近年來全球商用遙控無人機系統之相關系統軟、硬體技術發展已日趨成熟，以遙控無人機應用於農業病蟲害防治及獲取可見光（如紅、藍、綠光 ）與不可見光（紅光邊緣與近紅外光）影像方法的可行性與可靠度大幅提高，其方法具備了高機動性、即時性、低操作成本、可減少非必要之人員風險等優點。產學界藉由分析高光譜相機所拍攝得的各種波長影像，已推導出超過55種植生指標，可應用於推廣智慧農業、農作物性狀調查與病蟲害評估等需求，因此將遙控無人機系統搭載多光譜/高光譜相機是一可行的高效率作物監測方案。
本論文的研究重點因而在於如何落實將無人機系統的優點應用在輔助大型農場作物的防疫與監測應用，快速精準的定位出現病徵的農作物範圍，協助農場管理者優化日常管理檢測作業，提供一個事前預防、事後防治的高效率輔助作業，回饋遙控無人機農噴任務派工決策系統，為農場管理者提供一個有效降低經營成本的智慧型農業科技方案。

In recent years, the development of software and hardware technology of the relevant systems of commercial remote-controlled UAV systems in the world has become more and more mature, and therefore the feasibility and reliability of the imaging methods of remote-controlled drones for agricultural pest control and acquisition of visible light (such as red, blue, green light) and invisible light (red light edge and near-infrared light) have been greatly improved. By analyzing the various wavelength images taken by hyperspectral cameras, the industry has deduced more than 55 planting indicators that can be applied to the needs of promoting intelligent agriculture, crop trait survey and pest assessment, so it is a feasible and efficient crop monitoring program to carry a remote-controlled drone system with a multispectral/hyperspectral camera.
In this thesis, we propose ways to utilize the advantages of the UAV system in assisting large farm crops in epidemic prevention and monitoring applications, rapid and accurate positioning of disease-related crop range, to help farm managers optimize daily management testing operations, to provide a pre-prevention, after-the-fact prevention and control of high-efficiency auxiliary operations, to feedback remote-controlled drone task dispatch decision-making system, and to provide an effective smart farming solution to help farmer reduce the costs.

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