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Multispectral Imaging Camera Drones all set to Resolve Farmers' Miseries

Enterprise Technology Review | Wednesday, August 28, 2019

The drones with multispectral imaging camera now enable farmers to yield their crops in a better way and reduce crop damages.

FREMONT, CA: Drone-supported multispectral imaging enables farmers to grow disease-resistant, drought-tolerant, and great-yielding genetically improved crops. The camera sensors capture different pictures in the ultraviolet and infrared ranges. It enables farmers to handle crops, fertilizing, yielding, and irrigation more efficiently than before. Each image captured with the multispectral camera for agriculture has to pass through a filter for restricting light to a specific color or wavelength. The multispectral sensors are of great benefit to both farmers as well as to the environment by reducing the usage of fertilizers, pesticides, wastage of water, while simultaneously proliferating the yields at harvest time.

Multispectral camera remote sensing imaging technology uses green, red-edge, red and near-infrared wavebands to take both invisible and visible pictures of vegetation and crops. The multispectral pictures blended with comprehensive agriculture software translates the information into relevant data.

So what precisely are multispectral images? A multispectral image sensor takes image data at particular frequencies across the electromagnetic spectrum. The wavelengths may be divided by filters or by the usage of instruments that are sensitive to particular wavelengths, involving light from frequencies which is beyond the reach of our sight, such as infrared. Spectral imaging also enables for drawing of additional information which the human eye fails to see.

The human eye is only sensitive to wavelengths ranging between 400 to 700nm, which is also termed as the visible spectrum. Humans can identify a variety of colors varying from violet to red. Moreover, wavelengths can be longer (infrared) or shorter (ultraviolet) than those visible to the human eye.

Even though we cannot notice them, these invisible wavelengths give indications about the characteristics of plants, soil, and crops.

So how exactly does multispectral camera agriculture work?

The camera comprises a monochrome image sensor, which consists of a two-dimensional array of pixels that are light-sensitive. These pixels are susceptible to incoming light across a vast spectral range, for example, CMOS image sensor in a monochrome. Every pixel will be sensitive to light between 400nm and 1,000nm. This will cover visible and NIR ranges, which a monochrome image sensor can hardly capture. The pictures are black and white, just like a monochrome camera. However, a color camera consists of an image sensor with a two-dimensional display of pixels. A coating of the mosaic arrangement of pigments is done on multispectral camera remote sensing, that transmits green, red or blue colors. These pigments form what is known as Color Filter Array (CFA). Multispectral camera remote sensing image technology captures image data within a particular wavelength range using Green, Red Edge, Red, and NIR wavebands to reflect both invisible and visible images of vegetation and crops.

A raw image taken with a color camera can be imagined as of three different images which, when reconciled through a process of debayering form a familiar color picture. Spectral imaging devices employ identical principles for the generation of multispectral images. However, patterning pigments, representing blue and red colors, on the image sensor spectral devices, do the sensor patterning with micro-sized optical filters, which have tunable and transmission features. A raw image taken using multispectral camera agriculture have four different images, each captured at a particular wavelength with well-defined bandwidth, such as an RGB-NIR multispectral camera. It has bands which are green, blue, red and NIR. The RGB mono multispectral camera has green, red, blue, and panchromatic bands.

The farm telemetry data enables farmers to plan, monitor, and handle the farm more efficiently, thus saving money and time as well as reducing the usage of pesticides and fertilizers.

Multispectral Imagery Basics

Every surface reflects back some amount of light that it receives. Objects which have different surface characteristics will reflect or absorb the radiations of the sun in different ways. The ratio of the incident light to reflected light is called reflectance.

Vegetation Indices (VIs)

Vegetation Indices (VIs) are usually derived by vegetation reflectance properties. Multiple ecologies are analyzed using these indices. Vegetation Indices are built from measurements of reflections in two or more wavelengths for analyzing particular features of vegetation like water content and total leaf area.

Vegetation connects with solar radiation in a different way from other natural materials, like water bodies and soils. Thus, various interactions with numerous plant materials result in the reflection and absorption of solar radiation, which varies by wavelength.

Pigments, water, carbon, and nutrients are each expressed in the range of 400nm to 2500nm of the reflected optical spectrum, with often overlapping, but spectrally different, reflectance behaviors. These signatures enable the scientists to blend reflectance measurements at distinct wavelengths for enhancement in particular vegetation characteristics by defining VIs.

Benefits of Multispectral Imaging

• Providing information on soil fertility and refining fertilization by detecting nutrient deficiencies.

• Estimating crop yield.

• Help in measuring crop irrigation by detecting regions where the stress of water is suspected. After that, improvise the land areas such as install drainage systems and waterways according to multispectral data.

• Drones with a thermal camera can be utilized to locate livestock during night time, along with many other terrific uses.

• It helps in identifying pests, diseases, and weeds. Thus, optimizing the use of pesticides and crop sprays through early detection.

• It helps in counting plants and determining population or spacing difficulties.

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