人類對於地球資源的過度開發造成自然生態的急驟變化，使得我們的生活環境更為脆弱。環境變遷所造成的災害往往產生無法彌補的人力及財物損失，因此如何透過變遷分析(Change Detection)之手段，有效監控環境之變化，以促進人類與自然環境之永續發展，已成為產官各界所致力研究之課題。在全球意識高漲及空間資訊科技快速發展下，透過跨國及跨領域共享機制的建立，各領域研究人員將可在協同合作之運作方式下，對全球環境變化進行更有效之監控。然而，在共享機制逐漸成熟、空間資源大量累積、資源更易取得的環境下，分析者雖可享科技帶來之便，另一方面卻也勢必面對如何從「多元」與「巨量」資料的共享環境中找尋合適分析資料之挑戰。以變遷分析之觀點而言，分析者對於資料掌握的程度，更是決定分析成果是否正確之成敗因素。本研究結合「標準化詮釋資料」與「變遷分析知識」，提出一套創新之詮釋資料導向變遷偵測運作機制，針對變遷分析之「資料搜尋」部分，自動化產生基於變遷任務需求之資料搜尋條件，提升變遷資料搜尋上之精準度與效率。而在「變遷分析」部分，藉由引入變遷分析中所必要參考之資訊，並依據變遷分析任務之需求，設計資料風險評估之機制與品質感知之分析環境，提示分析者所採用資料可能帶有之風險，進而提升變遷偵測在決策分析上之正確性。
本研究以三類變遷偵測類型為例(移位型、幾何型、數量型)，分析各類型所需之條件及可供描述之標準化詮釋資料項目，並針對各類型之變遷分析需求設計資料搜尋之機制與品質感知之分析介面，成功驗證以標準化詮釋資料輔助領域應用需求之可行性。本研究提出標準化詮釋資料結合領域知識之概念，除能提升資料在變遷分析應用上之共享效益，亦可應用至其他領域。本研究除廣泛拓展詮釋資料之應用層面外，對於巨量資料與雲端技術(Cloud Computing)之應用以及未來智慧型決策系統之發展亦提供嶄新之觀點。

The environmental changes caused by the overexploitation have resulted in the loss of economy and human life. To effectively monitor these changes for sustainable developments between human and the Nature has aroused a widespread attention. As the environmental awareness and the Geospatial Technology rises, the analysts from various fields monitor the global environmental changes more effectively through an international and interdisciplinary framework. Although the analysts take advantages of geo-resources from the sharing environment, it remains a challenge for an analyst to select “right” data in such a “Variety” and “Big Data” environment. It is essential that the analysts must have a complete understanding of the data for making correct decisions. This research proposes an innovative metadata-driven framework which integrates the “standardized metadata” and “knowledge of change detection” to assist the search and application of change detection tasks. According to the automatically generated searching constraints with the concerns of change detection knowledge, both the precision and efficiency of the data search can be promoted. Meanwhile, by designing a quality-aware mechanism based on the change detection knowledge, an informative analysis environment can be proposed to warn the analysts the risks so as to improve the correctness of the results.
In this research, we select three types of change detection task: deformation, geometry change, and number change, to analyze the requirements of each task and provides the applicable metadata elements correspondingly. Besides, the intelligent searching mechanism and quality-aware analysis environment are developed for different kinds of the change detection tasks. This research successfully validates the feasibility of utilizing the standardized metadata in other applications. The concept of integrating standardized metadata with domain knowledge not only encourages the benefits of the change detection tasks sharing, but also can be applied in other specific applications. In addition to widen the application of the standardized metadata, the proposed framework provides a novel prospect toward the application of Cloud Computing, Big Data, and the intelligent Decision Support Systems for the future.

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