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

التفاصيل البيبلوغرافية
العنوان: Agriculture application with airborne hyperspectral images from two-dimensional concave grating system
المؤلفون: Ko, C.-H., Ren, H., Tsai, J.-R., Wang, B.-J., Lin, S.-F., Huang, C.-H., Hong, C.-T., Chiu, W.-H.
سنة النشر: 2019
المجموعة: National Taiwan University of Science and Technology Repository (NTUSTR) / 台灣科技大學
مصطلحات موضوعية: Airborne Hyperspectral Images, Back Propagation Neural Network (BPNN), Fully Constrained Least Squares (FCLS), Two-Dimensional Concave Grating
الوصف: 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. Copyright 2019 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.
نوع الوثيقة: conference object
وصف الملف: 101 bytes; text/html
اللغة: unknown
العلاقة: AIAA Scitech 2019 Forum; http://ir.lib.ntust.edu.tw/handle/987654321/79816Test; http://ir.lib.ntust.edu.tw/bitstream/987654321/79816/1/index.htmlTest
DOI: 10.2514/6.2019-1542
الإتاحة: https://doi.org/10.2514/6.2019-1542Test
http://ir.lib.ntust.edu.tw/handle/987654321/79816Test
http://ir.lib.ntust.edu.tw/bitstream/987654321/79816/1/index.htmlTest
رقم الانضمام: edsbas.A2E61B58
قاعدة البيانات: BASE