Reaping What You Sow
Aerial vegetation monitoring allows farmers to quickly assess and manage the health of their crops, improving yields and minimizing the use of irrigation, fertilizers and pesticides. The combination of unmanned aerial vehicles (UAVs) and compact spectrometers has increased the popularity of this form of remote sensing over the past decade. As the technology moves to the next level, lightweight, cost-effective microspectrometers like our STS are being designed into stand-alone systems that deliver high spatial and temporal resolution, allowing precision management of crops within a single field.
A multinational team of researchers at the Research Center Jülich IBG-2 Plant Sciences, Germany, has developed an airborne system to bridge the gap between ground-based and aerial hyperspectral imaging, using an Ocean Optics STS microspectrometer and open source electronics deployed on a UAV to scan a field and report data back wirelessly with GPS tagging. When synchronized to a ground-based STS microspectrometer viewing a reference standard, the spectra can be processed and compared to produce reflection spectra for the vegetation as a function of location.
Data from an airborne spectrometer is referenced against a ground-based spectrometer to calculate reflection spectra of vegetation.
The team tested the system on grasslands in New Zealand at a height of 20 m, scanning a pasture in a grid pattern and collecting at least three spectra at each location, with a 24° field of view. To validate the measurements, spectra were compared to readings collected using a ground-based spectrometer (75 spectra per location). Not only did all the UAV-based system measurements fall within the range of variability of the ground-based spectra, they did so with a 6x smaller standard deviation and were collected in 1/20 the time.
Reflection spectra from an airborne spectrometer agree with ground-based measurements, and can be captured with less variability and greater speed.
More Eyes in the Sky
Once acquired, the reflection spectra can be fed into processing software to calculate crop health indicators like chlorophyll concentration, canopy water content and Leaf Area Index (green leaf area per unit ground surface area). These parameters are used to assess plant vitality and serve as an early indicator of plant damage so that farmers can intervene rapidly to maximize crop yields with minimal use of resources. With a working altitude of up to 200 m and the ability to rapidly generate an accurate hyperspectral map in real time, this remote sensing system promises to put an effective and economical tool for crop management into the hands of more farmers than ever before.
The technology is used in apps like Cropio.
(Based on – http://oceanoptics.com/crop-monitoring/)