The View from Up Here is Great

University of Nebraska – Lincoln Author

08/31/2020 Added

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Drones & Remote Scouting in Pest Management – Dr. Ian MacRae The use of drones to pinpoint areas of the field that need on the ground scouting.
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[00:00:08.690]Hello, my name is Ian MacRae.
[00:00:10.610]I'm an entomologist with the department of entomology
[00:00:12.800]at the university of Minnesota.
[00:00:14.570]I am stationed at a research and outreach center,
[00:00:16.370]way up in the northwest part of the state
[00:00:18.460]and I'd like to thank you very much for inviting me here
[00:00:20.280]to talk to you today.
[00:00:21.800]I'm going to discuss some of the work,
[00:00:24.020]kind of in generalities and also some
[00:00:25.510]of the work we've done using drones
[00:00:27.730]and remote sensing to do some remote scouting for pests,
[00:00:31.640]both insects and disease.
[00:00:35.490]To understand what we're doing when we use remote sensing
[00:00:38.190]to evaluate plants, you kind of have
[00:00:40.020]to understand how plants use the electromagnetic energy
[00:00:44.230]that's coming down from the sun and what they do with it.
[00:00:47.950]Now, as you remember from school,
[00:00:49.470]if you take a prism, you can take white light
[00:00:52.600]and break it into the individual wavelengths
[00:00:54.600]of red all the way down to violet
[00:00:56.390]and each one of those represents a wavelength
[00:00:59.070]of how long the photons
[00:01:01.880]in that particular color are traveling in that wavelength.
[00:01:04.930]Well, plants use different wavelengths in different ways.
[00:01:08.530]For example, they reflect all of the photons
[00:01:12.020]that are in the green wavelength.
[00:01:13.960]We know that because plants are green
[00:01:15.740]and that's what you're seeing.
[00:01:16.600]You're seeing the reflected green light.
[00:01:18.450]However, photons that are in the red wavelengths
[00:01:21.400]and in the blue wavelengths, plants will absorb those
[00:01:24.300]because those photons actually power photosynthesis.
[00:01:28.200]There are other wavelengths that we can't see,
[00:01:29.850]they're slightly longer than red
[00:01:31.810]and those are in the infrared and what we see
[00:01:35.010]with infrared light is plants have evolved the ability
[00:01:38.930]to reflect infrared light
[00:01:41.000]and it's the cells in the mesophyll area of the leaf
[00:01:43.660]that are responsible for that.
[00:01:45.380]Now, the reason they reflect infrared light is
[00:01:47.280]because the photons that are
[00:01:48.840]in infrared light don't have enough energy
[00:01:50.480]to run photosynthesis,
[00:01:51.510]they wouldn't be that useful to the plant
[00:01:53.250]and therefore they wouldn't be used.
[00:01:54.490]They'd have to turn into a different kind of energy
[00:01:56.380]like heat and that wouldn't be healthy for the plant.
[00:01:58.830]So plants have evolved to reflect infrared light.
[00:02:03.000]When you measure the infrared light,
[00:02:06.140]you can see different things at different wavelengths
[00:02:08.390]in there as well.
[00:02:10.320]For example, when you stress a plant,
[00:02:13.000]one of the first things that happens is that the precursors
[00:02:16.110]to photosynthesis start to break down
[00:02:18.350]and this means that you start to get changes
[00:02:21.200]and disruptions in those cells that are in the mesophyll
[00:02:25.680]and there are other structural changes that happen as well
[00:02:28.587]and what happens is a stressed plant
[00:02:30.610]actually loses the ability
[00:02:32.270]or has it impaired that ability
[00:02:34.200]to reflect infrared light, that becomes impaired.
[00:02:37.550]So if you measure the amount of infrared light
[00:02:40.170]that's coming from a healthy plant,
[00:02:41.440]compare it to that that's coming from a stressed plant,
[00:02:44.460]you'll see the stressed plant is reflecting
[00:02:46.140]a lot less infrared light
[00:02:48.990]and if you look at the different wavelengths
[00:02:50.330]within the infrared light, you can actually get an idea
[00:02:53.360]of what is causing the stress.
[00:02:55.010]For example, drought stress
[00:02:56.110]or water content differences are going to be seen
[00:02:59.300]in what's called the shortwave infrared light
[00:03:01.540]and that's a little bit longer than near infrared,
[00:03:03.850]which is just above the visible red.
[00:03:06.370]In the near infrared, that area between just above
[00:03:10.715]that red that we can see,
[00:03:12.090]that's where you're going to start seeing impacts
[00:03:14.730]from plant disease and from insects.
[00:03:18.800]So which we've got a tool where when we look at these,
[00:03:22.160]we do have sensors that can take pictures of plants
[00:03:25.270]and look at the infrared light, they can see it
[00:03:27.230]even though we can't, the sensor can
[00:03:29.550]and by comparing the ratios
[00:03:31.450]of what light wavelengths are being reflected,
[00:03:34.080]we can actually start to have a little bit of an idea
[00:03:36.800]of what stress these plants are actually under
[00:03:39.710]and that's actually the basis of a lot
[00:03:42.540]of our research right now.
[00:03:46.810]The reason we use drones in remote scouting
[00:03:50.940]in agriculture is because,
[00:03:53.480]well, it's a happenstance, a very convenient happenstance
[00:03:56.610]between the development of simultaneous development
[00:03:59.110]of two different technologies.
[00:04:02.050]We started to see the development
[00:04:03.620]of very small unmanned aerial systems or drones.
[00:04:07.430]Their control software got a lot better, got a lot simpler.
[00:04:12.020]They got smaller.
[00:04:13.280]They had greater lift and take greater payloads.
[00:04:17.750]They became simpler to operate.
[00:04:19.470]They started to be able to fly for longer periods
[00:04:22.470]of time on battery.
[00:04:23.710]Basically what you saw was a tremendous development
[00:04:27.330]in drones and over the last 15 years
[00:04:29.410]and it's one of the reasons why they've kind
[00:04:30.840]of flooded the consumer market right now
[00:04:35.560]and simultaneously we saw advances in the technology
[00:04:40.620]and the resolution of the sensors themselves
[00:04:42.930]that we use in remote sensing.
[00:04:44.380]We saw them get smaller.
[00:04:45.820]We saw their power usage get smarter.
[00:04:48.580]We saw their resolution increase, they got better
[00:04:51.600]and so we ended up with very small sensors
[00:04:54.200]that could be supported by these drones
[00:04:57.340]and the result is we now have airborne platforms
[00:05:00.280]or airborne tripods, if you want
[00:05:02.710]for these high resolution sensors
[00:05:04.570]that can get us some very good information
[00:05:06.860]and help us in our decision making in agriculture.
[00:05:12.100]Now, there are a wide variety of drones available right now.
[00:05:15.520]In our research we use multi-rotor systems,
[00:05:17.900]these little quadcopters, sometimes larger copters
[00:05:21.490]with more rotors up to eight
[00:05:23.540]and so there's a wide variety out there though
[00:05:25.740]but if you're looking at just remote sensing,
[00:05:27.960]you don't have to lift a lot of weight.
[00:05:30.030]The sensors are actually quite small.
[00:05:32.030]So usually we can get away
[00:05:33.910]with using these smaller, less expensive drones
[00:05:37.090]but there's a lot of different options out there for you
[00:05:39.570]to utilize, a lot of these flying tripods
[00:05:43.830]that can get the sensors into areas immediately in a way
[00:05:47.350]that we haven't been able to do so far.
[00:05:50.204](mumbles) there are a number of different kinds of sensors
[00:05:52.650]that are out there for pest sensing or for pest scouting.
[00:05:56.480]Mostly what we're interested in are imaging sensors
[00:05:58.610]and there's a couple of different kinds
[00:05:59.820]that are in common use.
[00:06:00.800]There are a number of sensors out there
[00:06:03.100]but the two types that are
[00:06:05.000]in very real common use are multi-sensor arrays,
[00:06:08.520]which are kind of the images that are on the left-hand side
[00:06:12.310]of the screen and they all look like they've got a bunch
[00:06:13.960]of different lenses and thermal cameras,
[00:06:16.430]which is that camera that's on the right hand side
[00:06:18.640]of the screen.
[00:06:20.030]Multi-sensor arrays usually have one camera
[00:06:22.890]that's in the visible range or the VIS range
[00:06:25.740]and that's just the standard digital camera,
[00:06:28.030]much like what would be on your cell phone?
[00:06:30.270]The other lenses that are on there,
[00:06:32.140]whether it's three or six or however many,
[00:06:35.010]they're usually for specific ranges in the near infrared
[00:06:39.910]and oftentimes those different ranges are indicative
[00:06:43.380]of a different kind of stress and so these are sensors,
[00:06:47.620]many of them are sensors that are specifically designed
[00:06:50.330]to pick up one specific or identify one specific kind
[00:06:53.660]of stressor.
[00:06:55.020]Thermal cameras on the other hand,
[00:06:56.330]they're getting very small indeed.
[00:06:57.610]Some of them are getting smaller than the size
[00:06:59.280]of a computer mouse
[00:07:00.730]and they take an image where the color that's
[00:07:05.370]on the resulting image actually represents the temperature
[00:07:09.620]of the object in the image
[00:07:12.170]and so we can use a thermal camera to take a picture
[00:07:14.420]of a crop canopy
[00:07:17.010]and these are rather useful for plant disease
[00:07:20.160]because plant diseases usually have a greater impact
[00:07:24.110]on the stomatal ability of a plant than do insect damages
[00:07:29.010]and so oftentimes a plant that is been infected
[00:07:32.710]with a disease will have a higher temperature
[00:07:34.990]than healthy plants around it
[00:07:37.150]and so it's a way to kind of look at what the,
[00:07:40.910]if you use both of these sensors together,
[00:07:42.670]you can sometimes differentiate
[00:07:44.180]between different kinds of stressors.
[00:07:49.090]When you fly over a field,
[00:07:54.178]you're not going to be using this type of long video
[00:07:56.970]but as you're flying,
[00:07:58.270]these sensors are taking individual pictures as they go,
[00:08:01.790]which means you're gonna end up with a whole lot
[00:08:03.600]of pictures or even a small amount of land
[00:08:07.950]and you're going to have to put them together
[00:08:09.510]into one large picture so that you can actually use,
[00:08:12.850]do some analysis on that image
[00:08:14.870]and there's a software out there
[00:08:16.250]that will do this called stitching software.
[00:08:18.360]There's a number of different software that'll do it
[00:08:21.750]and it basically looks for common points in the imagery
[00:08:24.630]and joins them all together like a big jigsaw puzzle.
[00:08:27.670]For example, this is one of our research fields,
[00:08:30.780]it's a field of potato plots.
[00:08:32.350]It's about one and a half acres large
[00:08:34.520]and this is not one single image although it looks like it.
[00:08:38.670]It's actually a combination of stitched image
[00:08:42.340]of 128 separate photographs
[00:08:45.760]and it's a good example of this because up
[00:08:47.560]in the upper right corner you can see two yellow dots.
[00:08:50.870]That's actually the same person.
[00:08:53.810]It's a young lady who is taking data from those plots.
[00:08:56.270]We caught her as the drone was going up the field
[00:09:00.880]and then before it turned around and came back down,
[00:09:02.700]because it flies this pattern of the field back and forth
[00:09:05.460]to take all of these imagery.
[00:09:06.840]So we caught her once and then she moved on to the next one,
[00:09:09.010]we caught her in the next section.
[00:09:10.960]Those little white dots that are down in the center right,
[00:09:13.310]you can see there's a kind of two little short ones
[00:09:15.270]and then this long rectangle,
[00:09:16.840]that's actually one piece of, I think it's a plastic bag
[00:09:20.930]if I recall
[00:09:21.950]and it's being blown over the canopy by a gentle wind
[00:09:25.440]that we were having that day
[00:09:27.090]and so it's actually caught at about three or four
[00:09:30.210]or five different images
[00:09:31.330]and that's why that long one looks there.
[00:09:33.470]It looks like it's all long.
[00:09:34.480]It looks like it's one object.
[00:09:35.820]It's not, it's the same object caught multiple times
[00:09:38.740]and this underscores the need
[00:09:41.240]for having some personal knowledge of the field
[00:09:46.323]that you're dealing with,
[00:09:47.340]that you're trying to analyze, some history of it,
[00:09:49.700]without that, the imagery is not going to be as valuable.
[00:09:53.420]So it's a really good idea
[00:09:55.110]to have someone who knows the field take part
[00:09:57.880]in the analysis of it.
[00:10:00.930]Well, what can you use this with?
[00:10:02.060]Well, we've got a number of projects
[00:10:04.160]that we have used remote sensing with.
[00:10:06.700]One of our big ones was with a soybean aphid
[00:10:10.700]and in fact, we've received some very good results with that
[00:10:15.110]but the one I wanted to show you just as an example,
[00:10:17.410]because it has nice big photographs here
[00:10:19.450]is sugarbeet root maggot
[00:10:21.050]and I thought this would be a good example
[00:10:22.450]because root maggot and sugarbeets is a pest on the root.
[00:10:27.436]There is no visible damage on the leaves
[00:10:29.750]until the damage is quite a long way into the season
[00:10:33.390]and then you might get some wilting.
[00:10:35.050]To actually scout for root maggots, you actually have
[00:10:37.360]to destructively pull out the plant out of the ground
[00:10:40.960]and look for a root maggot.
[00:10:42.430]So we were looking for a way where we could estimate
[00:10:44.760]what root maggot damage was happening in a field
[00:10:47.140]or see some indication of it.
[00:10:49.020]So we were looking with near infrared photography.
[00:10:51.740]We were taking pictures of the canopy
[00:10:53.610]and we have two really good examples here.
[00:10:56.060]The top image, these are again, these are near IR.
[00:10:58.960]These are infrared images,
[00:11:00.720]the redder and the brighter the picture,
[00:11:02.410]the more infrared is being reflected.
[00:11:04.840]The top image is a plant that basically
[00:11:07.060]has very low sugarbeet root maggot populations on its root.
[00:11:10.150]We pulled them up after taking the images and counted
[00:11:12.700]and you can see a lot of infrared being reflected there.
[00:11:16.940]The image on the bottom is a plant
[00:11:18.820]that actually had very high root maggot populations.
[00:11:21.250]It was pretty heavily stressed and correspondingly
[00:11:24.150]it is not reflecting a lot of infrared light.
[00:11:28.060]The ability to reflect infrared light has been impaired
[00:11:31.560]and so if you have these stressed plants in a field,
[00:11:34.490]they become very visible amongst,
[00:11:37.560]especially if they're surrounded by healthy plants.
[00:11:40.390]So this is now aiding us in our scouting.
[00:11:44.060]You can use it in diseases as well.
[00:11:45.900]These are a wheat research plots again here in Crookston
[00:11:51.550]at our research and outreach center.
[00:11:53.930]and they represent the,
[00:11:55.640]these are plots that have been in infected
[00:11:58.160]with a particular disease.
[00:12:04.744]This is a thermal image
[00:12:05.900]so what we're actually looking at is the temperature
[00:12:07.940]that's being reflected in the canopy.
[00:12:09.680]A visible version of this field would
[00:12:11.400]just be solid green all the way across
[00:12:13.330]and you can see those little yellow hotspots in the middle,
[00:12:16.080]those are actually plants that have been infected
[00:12:18.930]with the disease about four to seven days prior
[00:12:22.210]to this image being taken.
[00:12:23.570]You can see other plots that have been in this image,
[00:12:25.870]kind of at the edges that have had the disease
[00:12:27.990]and it's well along
[00:12:29.770]but what this demonstrates is we can start to see some
[00:12:33.440]of the responses of the plant
[00:12:34.930]to being infected fairly early.
[00:12:37.030]So again, this is a potential scouting tool
[00:12:40.360]for plant disease as well.
[00:12:44.850]That's not to say that you need near infrared
[00:12:47.640]or thermal cameras to get good data
[00:12:50.940]and indeed visible data can provide you
[00:12:52.820]with a lot of information.
[00:12:54.580]Flying a digital camera over a field is a great way
[00:12:57.840]to look at your stand counts
[00:12:59.090]and look at your stand establishment.
[00:13:01.360]It will show you where you've had plantar skips,
[00:13:03.470]it'll show you where you may have nutrient problems,
[00:13:05.620]where there may be poor soil and poor establishment
[00:13:08.789]of your plants.
[00:13:11.540]Hail damage, planter skips, like I'd said, any defoliation,
[00:13:15.700]all of this would show up in visible imagery
[00:13:19.820]and in fact, anything you can see from the ground,
[00:13:22.070]you'll get a better view of,
[00:13:23.250]you'll get literally a bird's eye view.
[00:13:26.130]You'll get a larger picture of the field.
[00:13:27.940]You'll have a better idea of what's going on.
[00:13:30.280]For example, up here in Northwest Minnesota,
[00:13:33.714]all of our river systems run north
[00:13:35.860]and this means we have a problem in the spring because all
[00:13:38.690]of our surface drainage is going into streams
[00:13:42.590]that are emptying into rivers
[00:13:44.150]that are flowing into areas that are still frozen.
[00:13:46.530]So we get a backup of water
[00:13:48.660]and a lot of the growers
[00:13:50.320]in the area here have taken to using drones
[00:13:53.440]to flying their fields in the spring
[00:13:55.660]to see where they should put additional field drainage,
[00:13:59.700]where they should increase their ditching
[00:14:02.080]and so it's been quite useful to them for that.
[00:14:05.880]Perhaps one of the best uses for using just visible data
[00:14:09.650]would be looking at spray drift for herbicide injury.
[00:14:12.670]This image comes from a paper where the authors
[00:14:15.180]actually inflicted the damage themselves,
[00:14:19.430]they did an application down in the lower right hand corner
[00:14:22.460]and you can see the plume of herbicide on a very windy day
[00:14:25.530]as it streaks up across that field
[00:14:27.800]and it gives an excellent example of herbicide drift
[00:14:31.400]and so again, this would be an excellent use
[00:14:34.050]for this technology.
[00:14:37.350]Well, are we seeing this technology replace any
[00:14:40.558]of the others? No, not really.
[00:14:42.380]Satellites remain the least expensive way
[00:14:44.950]to get your kind of remote sensing data
[00:14:50.130]and the reason for that is their footprint is huge.
[00:14:52.700]So the amount of ground they cover,
[00:14:54.440]your cost per square foot is much lower
[00:14:56.350]with satellite (indistinct) or satellite imagery
[00:14:59.070]but the problem with satellite imagery
[00:15:00.790]is the resolution is quite high.
[00:15:02.950]The smallest thing you can see is probably
[00:15:04.680]about three meters and also they're stuck on a schedule,
[00:15:08.540]an orbital schedule.
[00:15:09.910]So if a satellite flies over right now and it's cloudy out,
[00:15:14.870]it's not going to get a lot of data
[00:15:17.190]and if that cloud clears in 30 minutes,
[00:15:19.510]you can't call back the satellite company or NASA
[00:15:21.880]and say, can you send that bird back cause it's clear now,
[00:15:24.640]no you can't
[00:15:25.550]but you could break out a drone and fly it immediately.
[00:15:28.470]So drones offer an immediacy of data that you don't have
[00:15:31.920]with some of the other methods.
[00:15:33.440]It also gives you a higher resolution than some
[00:15:35.360]of the other methods but it doesn't replace them.
[00:15:38.100]The way to look at drone imagery is that it's an addition.
[00:15:41.770]It's an addition to walking your fields,
[00:15:43.530]it's an addition to satellite data,
[00:15:45.400]it just provides you with more data that you can use
[00:15:48.020]to generate good information to make decisions.
[00:15:51.990]Well, why aren't everybody using these things?
[00:15:53.490]Why don't we have drones everywhere.
[00:15:54.870]We may someday but right now there are some barriers
[00:15:57.720]to adoption.
[00:15:58.553]There are regulatory issues.
[00:16:01.020]You still have to get a certification from the FAA
[00:16:03.690]to use these commercially.
[00:16:05.200]The return on investment
[00:16:07.087]might not be quite where people want to get it yet.
[00:16:09.310]There's an apparent complexity of technology,
[00:16:11.300]although that's getting much simpler
[00:16:13.400]and there's also these different adoption models.
[00:16:15.890]Most of the stakeholders I talk to are very interested
[00:16:18.810]in the data but they don't wanna be the one to acquire it
[00:16:21.650]or analyze it.
[00:16:22.870]So we may be looking at the adoption of service models,
[00:16:26.420]where it's contracted out as a job
[00:16:28.040]and that's gonna take a little while to maybe sort out
[00:16:30.640]and come up with the best uses.
[00:16:34.670]What's the future?
[00:16:35.560]If you could imagine the future for these things,
[00:16:38.810]probably somebody is working on it.
[00:16:40.610]We're seeing machine learning,
[00:16:41.700]which is a very in depth analysis
[00:16:44.670]of the data, large data sets
[00:16:46.250]so we can better identify what wavelengths are associated
[00:16:48.680]with what kind of stress.
[00:16:50.470]We're seeing swarm technology being developed.
[00:16:52.530]That's where you have multiple drones out.
[00:16:54.350]They all know where each other is and they fly set patterns,
[00:16:57.080]you cover more ground in less time.
[00:16:59.020]You also have machine language where drones are
[00:17:00.870]actually sending information to machines on the ground.
[00:17:04.400]So they may be sending information about what they're seeing
[00:17:06.880]to driverless tractors or to these individual robots
[00:17:11.617]that deliver inputs to individual plants.
[00:17:14.720]So there's a lot of future for this technology
[00:17:17.320]and I'm sure we're gonna see greater
[00:17:19.010]and greater adoption of it.
[00:17:20.750]My last piece of advice would be
[00:17:22.300]if you do want to get into this,
[00:17:24.570]I would advise you to invest heavily in spare parts
[00:17:27.060]because what goes up will come down
[00:17:30.050]and in fact, this particular one had a bad battery
[00:17:32.860]and the battery caught fire in midair and it came down
[00:17:35.680]and like I say, a very spectacular fiery manner.
[00:17:39.120]If you have questions,
[00:17:40.310]I will be available in the question period
[00:17:42.590]and I thank you for your attention.
[00:17:46.050]Questions I will be available in the question period
[00:17:48.680]and I thank you for your attention.

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