Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/12213
Title: The Dynamic Aerial Survey Algorithm Architecture and Its Potential Use in Airborne Fertilizer Applications
Contributor(s): Falzon, Gregory  (author)orcid ; Lamb, David  (author); Schneider, Derek  (author)orcid 
Publication Date: 2012
DOI: 10.1109/JSTARS.2011.2179020
Handle Link: https://hdl.handle.net/1959.11/12213
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.
Publication Type: Journal Article
Source of Publication: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 5(6), p. 1772-1779
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Place of Publication: United States of America
ISSN: 2151-1535
1939-1404
Fields of Research (FoR) 2008: 070104 Agricultural Spatial Analysis and Modelling
070101 Agricultural Land Management
090606 Photonics and Electro-Optical Engineering (excl Communications)
080605 Decision Support and Group Support Systems
Fields of Research (FoR) 2020: 300206 Agricultural spatial analysis and modelling
400909 Photonic and electro-optical devices, sensors and systems (excl. communications)
460507 Information extraction and fusion
Socio-Economic Objective (SEO) 2008: 960504 Ecosystem Assessment and Management of Farmland, Arable Cropland and Permanent Cropland Environments
820507 Wheat
820404 Sorghum
Socio-Economic Objective (SEO) 2020: 180601 Assessment and management of terrestrial ecosystems
260312 Wheat
260310 Sorghum
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article
School of Science and Technology

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