Abstract
Bananas are the world’s most popular fruit and an important staple food source. Recent outbreaks of Panama TR4 disease are threatening the global banana industry, which is worth an estimated $8 billion. Current methods to map land uses are time- and resource-intensive and result in delays in the timely release of data. We have used existing land use mapping to train a U-Net neural network to detect banana plantations in the Wet Tropics of Queensland, Australia, using high-resolution aerial photography. Accuracy assessments, based on a stratified random sample of points, revealed the classification achieves a user’s accuracy of 98% and a producer’s accuracy of 96%. This is more accurate compared to existing (manual) methods, which achieved a user’s and producer’s accuracy of 86% and 92% respectively. Using a neural network is substantially more efficient than manual methods and can inform a more rapid respond to existing and new biosecurity threats. The method is robust and repeatable and has potential for mapping other commodities and land uses which is the focus of future work.
Highlights
The aim of this study is to demonstrate that using a convolutional neural network and high-resolution imagery (
It consists of two parts: (i) An encoding this study, we aimed to classify of every pixel images; in the image or non-banana plantation stageIn that downsamples the resolution the input and, as (ii)banana a decoding stage that upsamples through semantic segmentation using a convolutional neural
We found the QLUMP banana plantation classification had a user’s and producer’s accuracy of 0.862 and 0.921 respectively and the U-Net banana plantation classification had a user’s and producer’s accuracy of 0.983 and 0.959 respectively (Table 1)
Summary
Panama TR4, a form of fusarium wilt that eventually kills infected banana plants [1,2]. Since the 1980s, Foc TR4 has been regarded as the most important biosecurity threat to the global banana industry, and an unparalleled botanical epidemic [2], persisting indefinitely in the soil with no effective control method. The disease can spread anthropogenically and naturally through the transportation of infected plant material, soil, and water [5]. Bananas are the world’s most popular fruit and an important staple food [6], with a global industry worth $8 billion annually [7]. The potential impact of Panama TR4 is severe, because Cavendish accounts for approximately 47% of bananas produced globally, predominantly sourced from Asia, Latin America, and Africa [7]
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