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自發性地理資訊品質評估探討-蝴蝶VGI案例分析

Quality Assessment of VGI Data- A Volunteered Butterfly Data Case Study

摘要


自發性地理資訊(volunteered geographic information, VGI)是近年地理資訊科學(geographic information science, GISc)發展的新研究方向,它是基植於空間定位技術及第二代互動網路架構(Web 2.0)的蓬勃發展,同時兼具技術面及社會面的議題,然VGI多由非專業者所產製,以致品質問題成為相關資料應用之關鍵。本研究以農委會特有生物研究保育中心於2010年間,透過競賽活動所蒐集之蝴蝶VGI資料為基礎,選取其中的青鳳蝶與大鳳蝶為對象,利用專家資料與基因演算(genetic algorithm for rule-set prediction,GARP)物種分布模式(speciesdistribution model)進行物種棲地的分布預測,進而探討志工與民眾所提供的資料品質狀況,提出生態性VGI資料的品質檢核方法。研究結果顯示以基因演算法的物種分布模式來檢核生態性VGI資料的品質是一個適當的方法,惟模式中的適當切點值(cut point)與距離誤差容忍值的決定是影響檢核結果的關鍵,本研究也經由大鳳蝶與青鳳蝶的案例,提出系統性的決定方法,包括:透過與專家資料的檢核比對,選擇適當切點值與距離誤差值。就本研究的蝴蝶VGI資料而言,其與專家資料為基礎的分布預測結果吻合度極高,其正確率分別達94%(青鳳蝶)與96%(大鳳蝶),顯示這些蝴蝶志工確實可以與專業的生物學家形成蝴蝶調查的互補作用,並可充實現有的資料庫內容,並進一步再優化預測模式,形成一良性的資料處理程序。

並列摘要


Recently, there has been considerable interest concerning volunteered geographic information (VGI) in the discipline of geography and geographic information science (GIS). This study aims to establish a VGI data assessment and filtering method by integrating GIS and species distribution modeling. The distribution of volunteered butterfly data of Graphium sarpedon connectens and Papilio memnon heronus is the focus of this study. Results indicate that integration of the distribution modeling technique with the GIS analysis provides a sound analysis for a volunteered ecological data assessment. The results also indicate that high quality volunteered butterfly data exits. The accuracy rates are 94% and 96% for Graphium sarpedon connectens and Papilio memnon heronus, respectively. This implies that volunteers can be a supplement to professionals.

參考文獻


黃美秀、吳尹仁、姚中翎、李培芬、王穎、吳海音(2009)。台灣黑熊棲息地利用及分布預測模式。特有生物研究。11(2),1-20。
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