Multispectral cameras are one of UAVs most impressive added payloads. They allow farmers to monitor and maintain their crops, as well as managing fertilising and irrigation more effectively.
There are massive benefits to the farmer, and the environment as a whole. It reduces the need for sprays and fertilisers, as well as water wastage. At the same time, it also increases the yield from crops.
The images created then integrate with specialised software which turns the image into meaningful data. Pix4D is usually the software of choice. The gathered data allows the farmer to manage their farm more effectively, and saves time and money.
The two main multispectral cameras are the MicaSense RedEdge and the Parrot Sequoia. First, we’ll take a look at the Rededge.
MicaSense RedEdge
The MicaSense RedEdge is one of the most advanced multispectral cameras, and is specially designed for small unmanned aircraft systems. It provides incredibly accurate multiband data for agricultural remote sensing, as well as providing you with scientific grade imagery. The RedEdge’s compact design allows it to seamlessly integrate with as many drones as possible.
The RedEdge-M has five bands—blue, green, red, red edge, and near-infrared. This data provides the operator with exceptional levels of data. This data can be used to analyse crops and make informed harvesting decisions.
You also need not worry about distortion in your images. The global shutter design allows images to be captured adeptly. It also makes used of geo-tagging and time stamping, as well as a more advanced self-triggering function and external GPS connections.
How accurate are its sensors?
The Rededge has high precision, and incredibly accurate sensors. You can fly across an 100-acre field (at 400 ft above ground level, 70% overlap) in only 27 minutes.
You have access to the raw data collected by RedEdge-M, thus meaning you can choose between various processing and analysis platforms. Alternatively you can process and analyse the data yourself.
See the RedEdge in action:
https://youtu.be/vIvOJtt0P9g
Parrot Sequoia
The Parrot Sequoia is a multispectral camera, and has been specially designed for use with all types of drones.
With its two sensors, multispectral and sunshine, Sequoia analyses plants’ vitality by capturing the amount of light they absorb and reflect. This intelligent data allows farmers to take optimal action on their land including the accurate spraying of expensive fertiliser.
The Sequoia enables farmers to take action at micro-plot level and provides accurate information on the plants health. It allows you to optimise the use of fertiliser by varying the quantity depending on your need. You can also reduce the number of pesticides to only the plots that require it and allows the user to analyse plants behaviour.
The Sequoia is data accessible on all devices whether on a computer, smartphone or tablet due to its Wi-Fi and USB connections.
Advanced data capture
The sequoia features two sensors. The multispectral sensors captures the light from the plants in four separate parts: green and red lights and two infrared bands that are invisible to the human eye.
The sunshine sensor records the intensity of light emanating from the sun in these four same bands of light. The Sequoia provides you with advanced agriculture technology.
See what the Sequoia has to offer:
Summary
The Parrot Sequoia and the Micasense RedEdge are two fantastic multispectral drones, and are the finest on the market. Click here to see our blog where we pit the RedEdge and the Sequoia against each other.
Multispectral cameras are of huge importance to the agricultural industry. They offer and time & energy saving solution, and therefore is incredibly cost effective. The use of multispectral cameras is only likely to grown in the agricultural industry, and it won’t be long before they are being used far wider across the industry.
Speak to the experts:
Contact us or alternatively, call our friendly team on 0330 111 7177 to discuss your drone camera needs or contact us via email at info@coptrz.com if you’d prefer.
