Precision Agriculture with NDVI

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 Agriculture Drones and Precision Agriculture with NDVI

Imaging with Multispectral Sensors

Agri Data Outputs Available with QuestUAV Drones

Optical Imagery

Optical Sensor Results taken by drones for Agriculture

Aerial imaging and 3D mapping

Topographic surveying

Plant counting/plant density

Field layouts/ infrastructure

Drainage designs

Multispectral Imagery

Multispectral Sensor Results as NDVI Image

Normalised Difference Vegetation Index calculation (NDVI)

Crop health/status

Growth monitoring

Pest and disease detection

Impact of chemical/biological treatments

Thermal Imagery

Thermal Sensor Results

Crop health

Water temperature detection

Water source identification

Livestock detection

Surveillance and security

What is NDVI?


NDVI stands for Normalised Difference Vegetation Index.  When used with drone sensors and agriculture NDVI is the classic indicator of plant health.

A technical explanation... live green plants absorb solar radiation which they use as a source of energy in the process of photosynthesis. Leaf cells emit more solar radiation in the near-infrared than in the visible spectral region. Hence, live green plants appear relatively bright in the near-infrared. The pigment in plant leaves, chlorophyll, strongly absorbs visible light (from 0.4 to 0.7 µm) for use in photosynthesis. The cell structure of the leaves, on the other hand, strongly reflects near-infrared light (from 0.7 to 1.1 µm). The more leaves a plant has, the more these wavelengths of light are affected, respectively.  The NDVI is calculated from these individual measurements as follows:

{mbox{NDVI}}={frac {({mbox{NIR}}-{mbox{VIS}})}{({mbox{NIR}}+{mbox{VIS}})}}

where VIS and NIR stand for the spectral reflectance measurements acquired in the visible (red) and near-infrared regions. Drone sensors using normal RGB along with infra-red, or or multispectral sensors capturing light in the 600 to 800nm range will be the most effective in providing the data for NDVI. Once processed, a farmer can analyse NDVI images for a range of indicators of crop status, plant vigour or disease. In particular an agronomist can analyse contrasting areas of plant vigour and be able to cover large inaccessible areas of land for analysis.

About the Use of Drones in Agriculture

Image of DATAhawk in Farm Land

The use of drones for agriculture, specifically in Precision Agriculture and farm management, has been rapidly increasing over the past five years. UAVs are a revolutionary tool for gaining knowledge about the development of a crop and hence for boosting yields and maximising production efficiency.

UAVs have the unique advantage to provide rapid response data of farmland with a high level of detail. Hundreds of hectares can be covered in a single flight at a lower cost and much higher spatial resolution than manned flights or ground surveys.

Photogrammetry software transforms the acquired information into orthomosaics and 3D models and creates a digital three-dimensional representation of the status of a field. When multispectral data is acquired, algorithms like the Normalised Difference Vegetation Index (NDVI), can be applied and become the basis for monitoring plant growth and examining crop health.

UAVs carry different sensors such as optical, multispectral or thermal modules which are used for a range of applications in farm management.

QuestUAV drones are operated over agricultural areas across the world over different crops and in different climates. For example, farmers fly QuestUAV drones in the UK to monitor the growth of potatoes and optimise fertiliser application while on the other side of the world plantation owners in the Philippines survey pineapple fields with the same type of drone to detect plant diseases and optimise water drainage.

Reviews and Articles on our Agri Drones

Multispectral Field Monitoring with the QuestUAV DATAhawkAG, MicaSense RedEdge and MicaSense ATLAS

QuestUAV’s All-Round Package for Precision Agriculture Mapping Multispectral Field Monitoring with the QuestUAV DATAhawkAG, MicaSense RedEdge and MicaSense ATLAS Simple Mapping Workflow - Quality Data - Better Decisions Aerial images captured with a drone is a great asset for growers and agronomists. They can monitor the health and vigour and track change over time. When […]

QuestUAV Training Team Starts Large-Team International Training with the Q-200 with GGP

QuestUAV's Flying Team Starts Large Team International Training One of QuestUAV Ltd's flight training teams arrived in Indonesia this past weekend, to provide in-country training for GGP (Great Giant Pineapple). Sunday saw the completion of a successful series of test flights with Q-200 AGRI Twin NDVI aircraft.                 […]

Maximizing a Fruit Plantations Yield using UAV Imagery | QuestUAV News

Maximizing a Fruit Plantations Yield using UAV Imagery Plant Counting and Gap Filling Techniques Determining plant density and identifying canopy gaps is crucial for good plantation management; this helps predict yields and to maximize the yield by refilling planting gaps. Scientific photographs taken from Unmanned Aerial Vehicles (UAVs) allow accurate plant counts and the identification […]

Photogrammetry Dramatically Increases Lifetime of Worlds Largest Pineapple Plantation | QuestUAV News

UAV Image Interpretation Dramatically Increases the Lifetime of the World’s Largest Pineapple Plantation Soil Erosion Reduced by a Factor of Almost Thirty, Ensuring Fruit Cultivation for the Next 100 Years Key Achievements Scientific photographs taken from Unmanned Aerial Vehicles, like the QuestUAV Agri-Pro system, and processed with Pix4D are a powerful tool to fight soil […]