Hydrology and Remote Sensing Laboratory Site Logo
ARS Home About Us Helptop nav spacerContact Us En Espanoltop nav spacer
Printable VersionPrintable Version     E-mail this pageE-mail this page
Agricultural Research Service United States Department of Agriculture
Search
  Advanced Search
Programs and Projects
Airborne Remote Sensing Basics
ARS Remote Sensing Workshop
OPE3
Crop Condition and Yield Research
Jornada Experiment
Monsoon '90
Soil Moisture Program
Remote Sensing in ARS Workshop 2000
 

Research Project: SPECTRAL AND SPATIAL MEASUREMENTS AND MODELING TO IMPROVE NUTRIENT MANAGEMENT AND ENVIRONMENTAL QUALITY

Location: Hydrology and Remote Sensing Laboratory

Title: HIGH RESOLUTION MULTISPECTRAL DIGITAL PHOTOGRAPHY USING UNMANNED AIRBORNE VEHICLES.

Authors
item Hunt, Earle
item Walthall, Charles
item Daughtry, Craig
item Fujikawa, Stephen - INTELLITECH MICROSYSTEMS
item Yoel, David - INTELLITECH MICROSYSTEMS
item Khorrami, Farshad - INTELLITECH MICROSYSTEMS
item Tranchitella, Michael - INTELLITECH MICROSYSTEMS

Submitted to: Meeting Abstract
Publication Type: Abstract
Publication Acceptance Date: June 21, 2005
Publication Date: October 5, 2005
Citation: Hunt, E.R., Walthall, C.L., Daughtry, C.S., Fujikawa, S.J., Yoel, D., Khorrami, F., Tranchitella, M. 2005. High resolution multispectral digital photography using unmanned airborne vehicles [abstract]. 20th Biennial workshop on Areal Photography, Videography, and High Resolution Digital Imagery for Resource Assessment. 2005 CDROM.

Technical Abstract: An Unmanned Airborne Vehicle (UAV) from IntelliTech Microsystems, Inc. was fitted with two down-looking digital cameras, an up-looking quantum sensor, and computer controls based on GPS position. The internal filters of the cameras were removed and external narrow-band filters at 490 nm, 550 nm, 610 nm, 675 nm, and 800 nm were fitted onto the cameras. Colored tarpaulins were used to calibrate the images; there were large differences in digital number (DN) for a given tarpaulin. When incident radiation was accounted for using the quantum sensor, the imagery matched the tarpaulin reflectances. For soybean, alfalfa and corn grown at the Beltsville Agricultural Research Center, dry biomass from zero to 120 g m-2 was linearly correlated to vegetation indices based on a visible band and the 800 nm band, but for biomass greater than 150 g m-2 in corn and soybean, these indices were saturated. UAV¿s can be launched in narrow windows of good weather, fly large fields in preplanned patterns, and deliver the data rapidly to the user at lower cost, making these data particularly suitable for precision agriculture.

   

 
Project Team
Daughtry, Craig
Rawls, Walter
Anderson, Martha
Walthall, Charles
Hunt, Earle - Ray
Gish, Timothy
 
Publications
   Publications
 
Related National Programs
  Soil Resource Management (202)
  Integrated Farming Systems (207)
 
 
Last Modified: 10/27/2008
ARS Home | USDA.gov | Site Map | Policies and Links 
FOIA | Accessibility Statement | Privacy Policy | Nondiscrimination Statement | Information Quality | USA.gov | White House