稻米為亞洲地區的主要糧食，因此水稻田清點及稻作產量預估為農政單住之重要任務之一。近年已使用遙測技術於稻作辨識，配合航空照片判釋稻作面積、進行航測耕地圖之建置等工作。調查後之成果逐年累積，卻缺乏後續通盤的規劃與管理，本研究重點在於將稻作調查資料加入時間觀點之考量，並整合至地理資訊系統中，藉由資料隨時間的變化作為變遷研究或農糧決策之參考。

　　本研究透過地理資訊系統(GIS)與資料庫之結合，依稻作調查資料之特性加入時間觀點之考量，設計三種不同管理架構：(1)單一空間圖層模式；(2)多重空間圖層模式；(3)時間差異模式。同時依其特性設計時間管理模式與操作機制，提供維持現況、回復特定期別狀態及記錄耕地變遷之功能。研究結果顯示單一空間圖層模式簡單直接的架構降低資料計算之處理量，但卻無法在空間範圍上顯示改變；多重空間圖層模式可完整顯示每個時期不同之耕種狀況，但其資料計算量十分龐大；時間差異模式精簡了資料量，並能回復至多重空間圖層模式架構，顯示各期別耕種之狀態。

　　研究結果驗證管理稻作調查資料加入時間因素之可行性，並可提供對過去與現況資料之查詢與分析，以作為稻作耕種習慣與區域變遷之分析基礎。加入時間觀點之稻作調查資料管理後，有助於農政單位之相關政策裁定與相關資料之掌控，此對目前國內稻作管理之資訊化無疑有正面之效益。

　　Rice is the major food to most people in Asia. Rice inventory is therefore the important reference data for the agricultural organizations and institutions to predict and control the production of rice harvest. Remote sensing images and aerial photographs have been used for the rice inventory interpretation for many years. Though the interpretation result steadily accumulates over the years, a well-organized management mechanism over the rice inventory database has not been fully developed yet. The major goal of this research is to introduce a spatio-temporal perspective towards the management of interpretation result. Such a mechanism is capable of providing supports to numerous agricultural organizations task, such as the change detection and policy making.

　　Based on the spatial and temporal nature of rice inventory data, three temporal database models are proposed: (l) single map coverage model; (2) multiple map coverage model; (3) time difference model. The developed mechanism must allow both spatial and temporal queries towards the historical database. The result indicates all of 3 model systems are feasible. Single map coverage model simplifies the data structure, but can only provide analysis based on attribute values. Multiple map coverage model can completely monitor all the conditions, but data volume may be overwhelming. Time difference model reduces the amount of stored data by only recoding the difference between two epochs, and in the meantime can still meet historical query demands.

　　This study shows it is beneficial and achievable to handle the paddy-recognized data by introducing temporal data models. Though there are still factors like efficiency and distribution mechanism, yet the result has established a solid foundation to the spatio-temporal management and analysis of rice inventory data.

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