Imagery in Agriculture: Some Sage Advice

Imagery in Agriculture: Some Sage Advice

SatShot President Lanny Faleide has been a fixture on the remote imagery scene for as long as about anyone still trying to make the technology work for agriculture. He was one of the first people we met back in the late 1990s as we were trying to understand what the new thing called “precision agriculture” was all about.


So as we wrapped up this issue featuring a special report on row crop imagery, we thought it would be appropriate to get some perspective on where he is, where we are, and where the industry needs to go to truly move imagery as a must-use tool in crop production.

PAg Pro: How did you get started on imagery in the first place?

Lanny Faleide: I took the first image of my field back in 1977 with near-infrared film (remember that stuff?). I never processed it because it couldn’t be done locally, but I didn’t need to. That day I discovered something I didn’t really want to know — my fields did not look good. Yes, this wet-behind-the-ears flying farmer found out that looking at fields from above revealed they had problems.

Twenty years later, in 1997, the first actionable Variable Rate Application (VRA) image from a satellite was done on my central North Dakota field, yet the industry still seems confused about VRA using an image to this day.

Every imagery product — from satellites, aerial sources, or UAVs — are great tools, and each source acquires data at different scales: satellites at 1 to 30 meters, airplanes at sub meter, and UAVs at sub inch.

But why this data is great is that it reveals from above where the problem and good areas are, and puts them in a mapped context to navigate from. Nothing more, nothing less. The near-infrared wavelength allows you to quantify vegetation (through an algorithm) to compare biomass at different times and detect [qualify] changes.

PAg Pro: What keeps you going in this market?

LF: This is my 23rd year being a professional vendor of satellite imagery in the precision ag industry, and many may wonder why I am still doing this. I guess it’s because I love being a detective. Every field has a different story and I like to discover it! I’ve even been called precision agriculture imagery’s elder statesman. (Sounds suspiciously like being put out to pasture!)

But, I have learned a lot, and the principles are the same as they were back when I first observed my fields from the air 40 years ago. The key is this: determine vegetation anomalies through geo-referenced pixels, relate it to the agronomic condition, and then do something about it. (That is to say, make a decision about it, even if that decision is to do nothing.) Change the yield potential by appropriately applying fertilizer, seed, or chemical where it’s needed, and not applying it where it is not needed.

PAg Pro: Are we closer to getting to that happy place where imagery finds a solid role in the precision agriculture regimen than we were two decades ago?

LF: We are closer to getting to that “happy place” where imagery finds a solid role in precision ag than we were two decades ago, but there are still doubters and cynics, and they have this elder statesman scratching his head.

Is it the technology that we are intimidated by? Or is it too simple? Do we really need to combine 10 different layers and make it complicated — to define that this anomaly is a hill or low area — before we do something about it?

Let your crops tell you the answer; listen to them, if you will. If “reading” the crop is problematic, study up. Research online or take a class to learn about soils, soil structure, how plants grow, and how they react to stimuli.

PAg Pro: What has to happen for us to get there?

LF: Fortunately — or unfortunately — there are no magic formulas in the vegetation index world. So laziness or lackadaisical attitudes will not reveal the man behind the curtain, and will not get the work done. Remember, it’s all just biomass with different hats on.

If you need any more incentive, currently an image of any field — in any place in the world — is shot every 5 days (except when prohibited by weather events), then sent to a machine in less than 5 minutes.

The answers are there. Pay attention to your crops. Listen. Evaluate. Respond.

That’s the answer to precision agriculture success.

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Robson Fernando de Paula says:

It was so great advice, Agree completely when the author pointed out that the answers are there and if the crop is problematic we need to learn agronomy deeply. It´s the real meaning of Precision Agriculture.

John Sulik says:

Vegetation indices aren’t just biomass with different hats on. Structural indices such as NDVI, SAVI, and EVI are just biomass but there are other useful indices that are more sensitive to pigments. For instance, chlorophyll indices don’t indicate biomass as much as they correspond with variation in chlorophyll content (i.e. mass vs color). In addition, we now have improved understanding of how to use spectra to sense reproductive (as opposed to vegetative) growth in some dicots, which is also of economic importance in some broad acre crops (e.g. canola) and horticulture.