The dynamic aerial survey algorithm architecture and its potential use in airborne fertilizer applications

Greg Falzon, David W. Lamb, Derek Schneider

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

The architecture and general structure of the Dynamic Aerial Survey (DAS) algorithm is presented in this paper. This algorithm is specifically designed for real-time airborne prescription fertilizer applications in the agricultural industry and is designed to batch process the dynamically updated data set after the aircraft completes each successive pass over the field using remote crop monitoring equipment. A key aspect of the DAS algorithm is that it allows a variety of different regression and segmentation modules to be added or deleted to suit user requirements. A specific application is presented concerning an aerial geo-survey of a 110 ha wheat field. The DAS algorithm, using the support-vector regression machine and the uniform-cut segmentation modules, will be demonstrated to allow accurate 'on-the-go' estimation, updating and segmentation of the entire field into different management zones as the aircraft completes each pass. The DAS algorithm constitutes a key step in a wider research program designed to develop active-sensor based aerial prescription technology.

Original languageEnglish
Article number6125997
Pages (from-to)1772-1779
Number of pages8
JournalIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Volume5
Issue number6
DOIs
Publication statusPublished - Dec 2012
Externally publishedYes

Keywords

  • Adaptive signal processing
  • agriculture
  • aircraft expert systems
  • algorithms
  • decision support systems
  • geophysical signal processing
  • remote sensing

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