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What is multispectral imaging and why are farmers in South Carolina using it?



Multispectral drone imaging is a cutting-edge technology that is revolutionizing the way farmers and agricultural researchers analyze and monitor crops. Multispectral imaging captures and analyzes data across a range of different wavelengths. This allows for a more comprehensive understanding of an object or scene, as each wavelength can reveal different information. By using drones equipped with multispectral cameras, farmers and researchers can quickly and easily capture data across a range of different wavelengths, including visible light, and infrared.


One of the biggest advantages of multispectral drone imaging for agriculture is that it allows farmers and researchers to quickly and easily identify problems with crops, such as pests, diseases, and nutrient deficiencies. By analyzing the data captured by the multispectral cameras, farmers and researchers can identify areas of the crop that are not healthy, and then take steps to address the problem.


Multispectral drone imaging is also useful for monitoring crop growth, yield, and water use. By analyzing the data captured by the multispectral cameras, farmers and researchers can determine the most efficient times to plant and harvest crops, as well as identify areas of the field that may need more water or fertilizer.


Another important application of multispectral drone imaging for agriculture is in precision farming. Precision farming is an agricultural technique that uses technology to optimize crop yields by precisely targeting inputs (e.g. seed, water, fertilizer) to specific areas of the field. Multispectral drone imaging allows farmers and researchers to identify variations in crop health and growth, which can then be used to create precision maps that guide where inputs are applied.


Overall, multispectral drone imaging is a powerful tool that is changing the way farmers and agricultural researchers analyze and monitor crops. With the ability to quickly and easily capture data across a range of different wavelengths, farmers and researchers can identify problems with crops, monitor crop growth, and even optimize crop yields. Multispectral imaging can be processed to produce multiple types of maps. The Mavic 3M we use at Aero AG can produce the NDVI, GNDVI, and NDRE maps.


What is NDVI?




Normalized Difference Vegetation Index - In precision agriculture, NDVI is used to measure biomass. Whereas, in forestry, it is used to quantify forest supply and leaf area index.




NDVI is a widely used index in agriculture that uses multispectral drone imaging to measure the health and productivity of plants. NDVI compares the difference in reflectance between the near-infrared and red regions of the electromagnetic spectrum, and is based on the principle that healthy plants reflect more near-infrared light and less red light than unhealthy or stressed plants. NDVI can be used to identify problem areas in crops, monitor crop growth, and optimize crop yields through precision farming. NDVI values can be obtained using multispectral cameras or satellite imagery, and are calculated using a specific formula. NDVI is an important tool that helps farmers and agricultural researchers to make informed decisions about crop management.


What is NDRE?


NDRE – Normalized Difference Red Edge - Index sensitive to chlorophyll content

in leaves against soil background effects. This index can only be formulated when the red edge band is available.


NDRE (Normalized Difference Red Edge) is an index that uses multispectral imaging to measure the health and productivity of plants in agriculture. It compares the difference in reflectance between the red edge and red regions of the electromagnetic spectrum. NDRE is based on the principle that healthy plants reflect more red edge light and less red light than unhealthy or stressed plants.


NDRE is similar to NDVI but it uses a different part of the spectrum, the red edge, which is the region of the spectrum where chlorophyll absorbs light the most. NDRE has been proven to be more sensitive to changes in chlorophyll content, making it useful to detect early signs of stress or nutrient deficiencies. NDRE can also be used to monitor crop growth, yield, and water use and NDRE values can be used to create maps that show the health and productivity of a crop at different stages of growth, which can be used to guide crop management decisions.


What is GNDVI?



GNDVI – Green Normalized Difference Vegetation Index - GNDVI index uses visible green instead of visible red and near infrared. Useful for measuring rates of photosynthesis and monitoring the plant stress.



GNDVI (Green Normalized Difference Vegetation Index) is an index that uses multispectral imaging to measure the health and productivity of plants in agriculture. It combines the NDVI and NDRE indices to improve the accuracy of vegetation monitoring and to provide a more accurate assessment of the greenness of vegetation. The Green reflectance in GNDVI comes from chlorophyll content, which makes GNDVI more sensitive to changes in chlorophyll content than NDVI, NDRE or other vegetation indices.


GNDVI can be used to identify areas of a crop that are not healthy, such as those affected by pests, diseases, or nutrient deficiencies. It can also be used to monitor crop growth, yield, and water use. GNDVI values can be used to create maps that show the health and productivity of a crop at different stages of growth, which can be used to guide crop management decisions.


GNDVI can also be used to detect variations in crop health and growth, which can then be used to create precision maps that guide where inputs are applied. GNDVI can be helpful to detect the areas of the field that may need more water or fertilizer, helping to optimize crop yields by precisely targeting inputs to specific areas of the field. GNDVI is a powerful tool that helps to identify and understand the health and productivity of plants and crops by using multispectral imaging.


Mavic 3M


At Aero Ag we use the DJI Mavic 3M to produce multispectral maps. The DJI Mavic 3M is a drone equipped with a multispectral imaging sensor that is capable of capturing data in several different spectral bands including:


Red: This band is commonly used to measure chlorophyll content and vegetation density.


Near-infrared: This band is commonly used to measure plant health and water

content.


Green: This band is commonly used to measure chlorophyll content and vegetation density.


Red Edge: This band is commonly used to measure the chlorophyll content and the vegetation stress, providing early warning signs of nutrient deficiencies.


With the data captured in these different spectral bands, the DJI Mavic 3M can create a variety of different multispectral maps, such as NDVI, NDRE, GNDVI, etc, which can be used to monitor crop health, detect problem areas, and guide crop management decisions.


https://enterprise-insights.dji.com/blog/mavic-3-multispectral-top-features


How we integrate - Pix4d Fields


Pix4Dfields is a powerful software that can be used to process and analyze multispectral data captured by drones, such as the DJI Mavic 3M. To create spot spray maps in Pix4Dfields from multispectral imaging, we follow these general steps:


1. Collect multispectral data: Use the DJI Mavic 3M drone to capture multispectral data over the field of interest. Be sure to collect data in the spectral bands that are relevant for your application, such as red, near-infrared, green, red edge and thermal.


2. Process the data: Import the data into Pix4Dfields and use the software's tools to process the data, including image alignment, radiometric calibration, and orthorectification.


3. Create vegetation indices: Use the software's tools to create vegetation indices such as NDVI, NDRE, and GNDVI, which can be used to assess plant health and crop productivity.


4. Create spot spray maps: Use the software's tools to create spot spray maps by identifying areas of the field that are experiencing stress or disease, based on the vegetation indices that you created. You can define threshold values for the indices to classify the areas that need to be sprayed.

Export the spot spray maps: Export the spot spray maps in a format that can be used by your equipment, such as .kml or .shp.


5. Use the spot spray maps: Use the spot spray maps to guide your spot spraying equipment and apply inputs to the specific areas of the field that need it. At Aero AG we use our DJI Agras T40 spraying drones.to spray fields and orchards based on the maps we create.


Check out the link below to book a free demo to learn more about what we do!





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