Agriculture application with airborne hyperspectral images from two-dimensional concave grating system

Cheng Hao Ko, Hsuan Ren, Jih Run Tsai, Bang Ji Wang, Shin Fa Lin, Chih Hsuan Huang, Chi Tsung Hong, Wei Huai Chiu

研究成果: 書貢獻/報告類型會議論文篇章同行評審

3 引文 斯高帕斯(Scopus)


Hyperspectral imaging spectrometers have been extensively researched in the past a few decades. They can measure electromagnetic energy in their instantaneous field of view in hundreds of wavelengths. With such high spectral resolution less than 10 nanometers, it is possible to distinguish materials of subtle difference in spectrum. Recently, a two-dimensional concave grating hyperspectral spectrometer has been developed under the support of National Space Organization in Taiwan. This airborne system is integrated with two subsystems of visible-near infrared (VNIR) and short-wave infrared (SWIR) bands with 3.5 and 10 nanometers spectral resolution respectively. With the design fly altitude of 2000 meters, the spatial resolution is about 70 cm. In this study, linear and nonlinear classification methods of Fully Constrained Least Squares (FCLS) and Back Propagation Neural Network (BPNN) for agriculture crops are discussed. Based on the ground truth, four crops are selected in the study site, including chives, broccoli, rape and pea. The experimental results indicate the classification accuracy of BPNN can exceed 90% and outperforms classification results of FCLS.

主出版物標題AIAA Scitech 2019 Forum
發行者American Institute of Aeronautics and Astronautics Inc, AIAA
出版狀態已出版 - 2019
事件AIAA Scitech Forum, 2019 - San Diego, United States
持續時間: 7 1月 201911 1月 2019


名字AIAA Scitech 2019 Forum


???event.eventtypes.event.conference???AIAA Scitech Forum, 2019
國家/地區United States
城市San Diego


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