Location: Location not imported yet.Title: Remote sensing for detecting and mapping whitefly (Bemisia tabaci) infestations) Author
Submitted to: Springer Verlag
Publication Type: Book / chapter
Publication Acceptance Date: 7/15/2011
Publication Date: 9/12/2011
Citation: Yang, C., Everitt, J.H. 2011. Remote sensing for detecting and mapping whitefly (Bemisia tabaci) infestations. In: Thompson, W.M.O., editor. The Whitefly, Bemisia tabaci (Homoptera: Aleyrodidae) Interaction with Geminivirus-Infected Host Plants. 1st edition. Springer Netherlands. p. 357-381. Interpretive Summary: N/A
Technical Abstract: Remote sensing technology has long been used for detecting insect infestations on agricultural crops. With recent advances in remote sensing sensors and other spatial information technologies such as Global Position Systems (GPS) and Geographic Information Systems (GIS), remote sensing is finding more and more practical applications for the detection and management of insect pests, including sweetpotato whitefly (Bemesia tabaci Gennadius). This chapter begins with an extended overview of remote sensing principles and systems that can be used for entomological studies. Properties and behavior of electromagnetic energy, major divisions of the electromagnetic spectrum (i.e., ultraviolet, visible, infrared and microwave), and the interactions between radiation and ground targets are discussed. Major types of remote sensing systems are described, including ground-based spectroradiometers, aerial photographic cameras, airborne digital multispectral and hyperspectral imaging systems, and moderate and high resolution satellite imaging systems. The second part of the chapter provides a brief review on the use of remote sensing for detecting whitefly infestations and presents an application example to illustrate how remote sensing can be integrated with GPS and GIS technologies for detecting and mapping whitefly infestations in cotton fields. The methodologies for ground reflectance and airborne image acquisition and for the integration of image data with GPS and GIS are discussed.