fbpx

Satellite Imagery: minimize your inputs and maximize your yield

Did you know that you could have a complete view of your farm thanks to satellite imagery, thus detecting problematic areas?

Remote sensing, a rich source of information with the advantage of being fast and non-destructive, is widely used in agriculture to increase productivity and profitability by promoting growth. In agriculture, remote sensing is based on the analysis of the interaction between radiation and plant cover.

In addition, remote sensing methods allow you to monitor your crops from a distance. SOWIT offers you the opportunity to improve the operational efficiency of your farm with scalable smart agriculture solutions combining satellite and meteorological data, such as the MONITOR+® solution.

Figure 1: Monitor+ interface

MONITOR+ allows the optimization of yields thanks to a better knowledge of crop needs, the use of historical data and a real-time view of crops (weather, intra-plot heterogeneity, etc.) to guide you in decision-making, thus limiting the loss of inputs.

How does it work ?

The water and pigment content of the leaves, as well as the internal structure of the plants change when they are infected by a disease, deficiency or infested by pests. These physiological and biochemical changes are reflected in their spectral signatures. Spectral signatures are the characteristic electromagnetic emissions of an object as a function of wavelength.

Figure 2: Spectral signatures of water, soil and vegetation; source ESA

In remote sensing, it is common to use band ratios, commonly called indices, to be able to identify certain characteristics of plants. The choice of vegetation indices is crucial for monitoring your farm. Among those used by SOWIT are, NDVI and NDWI.

  • Normalized Difference Vegetation Index (NDVI), highlights the health and vigor of vegetation.
  • NDVI=(NIR-R)/(NIR+R)

 NIR = Near Infrared reflectance; R= the reflectance at Red

The result of this formula generates a value between -1 and +1. If you have low reflectance (or low values) in the red channel and high reflectance in the NIR channel, it will give a high NDVI value. And vice versa.

Figure 3: Example of NDVI calculation; source NASA
  • Normalized Difference Water Index (NDWI), is used to highlight open water features in a satellite image, which allows a body of water to “stand out” from the ground and vegetation, subsequently allowing to highlight the water content of the leaves.
  • NDWI = (G – NIR)/(V=G + NIR)

NIR = Near Infrared reflectance; G = reflectance to Green

With SOWIT, get recommendations specific to your plot. Join us for a unique experience!

Monitor+®
Share on facebook
Share on twitter
Share on linkedin

Subscribe to our newsletter

* indicates required
Post Categories