise ratio (SNR). Moreover, these mathematical models were applied to existing sensors and their estimated performance was compared with and validated by the known sensor performance described in the literature. Such generic interpretation will make it possible to systemize the various types of earth observation sensors.

Although a vegetation index map derived from satellite images or drone observation data is useful for qualitatively identifying uneven crop growth within a field, the producer cannot use this information as a basis for predicting production volume and determining the optimum time to harvest. This is because quantitative growth information is not provided with physical units, such as plant height and above-ground fresh weight per unit area. We considered the use of close-range remote sensing measurement devices to effectively collect the ground truth data necessary to formulate the relationship between the vegetation index data derived from aerial images and quantitative crop growth information. Thus, we conducted a field observation test of Japanese mustard spinach (Komatsuna) using the GreenSeeker handheld crop sensor manufactured by Trimble and a spectral digital camera manufactured by Kimura OyoKogei Inc. to investigate the accuracy of estimating plant height and above-ground fresh weight per unit area using these indicator values. The Difference Vegetation Index derived from GreenSeeker observation raw data (GS_DVI) had a strong linear relationship with plant height (RMSE: 4.37 cm) and above-ground fresh weight per unit area (RMSE: 0.81 kg /m²).The green chlorophyll index (Cam_CI(green)), and the vegetation fraction, (VF_NIR[Maxentropy]), calculated from the multi-spectral images, also showed strong linearity with plant height and above-ground fresh weight per unit area, although the estimation accuracy was slightly less than when using GreenSeeker. These results suggest that the indices derived from the tested close-range remote sensing measurement devices are useful for quantitatively evaluating the crop growth of Japanese mustard spinach (Komatsuna).