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Multi‐spectral remote sensing applications for agriculture.
UAS Research Applications for Precision Agriculture 2012 Unmanned Aircraft Systems (UAS) Action Summit:“From Battlefield to Farm Field”May 22 & 23, 2012Alerus Center, Grand Forks, ND
Douglas R. OlsenUpper Midwest Aerospace Consortium (UMAC)Dept. of Earth System Science and PolicyJohn D. Odegard School of Aerospace SciencesUniversity of North DakotaGrand Forks ND
AcknowledgementsHo Jin Kim
Clint Streeter
Multi‐spectral Remote Sensing and Agriculture
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Agricultural Applications Crop identification, acreage
estimation Crop conditions – and in‐field
variability Decision support for management –
drought, pests, flooding, disease, etc.
Normalized Difference Vegetation Index (NDVI) NDVI = (NIR ‐ RED) / (NIR + RED)
Methods to obtain multi‐spectral imagery Satellite imagery – lower resolution,
wider area Airborne imagery – higher
resolution, generally cost‐prohibitive UAS – higher resolution without the
higher cost?
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400 800 1200 1600 2000 2400
Refle
ctan
ce
Wavelength (nm)
Spectral signatureSoil
Green Vege.
Scenese Vege.
Dry vege.Green Red
NIR
Blue
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AEROCamAirborne Environmental Research Observational Camera (AEROCam) 4‐band (B, G, R, NIR) multi‐spectral camera CCD array size of 1920 x 1080 Ground sample distance (GSD) between 0.25 to 2
meters, depending on aircraft altitude Radiometrically calibrated at NASA Ames
Equipment UND Student built; flown annually onboard UND
Piper Arrow aircraft since 2002 Inertial Measurement Unit (IMU), GPS, power,
computer, displays, mounting (~125 lbs.)
GSD 1
Altitude 1
Altitude 2GSD 2
AEROCam
AEROCam undergoing calibration
Non‐Agricultural Application using AEROCam – Disaster Monitoring
4AEROCam images over city of Minot, ND, illustrating inundation from Souris River flooding (July 5, 2011).
Agricultural end user applications of remote sensing imagery – a short list of examples…
• Assessing rangeland maturity for herd and pasture management• Estimating cow‐carrying capacity of leased rangeland• Detecting invasive species in grasslands, for spot treatment• Planning improvement in field drainage• Estimating nitrogen credit available from vegetation residual• Use as a field guide for fee hunting services• Verifying compliance with government programs• Mapping and estimating acreage and crop types• Crop condition monitoring to aid decision support in crop management• Determining zone map boundaries for variable rate application• Proving and quantifying crop damage due to human or environmental
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Application #1 – Precision Agriculture Variable‐rate application of fertilizer, herbicides, other inputs
Increase production where soils and other conditions allow Reduces cost and improves environmental stewardship
Crop vigor from previous year, determined by multi‐spectral imagery, can be used to “write a prescription” for fertilizer
Does NOT indicate how much, but rather, what parts of the field are alike, and thus can be treated in a similar manner
Satellite (ASTER): 15 meters Resultant zone map
Application #2 – Crop Management Decision Support
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Soybeans #
# Bean Leaf Beetleand GrasshopperDamage
#
Waterhemp
CornAreas wherenitrogen fertilizerwas not applied.
False Color Composite (FCC) imagery from IKONOS spacecraft (4 m pixels)
Is fungicide at $14.55/acre worth applying?
Enables spot treatment of weed and insect infestations
<-No fungicide
<-Fungicide applied(7.6 bu/ac more yield
Application #3 (Crop Damage Assessment)
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• Misapplication of fertilizer in sugar beets by vendor– Overlaps applied too much and “burned” foliage– Skips caused shortage of nutrients – Imagery allowed for easy measurement of total area affected– Farmer was reimbursed $24,000 for damage
False Color Composite (FCC) image from AEROCam (1 meter pixels)
Classified image from NDVI, with three classification levels: damaged areas in Red
Crop Damage Assessment (Cont’d)
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Crop damage due toherbicide drift in windyconditions
Crop Damage due to fault aerial equipment Visible damage was transitory, but caused reduction in yield
Timely image acquisition enabled insurance claim