Thai crops detection using the integration of multi-sensor remote sensing data and an RNN hierarchical algorithm

Noppadon Khiripet; Wongnaret Khantuwan; Li-Yu Chang; Yi-Yun Hsu

doi:10.1117/12.3040587

20 December 2024 Thai crops detection using the integration of multi-sensor remote sensing data and an RNN hierarchical algorithm

Noppadon Khiripet, Wongnaret Khantuwan, Li-Yu Chang, Yi-Yun Hsu

Author Affiliations +

Proceedings Volume 13266, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications VIII; 132660M (2024) https://doi.org/10.1117/12.3040587
Event: Asia-Pacific Remote Sensing, 2024, Kaohsiung, Taiwan

Conference Poster

Abstract

Sugarcane and paddy rice are stable food in Thailand, since they are significant cash crops for international trade. Currently the sugarcane and paddy rice investigation carried out by Thai government is in once per two-year period. However, due to the rapid change of farmers growing behavior and the needs of market, the field survey encounters low efficacy and accuracy. This research is supported under the joint project “Paddy Field Land Use Change Detection Using Data Cube’’ between Taiwan Space Agency (TASA) and National Electronics and Computer Technology Center (NECTEC) in Thailand.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Noppadon Khiripet, Wongnaret Khantuwan, Li-Yu Chang, and Yi-Yun Hsu "Thai crops detection using the integration of multi-sensor remote sensing data and an RNN hierarchical algorithm", Proc. SPIE 13266, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications VIII, 132660M (20 December 2024); https://doi.org/10.1117/12.3040587

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