Drones, Data and Weeds

John Coulombe

• I am originally from Sacramento California and have been an Australian citizen for 12 years.

• Environmental Science Degree (Resource Management) from Southern Cross University

• Adjunct Fellow and Lecturer at University of Queensland

• Casual Lecturer at Central Queensland University (Agriculture)

• PhD candidate with a focus on using aerial acquired thermal and multispectral data. (CQU)

• I have worked as a UAV consultant for, Applied Horticultural Research, MLA and Southern Cross Drones

Who am I?

Terminology Explained• RGB - Red, green, blue (standard camera similar to your phone camera)

• Multispectral- camera with near infrared lens and R,G,B (this is what is used for NDVI maps)

• Hyperspectral- also known as imaging spectroscopy, is a relatively new technology that is currently being investigated by researchers and scientists with regard to the detection and identification of minerals, terrestial vegetation, and man-made materials and backgrounds

• NDVI- This is Normalized Difference Vegetation Index (basically a calculation needed to turn Near infrared into a nice green, yellow and red heat map)

• Machine Learning/AI (artificial intelligence)- When used with drone data for weed or other types of identification, it is referring to the computer working out what you want from what you have been looking at (if you count a certain type of plant/weed over and over the computer will learn this and then through a bunch of math will start counting the plant/weed, cow or sheep for you.

Terminology Explained Cont.• VARI - The Visible Atmospherically Resistant Index (VARI) was designed and

tested to work with RGB sensors. VARI is a measure of “how green” an image is. VARI is not intended as a substitute for an NIR camera, but it is meaningful when working with non-NDVI imagery. RGB images with the VARI algorithm applied make it possible to detect areas of crop stress in a field

• Orthomosaic map- Put simply, an orthomosaic map is created out of many photos that have been stitched together and geometrically corrected (“orthorectified”) so that it is as accurate as a map

• Big Data- A new attitude by businesses, non-profits, government agencies, and individuals that combining data from multiple sources could lead to better decisions

• Photo metadata- allows information to be transported with an image file, in a way that can be understood by other software, hardware, and end users, regardless of the format.

More data doesn’t mean anything unless you can use it!

BIG DATA

DRONES

1 2 3

How It Works: It is much easier than you think!

Fly Process Analyze

Mission Planning Apps- These apps are usually free to use

This is what you see when you first start planning a new flight

Then you just start moving the points where you want them

Once you finish with where you want to fly you then determine how high, what overlap you want and direction of flight THAT’S IT YOU ARE READY TO FLY!

Choose upload

Click on upload and choose photos from desktop

Click on upload and choose photos from desktop THAT’S IT NOW WAIT FOR THE EMAIL

Orthomosaic map with volume of dead spot

Width of treatment

Weed counting

Weed counting, dead patch, treatment area #1 and weed count

Several measurements and annotations

Orthomosaic Map

Orthomosaic Map with VARI algorythm

Orthomosaic Map with VARI algorithm magnified

Orthomosaic Map (weed #1)

Orthomosaic Map (weed #1 with area)

Orthomosaic Map (weed #2 with area)

Not much to see when you don’t have irrigation or rain

Same data, but using VARI algorithm

No Silver Bullets- Most of the time you will still need to go to the spot of interest and ground truth what the variability is!

AI for counting cattle

Picterra

What to do now that you found the weeds?

Drone sprayerAerial spraying

Quad spraying

Hand sprayingBurning Tractor spraying

https://www.youtube.com/watch?v=qj5tODEA1-wYou Tube--

Picterra CH- FROM DEEP LEARNING TO CUSTOM GEO-INFORMATION “AI”

Picterra CH- FROM DEEP LEARNING TO CUSTOM GEO-INFORMATION “AI”

Picterra CH- FROM DEEP LEARNING TO CUSTOM GEO-INFORMATION “AI”

DRONES

• Agricultural Drones

Measure plant health details Generate plant counts and forecast yield Optimize input timing Detect plant health patterns before they’re visible Assess livestock health and weight gain Identify damaged fencing Assess storm damage Calculate grove maturity Determine optimal foraging areas

DRONES

• Corteva Agriscience™ Deploys The Largest Agricultural Drone Fleet In The World

The world’s largest agricultural drone fleet is transforming the way farmers manage their crops. Through a collaboration with Corteva Agriscience™, Agriculture Division of DowDuPont, DroneDeploy’s advanced mapping software is powering Corteva Agriscience’s fleet of more than 400 DJI drones

Detect Aphids, Rust & Fungi

By catching an aphid infestation early, Dusty prevented nearly $60,000 in lost revenue over

185 acres of sugar beet

Comparing Different Test Plots

Accurate Crop Loss Assessment

In one instance, DroneDeploy

helped a farmer identify crop

loss of almost 50%, compared

to the 34% offered by the

insurance adjustor and he was

able to recoup $110,000 from

insurance

QUESTIONS?