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Remote sensing with NDVI

What is satellite remote sensing?

Remote sensing uses satellites, ground-based weather stations and machine learning to capture NDVI and weather data.

The NDVI and weather data can be used to identify problems on the field, plan your tasks, and assess yield potential during the season.

Watch the video to learn more ➔

 

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Why use NDVI?

Locate problems on the field

  • Use with NDVI, NRI and NDWI pictures during the season
  • Discover drainage issues, nitrogen deficiencies, and Ph problems
  • Control your fields and ensure workers are not mismanaging your fields with NDVI pictures
  • Know exactly where to walk on the field to identify the problem areas

Plan your tasks

  • Ensure you are sowing when the temperature is right and the soil is dry enough
  • Spray and fertilize at the right temperature and wind speed with weather prediction
  • Harvest at the right time by predicting rains with weather prediction

Assess yield potential

  • Use temperature, rainfall, and past NDVI performance of your crops to assess yield potential
  • Predict the growth stages of your plant
  • Calibrate your investment decisions on the field based on the prediction

Technical specifications

  • Use 10m satellite images – the best value in the market
  • Images are taken multiple times a week – using Sentinel-2 and Landsat-8 satellites
  • Automatically filter out cloud images – don’t waste your time on bad pictures
  • Local weather captured with radars, a vast network of weather stations, along with data from global/local providers such as NOAA, Environment Canada, Met Office and calculated using proprietary convolutional neural network / Machine Learning model

Write to us through the chat bubble to sign up!