| Summary: | 碩士 === 嶺東科技大學 === 資訊管理系碩士班 === 105 === The UAV are widely applied to agriculture to collect the image data which become an important technique. However, how to analyze those Big-data is a tough and hard works. Conventionally, the classification focused on a single item such as paddy rice. This goal of this study is to help the image data company- Chung Hsin to analyze the multi-category image data of Golden Galley of Chia Yi. To improve the classification results, this study adopt (1) texture information: Contrast and Energy (2)vegetation index: Normalized Difference Vegetation Index (NDVI) and Modified Soil adjusted vegetation index, (SAVI). On the other hand, an apporach of this study is to observe the classification performance difference of classifier: Support Vector Machine, (SVM) and Back Propagation Neural Network, (BPN). The error matrix is computed and the thematic map of detail areas are drawn. All the control parameters is shown for discrepancy.
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