
Raptor Maps (YC S16) Uses Drones to Help Farmers Get Better Crops - stvnchn
http://themacro.com/articles/2016/08/raptor-maps/
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RaptorMaps
Hi Hacker News. This is Nikhil Vadhavkar. I'm a cofounder of Raptor Maps with
Eddie Obropta. We're super excited to announce we're a YC company today. We'll
be answering questions as much as we can. If you've ever wanted to know
anything about drones, technology and agriculture we'll do the best we can
share.

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James001
Hey Nikhil, I am interested in what you are using drones for in agriuculture.
I was using drones about 2 years ago for farming and helping farmers optimize
different things and am curious how far it's come since then.

Back then, we were just beginning to see the possibilities. Of course we'd do
drainage mapping, NDVI maps (as a yield-correlate), we found success mapping
field trials and monitoring field trials.

There were alot of possiblities we could've gotten into, but we found it hard
to totally commercialize. For example, trying to map chlorophyll content, or
water content. Water content was an easier sell, but I got the feeling that
drone-assisted precision agriculture was very much still in its infancy at
that point, more hype than substance. I am wondering what you think now? What
are you actually using your drones for, commercially, but with specific
regards to the actual agriculture decision-making.

Thanks eh.

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RaptorMaps
Hi James, great question. We have used drones of all shapes and sizes,
including off-the-shelf (DJI Phantom, S1000) and custom fixed-wing aircraft
(modified X8 flying wing, 11-ft wingspan composite plane).

We're using them to take measurements at the beginning of the growing season
(e.g., stand percentages), middle of the growing season (e.g., custom-built
sensors to hunt for specific diseases), and finally, tying that back to the
quality of the crops that are coming out of the ground. With that last
component, we can be very confident when we say our data assists with
agricultural decision-making.

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James001
Hey, thanks for responding.

I'm curious what the custom-built sensors for specific diseases are? Are you
using hyperspectral cameras? I know there was a lot of research into spectral
fingerprints of specific diseases.

Also, in regards to the data from the end of season, where you monitor the
quality of the crops coming out of the ground. How do you think that assists
agricutlrual decision-making? E.g. are you able to predict the quality of the
grain and that, in some way, makes it easier to manage?

Again, thanks for answering my questions

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eobropta
Hi James. This is Eddie, the CTO of Raptor Maps. We figured out the
combination of wavelength bands we need, and combining that with image
recognition we can identify particular diseases. We had to do a lot of
iterations and correlations to chemical samples to build up confidence that
this can actually work. We can only do a few specific conditions today in
potato farming, so I can't say this works for every disease everywhere, but
we'll keep getting better over time and are working quick to do so. The sensor
package is optics-lab style cameras tuned for wavelengths we know have the
best signal to noise ratio.

With regards to harvest monitoring, by knowing the exact yields and locations
we can correlate remote sensing data to the yield. This type of information
will help with management in the coming seasons. But it can also help today.
For example, you want to move your lower-quality inventory more quickly so it
doesn't affect the good stuff, so you want to put it by the door of the
storage facility.

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James001
Hey Eddie, thanks for getting back to me.

I was wondering when image recognition was going to play a stronger role in
the use of drones for agriculture. When I was doing it, it was simply using
combinations of spectral bands and not really delving into pattern
recognition. Sounds like that's the right way to be headed. Obviously just at
the beginnings of it and I appreciate that you know the current limitations of
the technology. But still, that's impressive.

Also curious if you are using satellite imagery in any contextual way or to
train your image recognition in any way? Or if you are using the lIDAR already
available at all? I imagine you are collecting higher-resolution LIDAR when
you fly over?

Anyway, good luck with this, sounds like you guys are doing it right.

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troyastorino
Awesome stuff! Why are you guys focusing on produce as opposed to say corn,
which has so much more acreage in the US?

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RaptorMaps
Produce costs farmers much more money to grow on a per-acre basis, since they
need so much more TLC. With produce, quality is everything to the farmers, and
there are many more opportunities during the growing season to make changes
that will improve the end result. We've all put bruised produce back on the
shelf at the grocery store, and for every one of those pieces, there are
several the didn't make the cut!

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kitepython
parrot.com has already thought of this

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kitepython
parrot is already doing this but only sell a camera and color sensor. they
sell drones too. parrot is the original person to think of this. here's the
link to their website ---> parrot.com

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eobropta
We actually don't sell drones. We use drones along with custom tractor-mounted
sensors and our software. With this combination we directly correlate field
performance at specific growth stages to yield. We're allowing produce growers
to perform controlled experiments on their fields to know exactly where the
good crop comes from and why. Sensors by Parrot are awesome and can be
integrated into this work flow.

