Automated detection and segmentation of vine rows using high resolution UAS imagery in a commercial vineyard

A. P. Nolan, S. Park, M. O'Connell, S. Fuentes, D. Ryu, H. Chung

Research output: Chapter in Book/Report/Conference proceedingConference PaperOther

15 Citations (Scopus)

Abstract

Climate models predict increased average temperatures and water scarcity in major agricultural regions of Australia over the coming decades. These changes will increase the pressure on vineyards to manage water and other resources more efficiently, without compromising their high quality grape production. Several studies have demonstrated that high-resolution visual/near-infrared (VNIR) vineyard maps acquired from unmanned aerial systems (UAS) can be used to monitor crop spatial variability and plant biophysical parameters in vineyards. However, manual segmentation of aerial images is time consuming and costly, therefore in order to efficiently assess vineyards from remote sensing data, automated tools are required to extract relevant information from vineyard maps. Generating vineyard maps requires separating vine pixels from non-vine pixels in order to accurately determine vine spectral and spatial information. Previously several image texture and frequency analysis methods have been applied to vineyard map generation, however these approaches require manual preliminary delineation of the vine fields. In this paper, an automated algorithm that uses skeletonisation techniques to reduce the complexity of agricultural scenes into a collection of skeletal descriptors is described. By applying a series of geometric and spatial constraints to each skeleton, the algorithm accurately identifies and segments each vine row. The algorithm presented here has been applied to a high resolution aerial orthomosaic and has proven its efficiency in unsupervised detection and delineation of vine rows in a commercial vineyard.

Original languageEnglish
Title of host publicationProceedings - 21st International Congress on Modelling and Simulation, MODSIM 2015
EditorsTony Weber, Malcolm McPhee, Robert Anderssen
PublisherModelling and Simulation Society of Australia and New Zealand Inc. (MSSANZ)
Pages1406-1412
Number of pages7
ISBN (Electronic)9780987214355
Publication statusPublished - 2015
EventInternational Congress on Modelling and Simulation 2015: Partnering with industry and the community for innovation and impact through modelling - Gold Coast Convention and Exhibition Centre, Broadbeach, Australia
Duration: 29 Nov 20154 Dec 2015
Conference number: 21st
https://web.archive.org/web/20150627050926/http://www.mssanz.org.au:80/modsim2015/
https://web.archive.org/web/20150626200712/http://mssanz.org.au:80/modsim2015/index.html

Conference

ConferenceInternational Congress on Modelling and Simulation 2015
Abbreviated titleMODSIM2015
CountryAustralia
CityBroadbeach
Period29/11/154/12/15
OtherThe 21st International Congress on Modelling and Simulation (MODSIM2015) was held at the Gold Coast Convention and Exhibition Centre, Broadbeach, Queensland, Australia from Sunday 29 November to Friday 4 December 2015.

It was held jointly with the 23rd National Conference of the Australian Society for Operations Research and the DSTO led Defence Operations Research Symposium (DORS 2015).

The theme for this event was Partnering with industry and the community for innovation and impact through modelling.

21st International Congress on Modelling and Simulation: Partnering with Industry and the Community for Innovation and Impact through Modelling, MODSIM 2015 - Held jointly with the 23rd National Conference of the Australian Society for Operations Research and the DSTO led Defence Operations Research Symposium, DORS 2015
Internet address

Keywords

  • Image processing
  • Photogrammetry
  • Precision viticulture

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