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The Dynamic Aerial Survey Algorithm Architecture and Its Potential Use in Airborne Fertilizer Applications

Gregory Falzon, David 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
Pages (from-to)1772-1779
JournalIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Volume5
Issue number6
DOIs
Publication statusPublished - 2012

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 2 - Zero Hunger
    SDG 2 Zero Hunger
  2. SDG 15 - Life on Land
    SDG 15 Life on Land

Keywords

  • Agricultural Land Management
  • Agricultural Spatial Analysis and Modelling
  • Decision Support and Group Support Systems
  • Photonics and Electro-Optical Engineering (excl Communications)

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