Case Study on the Strategy of Multivariate Classification with Hyperspectral Image–A Case of Golden Agricultural Corridor

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...

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Main Authors: CHEN, WEI, 陳瑋
Other Authors: WAN,SHIUAN
Format: Others
Language:zh-TW
Published: 2017
Online Access:http://ndltd.ncl.edu.tw/handle/3n35j7
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spelling ndltd-TW-105LTC003950052019-05-15T23:32:17Z http://ndltd.ncl.edu.tw/handle/3n35j7 Case Study on the Strategy of Multivariate Classification with Hyperspectral Image–A Case of Golden Agricultural Corridor 多元分類在高光譜影像的策略研究:以黃金廊道為例 CHEN, WEI 陳瑋 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. WAN,SHIUAN CHANG, SHIH-HSUN 萬絢 張士勳 2017 學位論文 ; thesis 88 zh-TW
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language zh-TW
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description 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.
author2 WAN,SHIUAN
author_facet WAN,SHIUAN
CHEN, WEI
陳瑋
author CHEN, WEI
陳瑋
spellingShingle CHEN, WEI
陳瑋
Case Study on the Strategy of Multivariate Classification with Hyperspectral Image–A Case of Golden Agricultural Corridor
author_sort CHEN, WEI
title Case Study on the Strategy of Multivariate Classification with Hyperspectral Image–A Case of Golden Agricultural Corridor
title_short Case Study on the Strategy of Multivariate Classification with Hyperspectral Image–A Case of Golden Agricultural Corridor
title_full Case Study on the Strategy of Multivariate Classification with Hyperspectral Image–A Case of Golden Agricultural Corridor
title_fullStr Case Study on the Strategy of Multivariate Classification with Hyperspectral Image–A Case of Golden Agricultural Corridor
title_full_unstemmed Case Study on the Strategy of Multivariate Classification with Hyperspectral Image–A Case of Golden Agricultural Corridor
title_sort case study on the strategy of multivariate classification with hyperspectral image–a case of golden agricultural corridor
publishDate 2017
url http://ndltd.ncl.edu.tw/handle/3n35j7
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