Precision Farming and Earth Observation

Repost from Medium Corp

For farmers and land managers, increasing crop yields and cutting costs while reducing environmental pollution is a constant challenge. To accomplish this goal, many farm managers are looking for new technologies to help them decide when and where to irrigate, fertilize, seed crops, and use herbicides. Using data collected by satellites combined with GIS environments, important agricultural factors like plant health, plant cover and soil moisture can be monitored from space, provide a much bigger picture of the land surface that can be combined with other technologies to help cut costs and increase crop yields.

The long term archiving of Landsat imagery and the relatively new ESA’s Sentinel-2 and yield mapping datasets sensed by precision agriculture allow yield predictions at a higher resolution, where the pattern of measurements highlights yield performance differences due to soil type and topographic location and where large variations in yield are evident.

By using different types of visual resolutions (RGB composites, multitemporal NDVI indices), a farm operator can determine the issues affecting their crops and apply appropriate remedies to affected areas. If spectral resolution has identified areas within the crop-field as having too little or too much of a given nutrient for example, farmers can apply less or more fertiliser to those areas as needed, as opposed to treating the entire field with an evenly metered dose.

Just to give an example, let’s see three different indexes that both Landsat and Sentinel can produce:

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