Mr. Huan-Chun Wang Profile

Huan-Chun Wang

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Proceedings Article | 21 December 2024 Paper

Satellite image monitoring and warning notification for Panama disease of banana in Central America

Li-Yu Chang, Hong-Jyun Jhu, Huan-Chun Wang, Hsuan-Cheng Wei, Kun-Mu Cheng

Proceedings Volume 13266, 132660C (2024) https://doi.org/10.1117/12.3041597

KEYWORDS: Satellites, Diseases and disorders, Satellite imaging, Earth observing sensors, Crop monitoring, Image processing, Vegetation, Statistical analysis, Image resolution, Data modeling

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Central America is one of the major regions for banana cultivation. However, due to the most of banana trees in this area are never infected by Panama disease, the major species of banana trees in Central America are still not Panama disease resistant and highly vulnerable to the threat of the disease. This disease causes yellowing, wilting, and reduced yield in banana plants, resulting in significant impacts on farmers' income and the economy of the region. In this study, Taiwan Space Agency (TASA) and the International Cooperation and Development Found (TaiwanICDF) are collaborated to develop an effective monitoring and early warning system to cope with this issue and a multi-temporal satellite image cloud storage and processing platform, as known as Taiwan Data Cube (TWDC), has been utilized. The platform majorly enables regular analysis process of satellite imagery from Formosat-5 and Sentinel-2 satellites and delivery of corresponding analyzed results to local users. These high-resolution images provide valuable surface observation data in assessing the health status of banana plants and tracking disease development trends. The project has established 15 monitoring areas in Guatemala and six in Belize, covering a total area of 200 hectares. The research demonstrates the feasibility of utilizing satellite data for large-scale plant disease monitoring and a successful collaboration with the Taiwan Technical Mission groups of TaiwanICDF in Central American. This development provides valuable information to farmers and disease control authorities, facilitating more effective disease monitoring and management practices.

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