Multispectral imaging systems for airborne remote sensing to support agricultural production management

Yanbo Huang, Steven J Thomson, Yubin Lan, Stephan J Maas

Abstract


This paper investigated three different types of multispectral imaging systems for airborne remote sensing to support management in agricultural application and production.  The three systems have been used in agricultural studies.  They range from low-cost to relatively high-cost, manually operated to automated, multispectral composite imaging with a single camera and integrated imaging with custom-mounting of separate cameras.  Practical issues regarding use of the imaging systems were described and discussed.  The low-cost system, due to band saturation, slow imaging speed and poor image quality, is more preferable to slower moving platforms that can fly close to the ground, such as unmanned autonomous helicopters, but not recommended for low or high altitude aerial remote sensing on fixed-wing aircraft.  With the restriction on payload unmanned autonomous helicopters are not recommended for high-cost systems because they are typically heavy and difficult to mount.  The system with intermediate cost works well for low altitude aerial remote sensing on fixed-wing aircraft with field shapefile-based global positioning triggering. This system also works well for high altitude aerial remote sensing on fixed-wing aircraft with global positioning triggering or manually operated.  The custom-built system is recommended for high altitude aerial remote sensing on fixed-wing aircraft with waypoint global positioning triggering or manually operated.

Keywords: airborne remote sensing, multispectral imaging, agricultural production management

DOI: 10.3965/j.issn.1934-6344.2010.01.0-0 

Citation: Yanbo Huang, Steven. J. Thomson, Yubin Lan, Stephan J. Maas. Multispectral imaging systems for airborne remote sensing to support agricultural production management.  Int J Agric & Biol Eng, 2010; 3(1):


Keywords


airborne remote sensing, multispectral imaging, agricultural production management



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