The first generation of cameras and photography was introduced in approximately 1816  and since then have been used for almost all applications we know. Despite some inherent advantages of analog film photography, such as higher spatial resolution, transition to digital imaging was inevitable . Photoreceptor cells in the human eye respond to violet (~440 nm), green (~540 nm), and yellow (~570 nm) light more than other bands. Similarly, in digital photography, the sensors are designed to be sensitive to specific bandwidths, and at least three bands combined to form a color image. For example, Blue (~ 450-490nm), Green (~ 520-560nm), and Red (~ 635-700nm) bands are combined to form a color image in RGB space. Sensors based on this band combination are referred to as RGB cameras with the primary purpose of mimicking the human eye in the digital world. These cameras are readily available off the shelf and has been used in many agricultural studies.
RGB cameras are extensively used for studying phenomena in which plants show visual symptoms such as diseases that affect the color composition of the leaves and visible pests or fungi on the leaves. This type of research needs high spatial resolution images that are available in RGB cameras more than other bands due to the high energy level at this region, as discussed in the previous section. Sometimes a camera is sensitive to all (or a large portion of the) wavelengths in the visible range that produces panchromatic images which usually have higher spatial resolution compared to images created by separate bands. This is because detectors on panchromatic cameras receive cumulative energy from the whole spectral range and, as a result, smaller detectors can be utilized and still sustain a high signal-noise ratio. Overall, images acquired in the visible region, whether panchromatic or RGB, are endowed with a high spatial resolution that makes these images a perfect choice for studies that need the most details.
Moreover, RGB cameras has been widely utilized for Greenness identification using various visible spectral indices as described in the following table:
Table 4- Some of the common vegetation indeces used for Greenees Idnetification using RGB cameras
Various combinations of R, G, and B bands are intended to minimize the environmental and lighting effects to achieve the best segmentation of green vegetation from the rest of the image. However, their unstable thresholding limits the usage of these indices. Cameras that take advantage of at least one band in Near-Infrared (NIR) region, such as Colored Infrared (CIR) or multispectral cameras, perform significantly better than RGB cameras that rely solely on visible region, in terms of vegetation segmentation  and canopy cover estimation throughout season.
One of the points that should be considered when using an RGB camera as a remote sensing device is that most of the RGB cameras are designed in a way that can capture relatively wide range in red, green, and blue regions and store them as separate arrays. The central band and bandwidth of different sensors might differ from each other, producing some inconsistency in the results that should be acknowledged. Moreover, sometimes measurements from a very narrow target wavelength are required without being affected by the adjacent wavelengths. As a result, digital sensors should be designed to be sensitive to the proposed narrow bands only, and an RGB camera cannot be used even though the goal bands are in the visible region. For instance, the Photochemical Reflectance Index (PRI) that is a powerful indicator of productivity and stress in both agricultural and forest ecosystems , can be derived from narrowband absorbance of xanthophyll pigments at 531 and 570 nm. Using an RGB camera for this index will not produce satisfactory results unless the camera is modified to filter unrelated bands.
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