本研究以MODIS/TERRA影像衍算之常態化差異植被指數與增強植被指數，建立每16天一張全年共23張影像之時間序列資料庫。依據常態化差異植被指數與增強植被指數探討臺灣六種主要的土地覆蓋類型（闊葉林、針葉林、混合林、旱作、稻作與都市）在時間序列剖面上的變化，並比較常態化差異植被指數與增強植被指數是否適用於臺灣的環境。經比較後發現，常態化差異植被指數較增強植被指數適用於臺灣。此外，稻作的常態化差異植被指數時間序列剖面可觀察到清楚的事節性變動，有兩個明顯起伏的波峰型態，未來可應用在其判釋與監測上。闊葉林、針葉林與混合林的常態化差異植被指數時間序列剖面全年變化幅度小、數值穩定。然而，使用常態化差異植被指數仍需注意，未來應持續建立更完整的多年份時間序列資料庫，用以探討年間與年際變化。建議變遷與監測的系統化研究可採用MODIS或其他中尺度的衛星影像（如AVHRR），可提供土地覆蓋在當地尺度較完整的空間特性與相關資料。
Remotely sensed measurements from MODIS/TERRA expressed as normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) have generated a 23-half-monthly time series appropriate for short-term studies of Taiwan. The land cover types observed included broadleaf forest, coniferous forest, mixed forest, dry cropland, paddy field, and urban area. Comparison of time series profiles (TSP) between NDVI and EVI shows that NOVI is more appropriate than EVI for the land cover/use studies in Taiwan. We found that half-monthly NOVI composites revealed seasonality in paddy fields, which can be used in their identification, whilst the phenology of other forest cover types varies little throughout the year. These results indicate the potential use of multi-temporal NOVI data for the environmental characterization and identification of land cover types, especially of forests and paddy fields. However, these data have to be used with a degree of caution. We will need to build the time series database of NDVI for land cover types in Taiwan to find out annual and inter-annual variations of NOVI TSP. Systematic studies of changes and monitoring on the landscape using moderate spatial resolution satellite data sets such as those from AVHRR and MODIS will provide a detailed spatial quantification and description of land cover types at local scale.
