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Analyzing Crop Yields by Drone

Posted 9 years ago
POSTED BY: Arnoud Buzing
5 Replies

Another interesting article on the subject:

Artificial intelligence + nanosatellites + corn: This startup uses machine learning and satellite imagery to predict crop yields

enter image description here

POSTED BY: Vitaliy Kaurov

This looks like a very promising direction in Agriculture. I just saw this article:

Six Ways Drones Are Revolutionizing Agriculture

and it mentions the following summary:

  1. Soil and field analysis: Drones can be instrumental at the start of the crop cycle. They produce precise 3-D maps for early soil analysis, useful in planning seed planting patterns. After planting, drone-driven soil analysis provides data for irrigation and nitrogen-level management.

  2. Planting: Startups have created drone-planting systems that achieve an uptake rate of 75 percent and decrease planting costs by 85 percent. These systems shoot pods with seeds and plant nutrients into the soil, providing the plant all the nutrients necessary to sustain life.

  3. Crop spraying: Distance-measuring equipment—ultrasonic echoing and lasers such as those used in the light-detection and ranging, or LiDAR, method—enables a drone to adjust altitude as the topography and geography vary, and thus avoid collisions. Consequently, drones can scan the ground and spray the correct amount of liquid, modulating distance from the ground and spraying in real time for even coverage. The result: increased efficiency with a reduction of in the amount of chemicals penetrating into groundwater. In fact, experts estimate that aerial spraying can be completed up to five times faster with drones than with traditional machinery.

  4. Crop monitoring: Vast fields and low efficiency in crop monitoring together create farming’s largest obstacle. Monitoring challenges are exacerbated by increasingly unpredictable weather conditions, which drive risk and field maintenance costs. Previously, satellite imagery offered the most advanced form of monitoring. But there were drawbacks. Images had to be ordered in advance, could be taken only once a day, and were imprecise. Further, services were extremely costly and the images’ quality typically suffered on certain days. Today, time-series animations can show the precise development of a crop and reveal production inefficiencies, enabling better crop management.

  5. Irrigation: Drones with hyperspectral, multispectral, or thermal sensors can identify which parts of a field are dry or need improvements. Additionally, once the crop is growing, drones allow the calculation of the vegetation index, which describes the relative density and health of the crop, and show the heat signature, the amount of energy or heat the crop emits.

  6. Health assessment: It’s essential to assess crop health and spot bacterial or fungal infections on trees. By scanning a crop using both visible and near-infrared light, drone-carried devices can identify which plants reflect different amounts of green light and NIR light. This information can produce multispectral images that track changes in plants and indicate their health. A speedy response can save an entire orchard. In addition, as soon as a sickness is discovered, farmers can apply and monitor remedies more precisely. These two possibilities increase a plant’s ability to overcome disease. And in the case of crop failure, the farmer will be able to document losses more efficiently for insurance claims.

See more related content at PwC global report on the commercial applications of drone technology.

POSTED BY: Vitaliy Kaurov
Posted 9 years ago

Fantastic stuff Arnoud!

I did try to play around with ta similar concept using the Landsat information (http://landsat.usgs.gov/) using the earth explorer app.

Mathematica is such a wonderful tool!

More details in the use of Landsat images.

http://www.nass.usda.gov/EducationandOutreach/Reports,PresentationsandConferences/Presentations/BoryanSeffrinJohnsonFASSeminar06.pdf

POSTED BY: Diego Zviovich

Is there any way to estimate the total bushels estimated from the area rather than a percentage?

POSTED BY: Roman Kopytko

Yes, but you need the geo position and the elevation of the drone/camera as well as the camera field of view, to compute the area that's visible in the image.

And an estimate of the "normal" yield in bushels for a given acre.

POSTED BY: Arnoud Buzing
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