249: Making it Easier to Use Satellite Data in Agriculture

Sustainable Winegrowing with Vineyard Team

NASA has connected data about the Earth’s surface since 1972. One of the first applications was for agriculture. Alyssa Whitcraft, Executive Director of NASA Acres grew up in the wine industry at her family’s property, Whitcraft Winery, located in Santa Barbara California.

Her goal is to make it easier for people and organizations to use satellite data to improve agriculture. Alyssa explains how different types of satellites including polar-orbiting and geostationary collect information that can be calibrated against crop-specific data to develop predictive models. Farmers can use these models to identify viral, fungal, bacterial, water, and nutrient stressors and forecast harvest.

While this technology is being used in commodity crops today, there is a huge opportunity for specialty crops.

Resources:

• 129: The Efficient Vineyard Project
• 199: NASA Satellites Detect Grapevine Diseases from Space
• 233: The Gap Between Space and Farm: Ground Truthing Satellite Data Models
• Alyssa Whitcraft
• Group on Earth Observations Global Agricultural Monitoring Initiative (GEOGLAM)
• NASA Acres
• NASA Harvest
• Whitcraft Winery

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• SIP Certified – Show your care for the people and planet
• Sustainable Ag Expo – The premiere winegrowing event of the year
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Transcript

[00:00:00]

[00:00:04] Beth Vukmanic: NASA has collected data about the earth surface since 1972, One of the first applications was for agriculture. Welcome to sustainable wine growing with the vineyard team, where we bring you the latest in science and research for the wine industry. I'm Beth. Vukmanic executive director. Since 1994 vineyard team has brought you the latest science-based practices, experts, growers, and wine industry tools through both in-field and online education, so that you can grow your business. Please raise a glass with us as we cheers to 30 years.

[00:00:39] And today's podcast Craig Macmillan, critical resource manager at Niner wine estates with long time sip certified vineyard and the first ever sip certified winery. Speaks with Alyssa Woodcraft, executive director of NASA acres. She grew up in the wine industry at her family's property. Whitcraft winery located in Santa Barbara, California.

[00:01:01] Alyssa's goal is to make it easier for people and organizations to use satellite data, to improve ag. Alissa explains how different types of satellites, including polar orbiting and geostationary collect information that can be calibrated against crop specific data to develop predictive models. Farmers can then use these models to identify viral, fungal bacteria, water, and nutrients stressors. And forecast harvest. While, this technology is being used in commodity crops today. There was huge opportunity for specialty crops.

[00:01:35] Alyssa is involved in numerous organizations and projects. So I highly recommend that you visit our show notes. And check out her website.

[00:01:43] If you want access to more viticulture research and technology from the world's top experts, then you won't want to miss the premier Winegrowing event of the year. The sustainable ag expo enjoy the perfect blend of in-person and online learning. Speak directly with national experts. Earn over 20 hours of continuing education and explore sustainable ag vendors. It all takes place November 11th through 13th, 2024 in San Luis Obispo, California. As a listener to this podcast. Make sure you use discount code podcast 24 at checkout to take $50 off of your ticket. Register

[00:02:19] today at sustainableagexpo.org. Now let's listen

[00:02:27] Craig Macmillan: Welcome to Sustainable Wine Growing with Vineyard Team. Our guest today is Alyssa Whitcraft. She is Executive Director of NASA Acres, and we're going to talk about all kinds of exciting stuff that she's involved with, and I'll let her explain those. Thanks for being on the podcast, Alyssa.

[00:02:43] Alyssa Whitcraft: Thank you for inviting me.

[00:02:45] Craig Macmillan: You're involved in a whole bunch of different projects and consortiums and programs mostly around remote sensing and agriculture.

[00:02:53] And you're excited about a number of different things in your field. What exactly is your field? I think it's a good place to start because I think a lot of people don't understand what it is.

[00:03:01] Alyssa Whitcraft: I'm a geographer, which is basically the world's oldest discipline. We use the lens of space and place and location to understand the world. And knowing that things that are near to one another tend to have more in common than things that are far from one another. And similarly, we know that where you are in the world matters for all sorts of different things. And that's really the lens through which I see and understand the world. Specifically within geography, because geography is a very broad discipline, my expertise is in using satellite data and other Earth observations to understand what's happening across the world in principally agriculture. I've done work in the past in forestry as well.

[00:03:47] Craig Macmillan: What kinds of things does this field have coming in the future? What are the things that you're most excited about in terms of all the different work that you're doing?

[00:03:55] Alyssa Whitcraft: Would it be helpful if I gave a little bit of history, or is that too much info?

[00:03:59] Craig Macmillan: . Please, please.

[00:04:01] Alyssa Whitcraft: Sure. So a lot of people don't realize that satellite data has been collected of the Earth's surface since 1972. NASA launched its first satellite back then, and one of its first applications was agriculture. It was really for looking at global forecasting, production forecasting, and things like that in areas where We couldn't gather statistics like the USSR, for example. And so that was very early.

[00:04:29] They thought, hey, we really need to understand what's happening with the global food production, global food supply. What kind of prices are we going to be able to get? Those were the very earliest experiments. And a lot of years have passed since then. It's 52 years now. That particular satellite was called Landsat. Well, it's called ERTS 1. It's been, renamed Landsat 1 in hindsight and they've just launched Landsat 9 two years ago. So we've really, we have a lot of series of it now with continuity of data for 52 years from that satellite, that mission alone. there's a huge plethora of other types of data though that are also collected. Landsat, for example, its characteristics are, it passes over the same place every 16 days at about 30 meter resolution. So 100 feet by 100 feet, about a football field, and then there's other satellites that pass over every day and they might have much coarser spatial resolution. So 250 meters by 250 meters, for example. And then there's also recently, because storage is cheap and the Internet is fast, there's a proliferation of these very fine spatial resolution satellites where you can tell almost down to the plant level.

[00:05:38] Definitely tree level, what you're looking at, that's quite fine in resolution and still have some degree of rich spectral information. And what I mean when I say that is basically everything around us is reflecting light all the time or emitting light. And we only see a little tiny piece of it, the visible spectrum.

[00:06:00] That's why it's called the visible. But there's so much richness, on both sides of the visible spectrum. So longer wavelengths and shorter wavelengths, and they tell us all kinds of things about what's going on with a surface. we see vegetation as green because that's what it's reflecting. But there's other things in near infrared that can tell us about vegetation health. Or sort of mid range infrared that can tell us about water stress, things like this. And so now we have more and more spectral information, more and more frequently and finer and finer spatial resolution.

[00:06:35] So our ability to see a great deal of detail has come a really long way. And still just like kind of any instrument you use, your ability to do something useful with it is contingent upon its quality and also the quality of the kind of science that you use to interpret the data and turn it into information.

[00:06:58] Craig Macmillan: What kinds of information is this data being turned into? And on what kinds of or agrosystems?

[00:07:06] Alyssa Whitcraft: All over the world. There's two broad classes of satellites. One is called polar orbiting. So it's going around the poles and it returns to look at the same spot every, you know, it's governed by its orbit and a couple of other things. I said Landsat was 16 days, for example and others can be much more frequently or even longer. So that's one kind, polar orbiting. The other type is geostationary, which means that as the earth turns, it's always looking at the same spot. And that's what most of the sort of weather satellites are. So that's why you can get really like frequently every 15 minutes, like a radar image, for example. all that's to say, like a lot of the satellites we use are polar orbiting, and that means it's not biased toward only collecting data over the United States.

[00:07:48] It's collecting data all over the world. In the past, because. storage was expensive. There wasn't very much storage capacity on the spacecrafts. You couldn't store it all. They used to have to select which images they were going to capture. So it might be passing over a surface, but it wouldn't turn the camera on. And only about, I want to say 2012, 2013 was when Landsat started acquiring almost every single opportunity. And not just capturing something like A third of the daylit scenes that could capture every day. so all that's to say, we now have like so much rich coverage the last 12 or so years with that kind of satellite. So that means like we're getting observations of the earth's surface where everywhere agriculture is grown at least every day, depending on the type of satellite you're talking about. And even for the finer resolution ones, you're getting it every day. 10 days, maybe once you are to 20 days once you account for cloud cover in a lot of areas.

[00:08:44] Craig Macmillan: what kinds of decisions can people make regarding how they farm based on this kind of information? And my understanding is that this is public information, is that correct?

[00:08:53] Alyssa Whitcraft: What I talked about was sort of where you can collect information. It's all over. It's not you know, biased toward any particular region per se. By virtue of that, it's not necessarily biased toward any one crop because it's collecting all those data. So those observations exist, but our ability to turn them into information is contingent upon how much we've studied that, that item. And, and how much what it, the light that it reflects in the satellite picks up on is related to whatever it is that we're trying to study. So that's to say if a satellite only collects visible information, then we're not going to be able to talk about sort of some of the items associated with chlorophyll content and like health of the plant. Or if it doesn't collect the long infrared or mid infrared you're going to miss out on information about water, things like that.

[00:09:41] And that's just kind of a simplified answer to that piece. And so we're able to collect all kinds of variables. In my work, we've called them essential agriculture variables. they're basically core building blocks, variables that we can measure and infer about the earth based on satellite data about the state, what the change has been over time and what the forecast is to the future.

[00:10:02] We can look at, Hey, what kind of crop is being cultivated here right now? We can see how has that changed over the last 10 years? We can look at, okay, this is the current condition. What's the forecast for harvest this year? different things like that. We can also do within season detection of certain stressors, biotic and abiotic stress.

[00:10:22] So you know, can be viral, fungal, bacterial diseases water stress that can help with precision kind of irrigation scheduling. We can also look at you know, when you couple that with like short term weather forecasts, you can see, okay, there's going to be really high demand evaporative demand. And so we need to think about maybe irrigating or doing something in advance to prep the vegetation for that. You can also use it for nutrient applications. So, this is primarily in row crops so not really vineyards per se. But, we can take a look at what the current nutrient status is. Nitrogen, if it's nitrogen deficient, then you are only applying what it needs and not too much. Same goes with pesticides. You're not just doing blanket spraying. You can do early detection and mitigation. With nitrogen, you only apply how much is needed and where it's needed, which has important environmental benefits. It also helps the farmers sort of bottom line, not wasting money. And also in terms of a fertile excess fertilizer being applied and also not leaving money on the farm by not applying enough. It can be really helpful in kind of zeroing in on what intervention needs to be done and what you can prepare for at the end of the season.

[00:11:32] Craig Macmillan: I'm just thinking through this, so you would have to have some crop specific, and maybe even region specific on the ground work in order to make the connection, the correlation between, I'm getting this reading, and then this is what's going on with the plants.

[00:11:47] Alyssa Whitcraft: Yes. Yep. That's completely accurate. And I'm really glad you said it because there is a perspective on satellite data that it's magic, that you just take the image and you have the information. And that's just like not really how it works. Now we're getting more and more sophisticated models out there, but all models have to be trained on something. And just because I've trained it on a ton of corn in Iowa doesn't mean it's going to work on corn in Argentina. Like that's just not necessarily how these things work. some people call it ground truth. I prefer to call it training data, validation data. you know, in situ site data, things like that, comparison data. And the reason for that nuance is just to say that there is error in all measurement. So just because if your scale is calibrated wrong and you say, this is, this was my harvest, this was my yield, then that's not necessarily ground truthed see what I mean? So, and I think that that's an important point to make because we're trying to add an additional piece of measurement to the picture, right?

[00:12:48] It can give you more frequent. more coverage deeper spectral information. It can a lot, but it's a piece, it's a component of a multi source decision support system. We say like garbage in garbage out on the remote sensing side of things. Our observations are very good, but you know, we're talking about hundreds of millions of dollars of engineering in the sensors and the satellites to go up into space. So those are incredibly high quality and the space agencies who fly them they do a lot of expensive CalVal, it's called, so they go and they make sure that the instruments like, you know, The analogy in your kitchen would be you stick your thermometer in boiling water to make sure 212 Fahrenheit or 100 degrees Celsius is exactly what your thermometer is picking up, right? So we do the same thing with satellites. that's great for the reflectance or for the wavelengths, but that's not information. So then what we go out, we might take some tissue samples. To understand what's happening with nutrients with pest and disease stuff, some soil samples for that purpose. Or for some of the more like workhorse, what we've been doing with satellite data for a lot longer, those are more novel applications. The lot much longer is what's growing where where it is. What's the season. Like why is it. Kind of just at the early part, is it flowering, reproductive, is it toward harvest and then also yield.

[00:14:09] And so we go out, we take crop cuts, we do things like that, then we calibrate our observations or our models against those data, and then we can run a predictive model that can tell us for the same site in another year, or more commonly you take it from that site and then generalize it. to where you have satellite data that are continuous, like so you have a whole an image, but you don't have any training data from this vineyard over here. So you take the training data from this vineyard and see if you can use it to identify what's happening in other vineyards. And then you assess, how well did I do off of another set of data that's from the ground.

[00:14:46] Craig Macmillan: And so I would imagine that that kind of work is done extensively in agronomic crops, or what we might call staple crops, you know, rice, maize, soy, things like that, wheat. But you can do this with specialty crops as well. You mentioned vineyards. If there is interest and if there is funding, we can do this kind of work and bring vineyards into this this, this kind of process, this kind of science.

[00:15:11] Alyssa Whitcraft: Yeah. I mean, you're spot on. Like I said earlier, the earliest applications of satellite data. Were in kind of global production forecasting with the reason being that wheat prices, for example, are incredibly correlated with conflict. So as wheat prices go up, you see more human conflict. And so these are the huge drivers of global trends in prices, in food security, all these kinds of things that are really important to track. And so the, you know, the early app applications were really for that type of crop and for very large scale forecasting in the sort of 80s, 90s was when you started to see some of the precision management. So on farm information but perhaps not as much as people hoped for in in this kind of satellite world, there was a lot of unsuccessful startups and, and things like that. I think the big reason for that is like, if you're going out and scouting your 10 acre vineyard, like you can generally walk it. It's not a big deal. You're not driving a combine through. My family's in the wine business and I grew up walking vineyards with my dad and taking tissue samples and taking fruit samples and doing things like, it was just a part of the day, you know, if you're farming 10, 000 acres, that's not viable.

[00:16:30] And so you're, you have, million dollar combine to these days and things like that. That's something with autonomous driving, you can program a great deal of information into it. sort of like historically, there just wasn't necessarily the, like. The demand for what satellite data could offer, you know, it was focused on kind of like yield and nutrients and water.

[00:16:49] There just wasn't the same use case in, in specialty crops. In a lot of ways, especially since some of them are growing greenhouses. So like, we're kind of out of luck with that. And so, yeah, whoops, but that things have just changed. We have better satellites now that collect more information more spectral information, higher spatial resolution, more frequently, we can process so much more data now, which means.

[00:17:14] we can kind of just keep throwing more and more data at a model until it picks up some signal that we never could have anticipated. That's kind of the basis of machine learning or artificial intelligence is that you just keep going like feeding it until you see if something comes out. That also has its own problems.

[00:17:31] Pretty funny fails AI. I think we've seen before the models get overtrained and it's very. clear that they don't work once they're over trained. They, they spit out like a baby with three hands AI image. And you're like, that's not, that's not right. Or I saw a matzah ball on a plate. It was like, rather than like a soup dumpling, it was like a tennis ball that was like matzah colored. I was like, that's not right either. You know, it's funny things like that. So the same thing can happen when we're looking at, you know, the earth's surface as well.

[00:18:00] Craig Macmillan: you are executive director of NASA Acres. That name has come up in a couple of other interviews. Could you explain, , what NASA Acres is and what you folks do?

[00:18:09] Alyssa Whitcraft: Yeah, sure thing.

[00:18:10] So NASA Acres is NASA's U. S. focused Applied Sciences

[00:18:15] So why, that's kind of a long title, NASA is principally a research agency. Now, it's not it's not USDA where it does farm services or loans or reports on statistics and agriculture. It's famous for people putting a man on the moon and missions to Mars, but NASA has this whole huge earth science division. within that, there's you know, the, the component that's dedicated to launching the satellites and making the data really high quality. And then there's an accessible data, high quality and data accessible. And then there's sort of like the core foundational research, which is. We've never used satellite data to measure this thing before, or we have used satellite data, but now we're just going to apply it elsewhere and do a study that results in a paper.

[00:18:56] So we learn a thing. That's research and analysis in NASA, and then there's applied sciences and earth action, which is, it's kind of new manifestation in NASA, which is like trying to take this data and really make an impact, really get the information, the data, the tools in the hands of people who are addressing, in our case, agricultural challenges.

[00:19:19] So that's farmers, that's ranchers. That's people in the ag value chain that's ag retailers, all the, I mean, there's a whole bunch of people in here who can benefit in some way from this data. And our job is to work with them to advance the science as much as possible because NASA's brand is really like quality, right?

[00:19:39] And then, but also neutrality. And so we kind of just try and lift. the floor, so to speak, make the quality as good as possible, advance the science, and then hope that the private sector that's out there that's serving people in agriculture can sustain the services or, and, and really be adding value to people in agriculture long, long after our projects end.

[00:20:00] Craig Macmillan: And so that, that's going to be where the next link is, is the private sector picking up this information, this data, and then figuring out how they can use it for their client base, maybe for a specific crop or a specific region, and then we can we'll see some development there. we've seen with like material science, I think is a classic example of that, you know the space program resulted in a lot of advances in materials that now we don't even think about. They're part of our everyday life,

[00:20:27] Alyssa Whitcraft: Yeah, like the blankets run a

[00:20:30] NASA, more than just Tang, you know, when I'm trying to like get across to people that, the planet we study most is Earth to quote Karen St. Germain, who's the Earth Science Division Director for NASA. I mean, material science is a really good example, but we have it so much in all these things that like, be them weather and climate services That's, you know, Noah's job principally to create the kind of forecasting models that are pushed out when we're talking about the United States.

[00:21:02] There's people all over the world doing it and then like weather channel or weather underground or whatever, build services on top of that. And then that's like what faces the consumer. So it's all kind of a part of an important chain. And in fact, NASA is in the background collaborating with Noah on this information as well. for us in the agriculture side of things NASA harvest, which still continues today as NASA's global agriculture applied sciences program. But from 2017, when it started until 2022, it was the whole kit and caboodle. So both us global international, the whole thing. And then they split the programs.

[00:21:39] So into Acres and Harvest. I was the deputy director and program manager for NASA Harvest from when it started until I took over the helm and founded NASA Acres in 2023. NASA Harvest, there's a great example of commercialization or of, of really strong collaboration with the private sector. Which is when the Ukraine war began there was obviously a huge hole in information all of a sudden about what on earth was going to happen with the food that comes out of Ukraine, which between Russia and Ukraine, it's 30 percent of the world's wheat, wheat's very correlated with conflict to begin with. And there's certain partners who are a hundred percent reliant upon imports from Ukraine and or Russia of wheat. , you don't just go drive down the street to the next grocery store and pick up your wheat. Like this is billions, trillions of dollars of movement that can't pivot overnight. So the potential implications were massive. And the more information you have earlier to plan for that, the better. And that's where satellite data came to bear. You couldn't send field agents out when there's an active war happening to be like, what was planted? Is it growing? Are farmers? Applying nutrients.

[00:22:50] Is it going to be harvested? Things like that. NASA Harvest partnered with a number of organizations, but one was a private space company called Planet who collects sub meter and three meter data. daily with they have many, many small satellites and so they're, these are not the three, 400 million satellites that NASA flies.

[00:23:08] These are much less expensive and they can fly way more of them. They're much smaller. They're a very different satellite. But they're great for getting high spatial resolution often. And when you can't go out and collect ground data. to do training on your images. Was this planted? Was this not planted?

[00:23:25] This appears to be this crop. This appears to be this crop. Satellite data of that kind are very helpful. And so then we would use that to train some of the other satellites that have perhaps richer spectral information or other qualities that we might look for in a certain analysis.

[00:23:40] And because we had this partnership with Planet, they were going out and collecting the data. We were able to do this analysis. talk about, you know, what we expected to see in terms of wheat harvest that year and sunflower and corn and rapeseed and all these really critical crops that Ukraine exports and help us prepare and mitigate any potential food security crisis and then Planet.

[00:24:03] On the flip side, they've suddenly made a huge impact with their data. And they've additionally been able to, you know, we do a lot of work on the. nitty gritty of the engineering of radiometric calibration and things like that. We also can support them in improving their imagery. And then now they have a use case in agriculture and all these different kind of things by partnering with us. But we've also advanced the models and the science and the knowledge that's all a public benefit. And so that's like a really lovely investment from the federal government that kind of has this big societal benefit, but then also supports the private sector and continued innovation and services.

[00:24:37] Craig Macmillan: in this case, it allows for the prediction of what may be available right?

[00:24:43] Alyssa Whitcraft: Yeah. In that example, for sure. The war broke out in February and the winter wheat harvest would have been, gosh, like may to June. You're looking to see how was the, was this coming back after winter? We're, what was the condition of the crop at a baseline? Were people able to apply nutrients of any kind? And once harvest time came. Were people able to go down in the field to harvest or did they not do it because they had been killed or evacuated or because there's unexploded ordinances in their field and things like this.

[00:25:13] And so that was really the beginning of the analysis and then it, it continued for other crops into the future. And it's a really rich ongoing project about which you can find copious resources online.

[00:25:26] Craig Macmillan: how are we doing on, on those areas? Are there people that are stepping up in the private sector to work on that.

[00:25:31] Alyssa Whitcraft: Definitely. Yeah, there are. The public sector, you know, my side of the house is too. but it's interesting. it's an interesting point because we focus so much on agronomic crops. We've done that because there's a really clear reason to invest public dollars. I think the very early stage collaboration with the private sector for specialty crops is much more critical than it was for these kind of big agronomic crops. So that means from the odd outset. the projects need to have very engaged partners from the private sector. It might be in the form of just working directly with the vineyard so that they can kind of maybe collect some of the ground data or if we're developing a tool, they can kind of like test it and provide feedback, things like that.

[00:26:14] But then there's going to be other circumstances where we might be trying to use a compendium of information. So you might be using some soil sensing to look at water status. But it's like, you can't place a million of them in your field. So, you know, you might take the benefit, the accuracy, the depth that you get from those expensive and ground instruments, and then try to pair them with the satellites and then build like kind of a hybrid measurement system.

[00:26:41] You get the benefit of the update frequency the satellites and the spatial coverage, of course. And then you get like the really good quality. measurements within the field. we've seen a lot of burgeoning partnerships in specialty crops and of course also agronomic commodity crops as well, but where we're trying to look at a hybrid network of in ground sensors or canopy sensors or drones. side canopy robots that my colleague Katie Gold, who was on your, podcast before, she uses these robots, Katie Gold and Yu Jiang, her collaborator at Cornell to, to sort of build toward the long term adoption of, of these, actually not even long term, to build toward the short and medium term adoption of these things, because that's real, it's really going to sustain them, NASA projects. typically three years acres and harvests are each in five year kind of increments harvest was renewed and For its global work and spit off its domestic work. And so hopefully we will be renewed as well But it's not the design of federal research to like provide every service forever We need to work with the people who need the information Because they're gonna tell us what to do and what like what matters to them You and then we need to work with the people who can kind of own the services long term and maintain those high touch relationships with their customers, growers, ag retailers, whomever it might be.

[00:28:04] Craig Macmillan: Spain, places like that Australia?

[00:28:06] Alyssa Whitcraft: You this is an area I'm definitely less comfortable talking about. within NASA Acres, we really only have Katie and you's project that's in specialty crops. And that's principally just by virtue of all the things I described. It's really only been the last four or five years that this stuff has started blossoming. And even within Katie's project. She's not using satellite data really, right now, she's done some demonstration stuff. We're preparing for a NASA instrument to launch in 2028. And we're doing years of preparatory work. NASA has an airborne fleet. People don't know that. And it's collecting very similar data to what will on this satellite SBG. Also, there's a sensor mounted on. The International Space Station called EMIT that also collects similar information. So we're already using that, but we're kind of like priming the pump for primetime, right? So Katie is very, Katie is like a very kind of ahead of the curve kind of situation person. The spectroscopy of the laboratory stuff, we all, we all know that it's been around for a long time, but the imaging capability to do it outside is novel. And so she and Yu are kind of working together on that. I don't have another project in my portfolio that does that right now. We are looking at using those data similarly, the hyperspectral is what it's called, data. We're starting to try and build use cases in rangeland monitoring as well for rotational grazing.

[00:29:33] So looking at forage quality, it's not just a matter of whether the biomass comes back, it's whether it's the right biomass, so the right mixture of different crops. If you've overgrazed an area, you'll just get like the one dominant. type of grass will come back, and that's not very nutrient dense, and it's not very sustainable, it's not very regenerative. If you don't overgraze an area, then things will grow back in a more balanced way, and that's something that we're trying to explore, how well satellites can pick up that heterogeneity in the landscape. That's an example there. I'm aware of some work in sort of olive groves in Spain, in Italy And I know there are some companies who have attempted to do kind of proxy measurements of shade coffee and cocoa. Very high value crops, but you can't see them because they're under the canopy of another tree. And there's been a lot of different experimental ways of trying to get at that. But in terms of my understanding of how successful those different cases have been. It's a little outside my wheelhouse. It's pretty novel. and yeah, I mean, I, the, the thing about being an applied sciences program, we're not the foundational research RNA. So what that means is like, we've got to kind of see the science demonstrated fairly firmly for it to move into a major part of the portfolio.

[00:30:53] That said, like there are some projects in my portfolio that are higher risk or that like, you know, that delivery might be a few years off because of the lack of instrumentation. And there are some stuff that's more experimental, but where those are the case like that Rangeland project or Katie's project That's because we have super engaged users already. So there's ranchers who are at the table for another purpose. Katie is, you know, an extension agent for Cornell working with grape and apple growers, and they want to know how to manage this.

[00:31:23] So she already has engaged parties. So having the satellite stuff be like maybe a little bit more nascent and its development cycle is okay versus, you know, where we don't necessarily have the strongest user. identified and partnered already, we're kind of relying on the more mature applications and starting to kind of transition that stuff out more quickly to broader audiences.

[00:31:45] Craig Macmillan: How can the wine grape industry or other crops, support this and encourage research in their particular area?

[00:31:54] Alyssa Whitcraft: There's legwork on both sides meaning that we need to be with the communities we live and work in. Thank you. to get those people involved in what we have to offer. So it's like there's a trust building component, there's an awareness building component and then there's also just the participate if somebody contacts you about being in a study or, you know, by word of mouth, Oh, this vineyard down the road is doing it.

[00:32:17] Like, maybe we'll do it here. I trust that person's discretion, so I'll do it here. Collaborating and being active in that research from the NASA acres perspective is, is really important. And more than just really from the NASA acres perspective, from really the kind of, you know, we're neutral, we're trying to build quality, we're trying to raise the floor.

[00:32:36] So even if you come, you know, you come through us, we hopefully make things better, which feeds back benefits to you in your, in your operation, but also to your kind of broader industry. So there are some vineyards, for example that I have personal relationships with from my whole life. And when Katie and I started collaborating and, you know, just generally sharing passions for a number of things, including wine and remote sensing, She asked if I had any, you know, friends who would let her take tissue samples who thought they might have particular diseases or were just curious to collaborate so that she could kind of do this proof of concept of these technologies and do these studies. And I was like, yeah, probably. So I just shot a couple of friends text messages and they were all like, sure. And the thing is, is like, they know me, right? And so they know that I'm not going to Never do anything intentional to bring harm. And I certainly would also go work very hard to make sure that even something I hadn't foreseen was protected. And I think that that's actually so critical, probably in every industry, but I'm most comfortable in agriculture. Like these are strong communities of trust that are built up. You know, you knew my dad and when I was 15 he had a major surgery in kind of mid, late August which coincides nicely with harvest, the beginning of harvest.

[00:33:57] Craig Macmillan: Yeah, the wine grape harvest in california.

[00:33:59] Alyssa Whitcraft: exactly. My dad was a winemaker in in Santa Barbara County, and that's where I grew up And I grew up in the winery so yeah when I was 15 He got he got really sick And he had to have a surgery and he was in the ICU for like a week and after that like it takes a while to recover so people that he had mentored, people who he had been close with for, you know, 20 odd years, 25 years in, in the region just kind of stepped up and processed his fruit, you know?

[00:34:28] So one, you miss one harvest, you're donezo, you know? Like that's just not how things work in the wine business. And my brother, who's now the winemaker, was only 19 at the time. So like, technically he wasn't even old enough to drink wine legally, but like, you know, he was there kind of. Running the ship with, you know, the huge support of these family friends who made it happen. So all that's to say, like those trust networks are everything in, in agriculture and everything in sort of agri food and like I said, probably other industries too, but I just don't know them. That's certainly the case in agriculture. And we're not going to make any like progress unless we build those trust relationships.

[00:35:08] And then since we can't meet everybody face to face, we need you know, those people to then be the hinge points to bring their, their kind of collaborators, colleagues, friends business partners, whatever, to the table to tell us what they need, to tell us what they want, give us feedback on what we've done and then work with us if they see value.

[00:35:27] Craig Macmillan: Yeah, I'm thinking of there are a number of organizations in the United States, in the wine industry, that fund or promote research on particular topics, and I can see there might be an opening there. you know, talking about trust, folks that have gotten awards, farmers that have been collaborators on these projects. I think it's a good place to start. For these new technologies. I think it's an interesting idea. I hadn't really thought about it that way. And I'm definitely going to take, take that away with me when I go to some of, these meetings. , and some of these, , some of these, , review, , committee

[00:35:57] Alyssa Whitcraft: Related to that, so one of the things we're just beginning to kind of explore the logistics of how we would implement it is identifying sort of farmer champions or kind of innovation partners. I don't know exactly what we want to call them, but they're people who are like amenable a collaboration

[00:36:17] , everybody only has so much time. So it takes time to do these things together. So if you have like a real passion or a real interest, it's something you might more willing to do. It helps us do it. the most good the most quickly. , so we're kind of looking at creating this kind of collaborator farmer innovation partner kind of thing where we work, you know, on their farms, they kind of give detailed feedback.

[00:36:38] They serve as different kind of hinge points, , to meet people in their community and really be champions we're doing, but also like not just be our hype guys and hype girls out there, but just be like, Hey, what you're doing makes no sense. Or like your aunt, you know, that's great that you created this capability.

[00:36:55] That gives me a forecast every week. I need it every day. Not useful to me. Things like that. So the frank feedback, , early adopters, but high touch early adopters, people who really are passionate about benefiting their industry and communities.

[00:37:10] Craig Macmillan: the state of the, world right now you've mentioned nations, lots of different crops, lots of, different technologies in your work and also kind of in the future, what's happening now to move all of this forward and where do you see it going?

[00:37:23] Alyssa Whitcraft: not to you know, date myself, somehow I'm one of like, the more se, I don't know senior is the right word, but like I'm no longer the young in this world. And so I've been around long enough that I started remote sensing in remote sensing of agriculture before.

[00:37:39] was really on an upward trajectory. Things have changed the last 15 or 16 years. But when things were really was the food price spikes in 2008 and 2011 that led to huge, push over a billion people into chronic food insecurity. It's horrible. So let's launch this called GeoGLAN Geo Global Monitoring that's going to use satellite data to give us information about, crop production globally.

[00:38:05] Some 40 odd years passed when. NASA first started doing it with Landsat. Within that GeoGLAM initiative, I was program and still in program scientist one of them. And my specific role is I work with the different space agencies in the world on developing new missions for agriculture.

[00:38:20] I basically advocate for the agriculture community to make sure we get the observations we need to do our analyses. what started out is very much this like food security, markets and trade kind of stuff. Segwayed over time, as the field grew, changed, ag tech blossoming, whatever it might be.

[00:38:38] And around 2019 2020 was when my specific focus started turning a little bit more, not stuff, but started zeroing in on the kind of farm level stuff. Because I got really interested in the way my discipline, my methods, my tools increasingly being used in the sort of sustainable ecosystem services marketplace.

[00:39:01] Without there being a whole lot of kind of methods, development, calibration, validation, like, yeah, we can, you know, create a map, but is it any good kind of thing? Or yeah, we can create a model, but does it work? People were coming to us with the NASA harvest name and the NASA kind of name and saying, can you validate this?

[00:39:17] Can you do And we all felt pretty strongly that our role was really to lift. votes for everyone. That's where we zeroed in on that topic wise in the Harvest Sustainable And Regenerative Agriculture Initiative, which we call Harvestera. I'm also the executive director of that. all these tools have advanced.

[00:39:35] The need has advanced. The audience's kind of openness has advanced. The kind of critical need for us to use agriculture as a tool belt to restore ecosystem health, soil health in rich communities and fight climate change, it all kind of needs to start at a baseline of understanding where we are and where we can go.

[00:39:54] And so I see satellite big part of that. This is all kind of coming together now. We still need the public sector's investment in terms of high quality observations. access, the lifting of the science in order for that to really take flight and be reliable and be good. that work that I've done for 12, 14, something like that, 13 years now through GeoGland with the space agencies has recently been morphing, into not just advocating for food security and market applications, but also saying, you guys, we got to think about ecosystem services.

[00:40:25] We have to think about sustainable management. Got to think about the precision. And so the space agencies are now receiving this message that there's a whole new set of value propositions for their data, but also the public sector pushing that direction.

[00:40:39] And then we like kind of push together. Toward impact.

[00:40:42] Craig Macmillan: one message that you would want to tell wine growers regarding this topic?

[00:40:46] Alyssa Whitcraft: Gosh, one message.

[00:40:48] Craig Macmillan: Two?

[00:40:51] Alyssa Whitcraft: Oh man, I guess you know, I think what a lot in my field don't think a lot about is quality Of the crops. We tend to think about quantity. Of the crops. and as a result, we can kind of answer use the wrong, use the wrong approach, answer the wrong question. And for specialty crops and I think, you know, what's finer than fine wine in, in terms of how much finesse you have to have from the 25 plus year old vines through bottling.

[00:41:20] What kind of needs a higher attention to quality I think that. for the grape growing community, particularly for wine and fine wine. they could maybe help shape this and push this, put out the demand there and say like, I don't need you to tell me how to absolutely maximize, make the like juiciest, wateriest, highest volume of berries.

[00:41:40] Like I need to know how to make the best quality. I need to know how to prevent losses related to extreme weather. I need to make sure I don't have my die that, I've been cultivating for so long to build these beautiful old growing and all that, they're more important than maybe they realize they are in this space and could push to really move our science and usership toward quality more than perhaps we have historically.

[00:42:03] Craig Macmillan: and I really appreciate you sharing that. This has all made me think about an interview that I did recently with an extensionist from Texas A& M we were chatting after the interview actually about climate change. She said, there is not a single grower in the state of Texas that is a climate denier.

[00:42:22] Everybody sees it. It is getting hotter. And things are changing and they're going to have to change. There's no doubt about it. And that reminds me of changes in other agro systems. over time whether it's changes in the way the soil fertility is, or changes in rainfall, or changes in disease patterns. I think there's applications, especially in areas that are suffering extreme stresses now, that'll apply to places that'll suffer extreme stresses, maybe a little bit later.

[00:42:49] So I think that's a great message that we can bring to These programs say, Hey, we need. And here's maybe how can we do it? How can we benefit from what you're already doing? I think that's a great message. Where can people find out more about you?

[00:43:01] Alyssa Whitcraft: if you want to find out more about NASA acres, you can go to org. If you want to find out more about the Harvest Sustainable and Regenerative Agriculture Initiative, that would be HarvestSara. org basically any program I've said today, you can just put a org at the end and it'll work. And if you want to learn about my family winery, it's WittcraftWinery. com And just shout out to my dad, my mom, and my brother for kind of sparking and maintaining my love of and interest in food and wine.

[00:43:33] Craig Macmillan: Yeah, And just on a personal note your dad, Chris was a mentor of mine. It was one of the first winemakers That I worked side by side with and had a huge impact on me. Especially around the idea of quality.

[00:43:43] Alyssa Whitcraft: Okay, so not to totally digress here, Maybe it's germane to the topic, which is I was pre med at UCLA. And I took a a geography general ed course called people in Earth's ecosystems just to fulfill a gen ed requirement and fell in love. And that professor bonded. and he did a lot of remote sensing of tropical I took his remote sensing class. We were supposed to. pick a and design it. And the picked was trying to. Compare every single metric that we could derive from satellite data for Conti, with, with some vineyards that my dad sourced from at the time so like Bien Nacido. Obeying these different vineyards and trying like in compare, I mean, it was the polar opposite of a robust study. I was like 20 and it was my first remote sensing class, but it really like capped my interest because trying to understand. Obviously there's the climate pieces to some degree, there's the soil pieces, but you know, my dad was the first or one of the first at least to do the blocks designation in wine.

[00:44:45] So he had N block and Q block and Bien Nacido. And I was like, well, what was it? characteristic that made them sort of different? Could you come up with that in a way, not that we should quantify and sanitize everything because there's certainly a je about these things, but like, what is it that creates quality, ?

[00:45:01] , and what of it is sort of biophysical in nature and could be measured and that kind of really sparked the interest that shaped the rest of my career.

[00:45:09] Craig Macmillan: That's fantastic. I really want to thank you for being on the podcast. Our guest today was Alyssa Whitcraft. She's executive director of NASA acres, fascinating conversation and tying together some pieces from previous podcasts. Yeah, just thanks for being a guest

[00:45:24] Beth Vukmanic: thank you for listening. Today's podcast was brought to you by, Baicor. A manufacturer of fertilizers, specializing in liquids for foliar and soil applications. By course, plant nutrients are 100% environmentally friendly and organically based. Each is specifically formulated to provide the optimum level of nutrients, plants need. Baicor's products. Are created from organic and amino acids found naturally in plants and in the soil. They use the finest natural materials. Blended scientifically to assure quality and effectiveness.

[00:46:02] Make sure you check out the show notes for links to Alyssa NASA harvest NASA acres plus sustainable Winegrowing podcast episodes 199 NASA satellites to detect grapevine diseases from space. And 233, the gap between space and farm ground-truthing satellite data models.

[00:46:21] If you'd like the show, do us a big favor by sharing it with a friend subscribing and leaving us a review. Until next time, this is a sustainable Winegrowing with the vineyard team.

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