Abstract
Banana Fusarium wilt, also known as "banana cancer", currently poses a significant threat to banana production worldwide. Timely and accurate identification of Fusarium wilt disease is crucial for effective disease control and optimizing agricultural planting structure. To explore the use of unmanned aerial vehicle (UAV) remote sensing for identifying banana wilt disease, in this study, we obtained comprehensive experimental data on wilted banana plants in a banana plantation in Long'an County, Guangxi. The dataset includes UAV multispectral reflectance data and ground survey data on the incidence of banana wilt disease. The UAV multispectral imagery was acquired under clear, cloud-free, and well-illuminated weather conditions, at a flying altitude of 120 meters with a spatial resolution of 8 cm/pixel. The ground sample points survey on the occurrence of banana wilt disease was conducted using a high-precision handheld GPS unit to collect latitude and longitude information for each sample point, and the positions were matched with the corresponding center positions of banana plants in the UAV imagery indoors. The dataset provides high- spatial-resolution UAV multispectral imagery data and accurate ground sample point survey data. It can be applied in the research and monitoring of UAV remote sensing identification and surveillance of banana wilt disease. It plays a crucial role in advancing research and application of remote sensing monitoring for agricultural crop diseases.
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