MULTISPECTRAL IMAGING SYSTEMS FOR AIRBORNE REMOTE SENSING TO SUPPORT SITE-SPECIFIC AGRICULTURAL MANAGEMENT
Remote sensing has shown promise as a tool for site-specific management in agricultural application and production. Earth-observing satellite systems have an advantage for large-scale analysis at regional levels but are limited in spatial resolution. High-resolution satellite systems have been available in recent years, but scheduling these systems for appropriate bands, location of flight, proper altitude, and time of acquisition is difficult. Airborne remote sensing systems offer a flexible, do-it-yourself platform to configure for high quality, high spatial resolution imagery at any desired spectral combination, location, altitude, and time. Use of airborne hyperspectral remote sensing in agriculture has been steadily increasing during the past decade. Compared with hyperspectral systems, multispectral systems are much lower in cost and are less data-intensive. Airborne multispectral techniques are cost-effective and still a good source of crop, soil, or ground cover information for agricultural application and production. This paper investigates three different types of multispectral imaging systems for airborne remote sensing to support site-specific 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 individual imaging with assembly of separate cameras. Practical issues regarding use of the imaging systems are described and discussed. The advantages and disadvantages of each system are summarized and compared in different configurations. The information is provided for developing practical aerial remote sensing systems. System applications are suitable for fixed-wing aircraft and unmanned autonomous helicopter or fixed-wing platforms.
Airborne Remote Sensing Multispectral Imaging Site-Specific Management
Yanbo Huang Steven.J.Thomson Yubin Lan Stephan J.Maas
USDA ARS Application and Production Technology Research Unit,Stoneville,MS 38776,USA USDA ARS Areawide Pest Management Research Unit,College Station,TX 77845,USA Texas Tech University,Lubbock,TX 79409,USA
国际会议
北京
英文
1-21
2009-10-14（万方平台首次上网日期，不代表论文的发表时间）