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Title: Remote Sensing of Leaf Area Index from Unmanned Airborne Vehicles (UAVs)

Author
item Hunt Jr, Earle
item Hively, Wells - Dean
item FUJIKAWA, STEPHEN - INTELLITECH MICROSYSTEMS
item TRANCHITELLA, MIKE - INTELLITECH MICROSYSTEMS
item NG, T - INTELLITECH MICROSYSTEMS
item RASZULA, WOODY - INTELLITECH MICROSYSTEMS
item YOEL, DAVID - INTELLITECH MICROSYSTEMS
item Daughtry, Craig
item McCarty, Gregory

Submitted to: Society for Range Management Meeting Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: 9/19/2007
Publication Date: 1/26/2008
Citation: Hunt, E.R., Hively, W.D., Fujikawa, S., Tranchitella, M., Ng, T.L., Raszula, W., Yoel, D., Daughtry, C.S., McCarty, G.W. 2007. Remote sensing of leaf area index from Unmanned Airborne Vehicles (UAVs)[abstract]. Society for Range Management Meeting Proceedings. 2008 CDROM.

Interpretive Summary:

Technical Abstract: Remote sensing with unmanned airborne vehicles (UAVs) has potential for rangeland management because: (1) pixels have very high spatial resolution, (2) cloud cover would not prevent acquisition during critical periods of plant growth, and (3) information is quickly delivered to the user. Winter wheat was planted early (October 2006) and late (November 2006) on the Eastern Shore of Maryland (39° 2’ 2” N latitude, 76° 10’ 36” W longitude). Each planting was divided into 6 north-south strips, each with various levels of nitrogen fertilizer, which caused large variations in leaf area index, biomass and yield. The Vector P aircraft from IntelliTech Microsystems (Bowie, Maryland) was flown on three dates in late April/early May 2007 at two elevations. A color-infrared digital camera was mounted in the Vector P and the pixel sizes were 6 cm at 210 m elevation and 3 cm at 115 m elevation. Inspection of the photographs revealed large spatial variation in biomass and leaf area index within each strip. Because pixel size was much smaller than the position error of the airborne global positioning system, field plots (20 cm by 50 cm) were located using visual features. As with most airborne photography, there were problems with vignetting and anisotropy, which reduces the usable area of each photograph. Vegetation indices are useful to reduce problems with radiometric calibration, exposure, solar irradiance, and view angle. The green normalized difference vegetation index [GNDVI = (NIR - green)/(NIR + green)] was linearly correlated with leaf area index and biomass. There were no significant differences in the regressions of GNDVI and leaf area index based on pixel size. In rangeland ecosystems, GNDVI is more likely to be related to plant cover than ecosystem leaf area index.