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| 題 名 | 基於人工智慧分類法之無人機影像在精準農業中的應用:以臺灣宜蘭縣部分鄉鎮的水稻田坵塊分類為例=Application of UAV Imagery in Precision Agriculture Based on Artificial Intelligence Classification Methods: A Case Study of Paddy Fields in Selected Townships of Yilan County, Taiwan |
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| 作 者 | 沈育璋; 雷祖強; 陳勝義; | 書刊名 | 航測及遙測學刊 |
| 卷 期 | 30:2 2025.06[民114.06] |
| 頁 次 | 頁123-137 |
| 分類號 | 312.831 |
| 關鍵詞 | 精準農業; 水稻田; 機器學習; 深度學習; UAV影像; Precision agriculture; Paddy fields; Machine learning; Deep learning; UAV imagery; |
| 語 文 | 中文(Chinese) |
| DOI | 10.6574/JPRS.202506_30(2).0004 |
| 中文摘要 | 隨著無人機與影像分析技術進步,精準農業逐漸成為提升農業效率的關鍵,本研究使用高解析度UAV影像並比較三種機器學習與深度學習模型於宜蘭縣水稻田坵塊偵測問題。機器學習模型如倒傳神經網路、羅吉斯迴歸與C5.0決策樹利用原始波段與紋理特徵,最佳精度為倒傳神經網路(總體精度95.62%、Kappa值0.912);而深度學習模型為Alexnet、VGG16、VGG19同樣利用原始波段與影像增揚特徵後,最佳精度為VGG16(總體精度93.83%、Kappa值0.894)。雖然機器學習部分工具精準度略高,但其需依賴繁瑣特徵工程才能達成目的,反之深度學習只需要原始波段加入簡單影像增揚特徵後就能產生一定程度的判釋結果,這顯示圖像式(2D)CNN在地物判釋上的優越性,其在農業環境調查中具有高度的應用潛力。 |
| 英文摘要 | With the advancement of UAV and image analysis technologies, precision agriculture has become a key strategy for enhancing productivity. This study uses high-resolution UAV imagery to evaluate three machine learning and three deep learning models for detecting rice paddy plots in Yilan County, Taiwan. Among the machine learning models (BPNN, logistic regression, and the C5.0 decision tree), the BPNN performed best, achieving 95.62% accuracy and a Kappa coefficient of 0.912. In the deep learning category (AlexNet, VGG16, and VGG19), VGG16 yielded the highest performance with 93.83% accuracy and a Kappa of 0.894 using RGB bands and basic enhancements bands. Although certain machine learning models demonstrated slightly higher accuracy, they required complex and time-consuming feature engineering. In contrast, deep learning models produced competitive interpretation results using only RGB bands and simple enhancement techniques. These findings demonstrate the superior capability of image-based (2D) convolutional neural networks (CNNs) in land cover interpretation and highlight their strong potential for application in agricultural environmental surveys. |
本系統中英文摘要資訊取自各篇刊載內容。