本研究利用衛星遙測資料對河口及海洋環境進行研究，衛星遙測比起傳統的船測，在收集資料上能得到時間上較連續且空間上較廣泛的資訊，也不需要大量的人力及經費。
在河口研究上，我們選用的是2005年期間14幅蘭陽溪口SPOT衛星影像，利用影像分類法最大似然分類法，推得蘭陽溪口水舌在影像中分佈的情形及範圍。我們推測水舌分佈的範圍應會受到流量大小的影響，因此將所推算出來的水舌分佈的範圍與蘭陽溪流量做線性關係，我們發現的水舌分佈的範圍與蘭陽溪前二日累積流量有最佳的相關性 ， ，顯示出兩者具有高度相關性。最後利用實際觀測的海流資料做為佐證，其水團移動方向與所推得的水舌分佈的情形相符合，顯示此方法所得之水舌有其可信度。
並且為了瞭解蘭陽溪口之水舌分佈實際情形及水文特性，我們在2011年10月8日，於蘭陽溪外海進行船測採樣。我們推測低鹽度水團分佈情形應與遙測之淡水舌分佈情形相似，因此，利用宜蘭縣雨量模擬蘭陽溪流量資料，將遙測結果之淡水舌面積與蘭陽溪前二日累積流量迴歸關係，代入流量及船測資料，推算出淡水舌面積應為鹽度低於29.4 psu之範。利用船測照片做為佐證，從照片中可以觀察到在利用鹽度所定出之水舌範圍內，海水較混濁，而在水舌之範圍外海水較清澈。
在大洋研究上，我們利用MODIS及SeaWiFS衛星資料，建立一組長達14年在SEATS測站之葉綠素a濃度時序資料，並且以風速資料做為比較。從葉綠素a濃度與風速時序資料中，可知在季節性變化上，冬季期間之葉綠素a濃度比起其他季節還來得高。在年間變化上，我們從HHT的EMD分析結果，在SEATS測站月平均葉綠素a濃度及風速隨時間的變化，兩者趨勢皆降低，葉綠素a濃度降低了約13%，風速降低了約19%。
我們也與西菲律賓海區域做比較，兩區域皆受到ENSO事件的影響，但所表現出來的情況不同。SEATS測站在MEI>0( El Nino )期間，葉綠素a濃度與風速異常值有一定程度的關係性，在MEI<0( La Nina )期間，因營養鹽躍層較深，風速雖強但風造成的營養鹽通量並不能成比例的增加，所以葉綠素a濃度與風速異常值關係較弱。而西菲律賓海區域是開放性大洋，受到NEC及MD等海洋環流機制的影響，在MEI>0期間，所受到的影響較大，葉綠素a濃度與風速異常值關係差，MEI<0期間，受到NEC及MD等海洋環流機制的影響較小，葉綠素a濃度與風速異常值有一定程度的關係。我們推測這是因為SEATS測站為半封閉海盆的陸緣海，受到南海海盆湧昇效應影響，而西菲律賓海區域是開放性大洋，受到NEC及MD等海洋環流機制的影響，因此有著不同情況的表現。

In this study, we used satellite remote sensing data to investigate environmental conditions in the coastal zone off river mouth and in the South China Sea. Satellite remote sensing can provide longer time-series data with wider spatial coverage than traditional ship measuredments without using too much manpower or resources.
To study river plume, we used 14 SPOT satellite images of the coastal zone off the Lanyang River mouth in 2005. We applied a supervised maximum likelihood classification procedure to process the satellite images in order to identify the span of the Lanyang River plume. We suspected that Lanyang River plume should be affected by discharge, so we conducted liner regression between Lanyang River discharge and plume area. We found good correlation between them with R2=0.87 and P<0.01. Besides. we used in situ measured current data to demonstrate that the plume identified by the method is credible.
In order to understand the actual Lanyang River plume distribution and hydrological characteristics, we collected water samples in the coastal zone off Lanyang River moth on Oct. 8, 2011. Assuming that the distribution of the low salinity water was similar to the river plume identified by remote sensing images, we used Yilan County’s rainfall data to derive the discharge of the Lanyang River and calculated the plume area from the discharge using the linear regression relationship mentioned above. From the estimated plume area we determined from the salinity distribution that the Lanyang River plume should be within the salinity contour of 29.4 psu. The plume so defined is consistent with the photos taken during the cruise.
To study the open ocean, we used both MODIS and SeaWiFS satellite remote sensing data get 14 years of chlorophyll-a concentration time-series data at the SEATS station from Sep. 1997 to Dec. 2011. We also used NCEP data of wind speed to delineate their relationship with the chlorophyll-a data. In seasonal variability, both wind speed and chlorophyll-a concentration have higher values in winter. In inter-annual variability, we used Hilbert-Huang Transform to analyze the wind speed and chlorophyll-a data. The results show that the trend of both wind speed and chlorophyll-a concentration decreased. The wind speed decreased by 13%. The chlorophyll-a concentration decreased by 19%.
We compared the SEATS station with the Western Philippine Sea. At the SEATS station, wind speed anomaly and chlorophyll-a concentration anomaly have significant correlation when MEI>0 (El Nino phase), and very poor correlation when MEI<0 (La Nina phase). In the West Philippine Sea, the wind speed anomaly and chlorophyll-a concentration anomaly have worse correlation when MEI<0, and better correlation when MEI>0. The contrast probably results from the fact that the south China Sea is a semi-enclosed basin, where the basin wide upwelling was weaker, when MEI<0, while the WPS is an open ocean and strongly modulated by the North Equatorial Current and Mindanao Dome.

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