In-field and Remote Sensing for Precision Agriculture. John Nowatzki Extension Ag Machine Systems Specialist North Dakota State University

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Transcription:

In-field and Remote Sensing for Precision Agriculture John Nowatzki Extension Ag Machine Systems Specialist North Dakota State University

UAS in Precision Agriculture In-field Sensors Selecting UAS Equipment NDSU UAS Activities Current UAS Applications Future UAS Applications and Needs

Precision Agriculture & Data Management Computer Software Commercial Services Big Data

Selecting suas Equipment for Agricultural Applications Multi-Rotor Fixed-wing Advantages Disadvantages Advantages Disadvantages Any Camera Short flight time Cover larger area Takeoff space Ease of use Small area Longer flight time Ability to hover Slower Speed Simpler structure More stable flight Vertical takeoff and landing Assistance for takeoff More complex Greater payload Larger in size Less expensive Smaller Payload Multiple sensors More expensive https://www.ag.ndsu.edu/agmachinery

UAS Platforms Hermes 450 Small UAS Rules Phantom 3 3DR RTF X8 Altavian Trimble UX5 RF70 - Troybuilt https://www.ag.ndsu.edu/agmachinery

Small UAS Rules Less than 55 lbs. Remote Pilot Airman Certificate Line of Sight Daylight Hours 400 or Below https://www.ag.ndsu.edu/agmachinery

Remote Sensing for Agricultural Applications Color RGB Multi-spectral Hyper-spectral Vegetative Index NDVI https://www.ag.ndsu.edu/agmachinery

UAS Sensors Ximea Cameras GoPro Camer ICI 9640 S Thermal camera Hyperspectral Large area scanning EO/IR/NIR camera Sony NEX-5R camera with NIR Tetracam ADC Sentera dual sensor (4 band) Sentera Quad sensor (6 band) MicaSense Rededge Ximera Hyperspectral sensor Rikola Hyperspectral sensor Rikola Elbit EO/IR ICI 9640 Thermal Sentera Sony NEX-5R

NDSU UAS Activities Small and Large UAV S Phantom 3 Trimble UX5

Large-scale UAS Project Imagery in May, June, July and August Color, Infrared Sensor 4,000, 6,000 and 8,000 ft Small UAS, Satellite, Ground and Yield Data All Imagery Securely Stored on NDSU Computers Objectives Uses for Crop Management Economic Value to Producers

Project Location Eastern ND

Hermes 450 UAS

Hermes 450 UAS Control Center

Hermes 450 UAS Control Center

First Large UAS Civilian Flight in North Dakota

Landing the Hermes 450

View from CAP Chase Plane

Data Management Large UAS Entire Corridor Each Date Date May 23-27 June 20-24 July 18-22 August 15-19 Altitude 4,000 6,000 8,000 6,000 8,000 6,000 8,000 4,000 8,000 Image Quantity Total Size 2.0 TB 1.5 TB 0.5 TB 4.0 TB 1.5 TB 0.5 TB 2.0 TB 1.5 TB 0.5 TB 2.0 TB 2.0 TB 0.5 TB 2.5 TB Total Quantity of Imagery Collected during the Project: 10.5 TB Plus Small UAS Imagery Plus Image Analyses

NDSU Extension Role Facilitate Collaborate Educate

May Imagery: 4,000 6,000 8,000 4,000 8,000 6,000 Detailed Imagery - 50,000 Acres/Hour

Analyses from Imagery: Cattle from 8,000

Cattle in May Imagery: 4,000

Corn Imagery: May June July - August

Analyses from Imagery: Zone Map

~ 40 Acres Imagery 4,000 RGB Image 4 cm Pixel Size

~ 200 x200 Imagery 4,000 RGB Image 4 cm Pixel Size

Imagery Issues: Time Between Images

Imagery Issues: Time Between Images Color Image

Imagery Issues: Time Between Images NDVI Image NDVI Mean=0.6514 NDVI Mean=0.4975

Sensors Ag Leader OptRx

Available Crop Sensors OptRx Ag Leader CropSpec Topcon GreenSeeker Trimble Crop Circle Holland Scientific

$50 ipad iphone app Android coming soon! $100

Collecting NDVI with Ground Sensors Collecting In-field OptRx Sensor Data.

NDSU Soybean Plots

Variety 1: lb N and Aug NDVI NDSU Steele County Plots 0.548 0.547 y = 0.0001x + 0.5411 R² = 0.9643 0.546 0.545 0.544 0.543 0.542 0.541 0.54 0 10 20 30 40 50

63.5 August NDVI and Yield for 0, 25, 50 lb N NDSU Steele County Plots 63 62.5 y = 268.03x - 83.261 R² = 0.74 25 lb N /acre 62 61.5 61 0 lb N /acre 50 lb N /acre 60.5 0.536 0.537 0.538 0.539 0.54 0.541 0.542 0.543 0.544 0.545

Hail Damage: Corn from 4,000 17 Acres out of 67 acres

Digital Elevation Model Using Large UAV

Corn Field May 23, 2016 Flight Altitude: 50ft NDVI Mosaic

Ground count Corn plants detection and counting ground truth 1800 1600 1400 1200 1000 y = 1.0308x + 0.4078 R² = 0.9991 800 600 400 200 0 0 200 400 600 800 1000 1200 1400 1600 1800 UAS Count

Web Application for Stand Count Analyses from UAS Imagery

Identifying Herbicide-resistant Weeds

Sugarbeet Disease Detection with UAS Rhizoctonia solani infestation Cercospora infestation AIR-AGFO, 2015 44

What Has Gone Well Collaboration: NDSU NP UAS Test Site Elbit - CAP FAA and FCC NDSU County Extension Service Hillsboro Airport Authority Image Quality Objectives: Imagery from 4,000 6,000 8,000 Transfer and Storage of Imagery at NDSU Analyses Nitrogen Management Stand Count Disease Identification Hail Damage Elevation Model

Future of UAS in Agriculture Small UAS Plant Stand Count Monitoring and Scouting In-season Fertility Large and Small UAS Digital Elevation Model In-season Fertility AeroDrone Yield Predictions Insect and Disease Movements Identification of Management Issues Yamaha RMAX 8 liters x 2 tanks One More Layer for Big Data Precision Agriculture

Book for Technology Early Adopters Innovation and It s Enemies. Why People Resist New Technologies Calestous Juma Moral Values Human Health Environmental Safety Socioeconomic Coffee Printing Press Margarine Farm Mechanization Electricity Refrigeration Recorded Music Transgenic Cops Transgenic Animals

Questions - Comments Office 701-231-8213 Cell 701-261-9842 John.Nowatzki@ndsu.edu http://www.ag.ndsu.edu/agmachinery