使用地圖融合方法檢核數值地圖之異動

Detection of Feature Changes in Cartographic Data By Map Conflation Approach

數值圖的建立需耗費大量的時間與金錢。隨著地物變遷與人為經建活動，未更新的地圖將不再反應現況，以致降低使用價值。傳統的地圖更新方式使用人工方式全面性的檢核地物異動情況並取得更新資料，因需要涉及大量人工與龐大的經費，使得地圖的更新總趕不上地物的變遷。此外，使用人工方式檢核地物的異動也容易發生錯誤。本文提出使用同一地區不同來源的數值地圖資料，以地圖融合技術自動化檢核地物異動的變通方法。根據此方法，本研究並開發一個原型的地圖融合更新系統，以驗證地圖融合技術可有效率地實施數值地圖的異動檢核工作。 The acquisition of digital maps is very costly and time consuming. With topographic feature changes and the course of human events, maps that lack of updated will not truly reflect current status of the terrain and reduce its value. As traditional map updating method checks feature changes comprehensively and collects new data globally, it requires a lot of labor involved and tremendous expenditure. As a result, the map updating will not always catch up with feature changes. In addition, checking feature changes manually is error-prone. This paper proposes an alternative approach to check feature changes automatically by map conflation technique, utilizing different sources of map data in the same area. Based on this approach, a prototyped Map Conflation and Updating System (MCUS) is developed to demonstrate that the detection of feature changes in digital maps can be fulfilled efficiently.

The acquisition of digital maps is very costly and time consuming. With topographic feature changes and the course of human events, maps that lack of updated will not truly reflect current status of the terrain and reduce its value. As traditional map updating method checks feature changes comprehensively and collects new data globally, it requires a lot of labor involved and tremendous expenditure. As a result, the map updating will not always catch up with feature changes. In addition, checking feature changes manually is error-prone. This paper proposes an alternative approach to check feature changes automatically by map conflation technique, utilizing different sources of map data in the same area. Based on this approach, a prototyped Map Conflation and Updating System (MCUS) is developed to demonstrate that the detection of feature changes in digital maps can be fulfilled efficiently.