# Application of Reflectance Indices for Remote Sensing of Plants and Revealing Actions of Stressors
## 2 Optical Methods and Platforms of Remote Sensing of Plants  
### Main Optical Methods of Remote Sensing  
The remote sensing of plants is often based on optical methods, including imaging of a chlorophyll fluorescence, RGB imaging, thermal imaging, and spectral imaging of the reflected light [23] (Figure 1). These methods are non-invasive; additionally, many of their modifications are remote and high-throughput. The RGB imaging is a very important method of plant remote sensing because it is characterized by technical simplicity and availability [23; 27]. As a result, this method can  
Figure 1: The optical methods of estimation of growth and development, physiological processes, and biochemical composition of plants, including the RGB, thermal, fluorescence, and spectral imaging. (**a**) Spectral ranges of these optical methods. (**b**) Examples of using the RGB imaging, the thermal imaging, the imaging of the chlorophyll fluorescence, and the spectral imaging of reflected light. These examples are based on works [24; 25; 26]. R, G, and B are the red, green, and blue spectral bands of the reflected light that are measured at the RGB imaging. be used for the remote sensing of plant changes on various spatial scales (from single leaf to whole ecosystem(s)) (Figure 2); at that, RGB-imaging can be used for revealing relatively slow changes in plants (from hours and even days). The RGB cameras measure light in broad spectral bands of the visible light (red, green, and blue bands) (Figure 1a); these cameras also have weak sensitivity to the near-infrared light (NIR) [28]. The RGB imaging is widely used for morphometric analysis (e.g., estimation of biomass [29] or leaf area index (LAI) [30]), recognition and classification of plants [31; 32; 33], mapping of species in the ecosystem (e.g., forest) [34; 35], and others. However, the RGB analysis is restricted by a number of problems. First, the RGB imaging can be disturbed by fluctuations in light intensity or wind gusts [27]. Second, the calibration of the RGB camera is difficult due to the nonlinear gamma correction effect [33]. Additionally, a large number of interpolations for the transformation of the RGB image to the digital surface model are necessary; this decreases the accuracy of using the RGB imaging at remote sensing of this surface [33]. Moreover, relations between the broad bands of reflectance and specific physiological changes can be weak (e.g., these bands are not significantly related to changes in the parameters of photosynthetic light reactions [36]). Finally, the structural analysis of the plant canopy on the basis of the RGB imaging has limitations and requires special software [33]. Another prospective method of plant remote sensing is the measurement of a chlorophyll fluorescence, which is strongly related to the distribution of energy in the photosynthetic apparatus [37]. There are active (the fluorescence is induced by special measuring light with controlled intensity) and passive (the fluorescence is induced by ambient light) methods of fluorescence imaging [38]. The emission of the chlorophyll fluorescence is mainly observed at a 650-750 nm spectral range; the fluorescence is maximal at about 680 nm [39] (Figure 1a). The active measurements of the chlorophyll fluorescence are used for the estimation of photosynthetic activity on spatial scales from leaves to plants. However, using the active illumination of plants by the measuring light strongly limits the application of this method in cases of the remote sensing of canopy or ecosystems because long distances between the camera and plants are necessary in these cases [38] (Figure 2). In contrast, the passive measurement of the chlorophyll fluorescence does not require using the artificial measuring light because the ambient light (especially sunlight) is used for the fluorescence induction in this method [38; 40].