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Remote Sens. 2014, 6(9), 8261-8286; doi:10.3390/rs6098261

Mapping Banana Plants from High Spatial Resolution Orthophotos to Facilitate Plant Health Assessment

1
Biophysical Remote Sensing Group, School of Geography, Planning and Environmental Management, The University of Queensland, Brisbane, QLD 4072, Australia
2
Trimble Geospatial, Arnulfstrasse 126, Munich 80636, Germany
3
Australian Banana Growers' Council Inc., South Gate East Commercial Centre, 250 Sherwood Road, Rocklea, QLD 4106, Australia
4
Peasley Horticultural Services, P.O. Box 542 Murwillumbah, NSW 2484, Australia
*
Author to whom correspondence should be addressed.
Received: 31 March 2014 / Revised: 21 August 2014 / Accepted: 22 August 2014 / Published: 2 September 2014
(This article belongs to the Special Issue Advances in Geographic Object-Based Image Analysis (GEOBIA))
View Full-Text   |   Download PDF [11857 KB, uploaded 2 September 2014]   |  

Abstract

The Banana Bunchy Top Virus (Genus: Babuvirus) reduces plant growth and prevents banana production. Because of the very large number of properties with banana plants in South East Queensland, Australia, a mapping approach was developed to delineate individual and clusters of banana plants to help plant identification and enable prioritization of plant inspections for Banana Bunchy Top Virus. Due to current outbreaks in South East Queensland, there are concerns that the virus may spread to the major banana growing districts further north. The mapping approach developed was based on very high spatial resolution airborne orthophotos. Object-based image analysis was used to: (1) detect banana plants using edge and line detection approaches; (2) produce accurate and realistic outlines around classified banana plants; and (3) evaluate the mapping results. The mapping approach was developed based on 10 image tiles of 1 km × 1 km and was applied to orthophotos (3600 image tiles) from September 2011 covering the entire Sunshine Coast Region in South East Queensland. Based on field inspections of the classified maps, a user’s mapping accuracy of 88% (n = 146) was achieved. The results will facilitate the detection of banana plants and increase the inspection rate of Banana Bunchy Top Virus in the future. View Full-Text
Keywords: banana plants; Banana Bunchy Top Virus; orthophotos; high spatial resolution; object-based image analysis; eCognition banana plants; Banana Bunchy Top Virus; orthophotos; high spatial resolution; object-based image analysis; eCognition
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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Johansen, K.; Sohlbach, M.; Sullivan, B.; Stringer, S.; Peasley, D.; Phinn, S. Mapping Banana Plants from High Spatial Resolution Orthophotos to Facilitate Plant Health Assessment. Remote Sens. 2014, 6, 8261-8286.

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