It is not only the commercial world that has taken to this technology. There is a whole open source DIY community focused on building autonomous vehicles. Although not specifically aimed at agriculture, DIY Drones along with it’s partner 3D Robotics has developed hardware and software capable of controlling unmanned planes, …copters and rovers. The beauty of this is that the software is essentially free and the hardware is reasonably priced and readily available. Also, there is a community that is openly discussing and evolving the project so it is relatively easy to troubleshoot and learn a bit of what goes on behind the scenes.
A few months ago I took the plunge and ordered the hardware needed to build an autonomous vehicle. I designed and built a small rover that uses two 500W electric motors as it’s ‘powerhouse’. It works with tank style steering. It is essentially a large remote controlled car. The ArduPilot Mega (APM) sits between the remote control receiver and the motor controller (Sabertooth 2×60). The APM has an internal compass, external GPS and an external radio transmitter/receiver.
Using the Mission Planner software you can set waypoints that the rover follows. The rover’s GPS position, speed and other information can be monitored from within the Mission Planner software as the rover completes it’s mission.
I have put together a small video that shows the basic operation of the autonomous vehicle.
The question you are probably asking is ‘Why is this significant?’ or ‘Whats the point?’. The answer is that it is part of the next step in agriculture. Queensland University of Technology (QUT) is involved in similar research. Imagine a fleet of small autonomous vehicles sent to patrol the summer fallows to keep them weed free. For me, building a simple autonomous vehicle of my own shows that the technology exists, it is not that expensive and commercially, shouldn’t be to far away.
My next steps are to use sonar sensors to implement object avoidance. Further down the track I will think about mounting a camera or some other sort of sensor to collect data.
February this year USGS has sent another satellite up into orbit to continue observing the earth. This satellite, named Landsat 8, provides the same spatial resolution in all bands as Landsat 7. That is one pixel equals 15m pan-chromatic and 30m for all other bands (excluding thermal). In addition, it has a couple extra bands for water, cloud and surface temperature (this link explains the other similarities and differences in more detail).
Here is a sample that I have pan-sharpened using the open source Orfeo Toolbox. Bands displayed are 6, 5 & 2, which is comparable to 5, 4 & 1 in Landsat 5 & 7. This image was capture 27th of May 2013. Most of the bright green paddocks are canola and you can see some of the earlier cereals coming through.
More info: As suggested in comments, Spectral Transformer for Landsat-8 imagery by GeoSage is another free option for pan-sharpening Landsat 8 imagery. I have tried it and it works well if you don’t mind following some simple command line instructions. Check it out at this link.
Even more info: To get an idea of the best Landsat 8 band combinations and comparison with Landsat 7 bands check out this blog article from ESRI.
Our winter plant operation has finished for another year. We came into May with good sub-soil moisture but dry in the top 10cm. The wheat and barley was planted shallow into the dry soil. A 12mm fall of rain mid-May was enough to wet up the soil and germinate the seed. Following the rain we planted chickpeas into moisture. After finishing planting the chickpeas we had another 10mm.
We are trialling Spitfire and Suntop wheat this winter, alongside our usual Sunvale. Below are some comparisons so far.
And a couple pictures of our chickpeas and malt barley.