Using GeoEye-1 Imagery for Multi-Temporal Object-Based Detection of Canegrub Damage in Sugarcane Fields in Queensland, Australia

Handle URI:
http://hdl.handle.net/10754/626594
Title:
Using GeoEye-1 Imagery for Multi-Temporal Object-Based Detection of Canegrub Damage in Sugarcane Fields in Queensland, Australia
Authors:
Johansen, Kasper; Sallam, Nader; Robson, Andrew ( 0000-0001-5762-8980 ) ; Samson, Peter; Chandler, Keith; Derby, Lisa; Eaton, Allen; Jennings, Jillian
Abstract:
The greyback canegrub (Dermolepida albohirtum) is the main pest of sugarcane crops in all cane-growing regions between Mossman (16.5°S) and Sarina (21.5°S) in Queensland, Australia. In previous years, high infestations have cost the industry up to $40 million. However, identifying damage in the field is difficult due to the often impenetrable nature of the sugarcane crop. Satellite imagery offers a feasible means of achieving this by examining the visual characteristics of stool tipping, changed leaf color, and exposure of soil in damaged areas. The objective of this study was to use geographic object-based image analysis (GEOBIA) and high-spatial resolution GeoEye-1 satellite imagery for three years to map canegrub damage and develop two mapping approaches suitable for risk mapping. The GEOBIA mapping approach for canegrub damage detection was evaluated over three selected study sites in Queensland, covering a total of 254 km2 and included five main steps developed in the eCognition Developer software. These included: (1) initial segmentation of sugarcane block boundaries; (2) classification and subsequent omission of fallow/harvested fields, tracks, and other non-sugarcane features within the block boundaries; (3) identification of likely canegrub-damaged areas with low NDVI values and high levels of image texture within each block; (4) the further refining of canegrub damaged areas to low, medium, and high likelihood; and (5) risk classification. The validation based on field observations of canegrub damage at the time of the satellite image capture yielded producer’s accuracies between 75% and 98.7%, depending on the study site. Error of commission occurred in some cases due to sprawling, drainage issues, wind, weed, and pig damage. The two developed risk mapping approaches were based on the results of the canegrub damage detection. This research will improve decision making by growers affected by canegrub damage.
KAUST Department:
Biological and Environmental Sciences and Engineering (BESE) Division; Water Desalination and Reuse Research Center (WDRC)
Citation:
Johansen K, Sallam N, Robson A, Samson P, Chandler K, et al. (2017) Using GeoEye-1 Imagery for Multi-Temporal Object-Based Detection of Canegrub Damage in Sugarcane Fields in Queensland, Australia. GIScience & Remote Sensing: 1–21. Available: http://dx.doi.org/10.1080/15481603.2017.1417691.
Publisher:
Informa UK Limited
Journal:
GIScience & Remote Sensing
Issue Date:
18-Dec-2017
DOI:
10.1080/15481603.2017.1417691
Type:
Article
ISSN:
1548-1603; 1943-7226
Sponsors:
Funding for this work was provided by Sugar Research Australia. Significant input and field assistance were provided by cane growers, productivity services, and mills from each of the three regions.
Additional Links:
http://www.tandfonline.com/doi/full/10.1080/15481603.2017.1417691
Appears in Collections:
Articles; Water Desalination and Reuse Research Center (WDRC); Biological and Environmental Sciences and Engineering (BESE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorJohansen, Kasperen
dc.contributor.authorSallam, Naderen
dc.contributor.authorRobson, Andrewen
dc.contributor.authorSamson, Peteren
dc.contributor.authorChandler, Keithen
dc.contributor.authorDerby, Lisaen
dc.contributor.authorEaton, Allenen
dc.contributor.authorJennings, Jillianen
dc.date.accessioned2018-01-01T12:19:01Z-
dc.date.available2018-01-01T12:19:01Z-
dc.date.issued2017-12-18en
dc.identifier.citationJohansen K, Sallam N, Robson A, Samson P, Chandler K, et al. (2017) Using GeoEye-1 Imagery for Multi-Temporal Object-Based Detection of Canegrub Damage in Sugarcane Fields in Queensland, Australia. GIScience & Remote Sensing: 1–21. Available: http://dx.doi.org/10.1080/15481603.2017.1417691.en
dc.identifier.issn1548-1603en
dc.identifier.issn1943-7226en
dc.identifier.doi10.1080/15481603.2017.1417691en
dc.identifier.urihttp://hdl.handle.net/10754/626594-
dc.description.abstractThe greyback canegrub (Dermolepida albohirtum) is the main pest of sugarcane crops in all cane-growing regions between Mossman (16.5°S) and Sarina (21.5°S) in Queensland, Australia. In previous years, high infestations have cost the industry up to $40 million. However, identifying damage in the field is difficult due to the often impenetrable nature of the sugarcane crop. Satellite imagery offers a feasible means of achieving this by examining the visual characteristics of stool tipping, changed leaf color, and exposure of soil in damaged areas. The objective of this study was to use geographic object-based image analysis (GEOBIA) and high-spatial resolution GeoEye-1 satellite imagery for three years to map canegrub damage and develop two mapping approaches suitable for risk mapping. The GEOBIA mapping approach for canegrub damage detection was evaluated over three selected study sites in Queensland, covering a total of 254 km2 and included five main steps developed in the eCognition Developer software. These included: (1) initial segmentation of sugarcane block boundaries; (2) classification and subsequent omission of fallow/harvested fields, tracks, and other non-sugarcane features within the block boundaries; (3) identification of likely canegrub-damaged areas with low NDVI values and high levels of image texture within each block; (4) the further refining of canegrub damaged areas to low, medium, and high likelihood; and (5) risk classification. The validation based on field observations of canegrub damage at the time of the satellite image capture yielded producer’s accuracies between 75% and 98.7%, depending on the study site. Error of commission occurred in some cases due to sprawling, drainage issues, wind, weed, and pig damage. The two developed risk mapping approaches were based on the results of the canegrub damage detection. This research will improve decision making by growers affected by canegrub damage.en
dc.description.sponsorshipFunding for this work was provided by Sugar Research Australia. Significant input and field assistance were provided by cane growers, productivity services, and mills from each of the three regions.en
dc.publisherInforma UK Limiteden
dc.relation.urlhttp://www.tandfonline.com/doi/full/10.1080/15481603.2017.1417691en
dc.subjectgeographic object-based image analysisen
dc.subjectDermolepidaen
dc.subjectSugarcaneen
dc.subjectgeoeye-1en
dc.subjectQueensland Australiaen
dc.subjectdamage mappingen
dc.titleUsing GeoEye-1 Imagery for Multi-Temporal Object-Based Detection of Canegrub Damage in Sugarcane Fields in Queensland, Australiaen
dc.typeArticleen
dc.contributor.departmentBiological and Environmental Sciences and Engineering (BESE) Divisionen
dc.contributor.departmentWater Desalination and Reuse Research Center (WDRC)en
dc.identifier.journalGIScience & Remote Sensingen
dc.contributor.institutionDepartment of Agriculture and Water Resources, 114 Catalina Crescent, Cairns Airport, Cairns QLD 4870, Australiaen
dc.contributor.institutionPrecision Agriculture Research Group, School of Science and Technology, University of New England, Armidale, NSW 2351, Australiaen
dc.contributor.institutionSugar Research Australia, 50 Meiers Road, Indooroopilly, QLD 4068, Australiaen
dc.contributor.institutionSugar Research Australia, 26135 Peak Downs Highway, Te Kowai QLD 4741, Australiaen
dc.contributor.institutionSugar Research Australia, 71378 Bruce Highway, Gordonvale QLD 4865, Australiaen
dc.contributor.institutionSugar Research Australia, 26135 Peak Downs Highway, Te Kowai, QLD 4741, Australiaen
kaust.authorJohansen, Kasperen
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