Please use this identifier to cite or link to this item:
https://hdl.handle.net/1959.11/23037
Title: | Using GeoEye-1 Imagery for Multi-Temporal Object-Based Detection of Canegrub Damage in Sugarcane Fields in Queensland, Australia | Contributor(s): | Johansen, Kasper (author); Sallam, Nader (author); Robson, Andrew (author) ; Samson, Peter (author); Chandler, Keith (author); Derby, Lisa (author); Eaton, Allen (author); Jennings, Jillian (author) | Publication Date: | 2018 | DOI: | 10.1080/15481603.2017.1417691 | Handle Link: | https://hdl.handle.net/1959.11/23037 | 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. | Publication Type: | Journal Article | Source of Publication: | GIScience and Remote Sensing, 55(2), p. 285-305 | Publisher: | Taylor & Francis | Place of Publication: | United Kingdom | ISSN: | 1943-7226 1548-1603 |
Fields of Research (FoR) 2008: | 070108 Sustainable Agricultural Development 070107 Farming Systems Research 070302 Agronomy |
Fields of Research (FoR) 2020: | 300210 Sustainable agricultural development 300403 Agronomy |
Socio-Economic Objective (SEO) 2008: | 960403 Control of Animal Pests, Diseases and Exotic Species in Farmland, Arable Cropland and Permanent Cropland Environments 820304 Sugar |
Socio-Economic Objective (SEO) 2020: | 180602 Control of pests, diseases and exotic species in terrestrial environments 260607 Sugar |
Peer Reviewed: | Yes | HERDC Category Description: | C1 Refereed Article in a Scholarly Journal |
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Appears in Collections: | Journal Article School of Science and Technology |
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