臺灣博碩士論文加值系統

本論文強調衛星觀測資料在海洋地理資訊系統之應用。衛星遙測具有空間覆蓋面廣、時間序列長和空間解析度高等優點，為海洋觀測與研究提供一個嶄新的資料庫。本研究結合QuikSCAT衛星SeaWinds海表面風場資料以及Aqua衛星MODIS之海表溫與葉綠素甲濃度資料，在SuperGIS 2平臺上開發衛星資料之空間變化及時間序列分析，及查詢等功能，同時透過經驗正交函數（Empirical Orthogonal Function）分析及經驗模態分解法(Empirical Mode Decomposition)、突顯大範圍衛星資料之時空主要變化，希望能有助於擴展海洋地理資訊系統(Marine Geographical Information System)在現象解說及分析上之運用及發展。

Satellite image covers a wide range of area and long period of time, as well as with high-resolution nowadays. It’s an important and innovate database for the marine environmental informatics (Marine GIS). In this study, application of the satellite data and image in marine geographical system is demonstrated. We use EOF (Empirical Orthogonal Function) and EMD (Empirical Mode Decomposition) to analyze the Aqua satellite MODIS sea surface temperature (SST), and chlorophyll-a concentration (Chl-a), and QuikSCAT satellite Sea Winds sea surface wind (SSW). The SuperGIS 2 is used as a platform to integrate the analysis tools (e.g., EOF and EMD) and to present the temporal and spatial changes of assimilated SST, Chl-a, SSW, respectively. This GIS-based marine environmental information system, integrating satellite data and analysis tools, provides query and visualization functions. We can use it to process, analyze and present the satellite data efficiently.

謝辭 I
中文摘要 II
Abstract IV
目錄 IV
表目錄 VII
圖目錄 VIII
第一章 前言 VIII
1.1地理資訊系統 1
1.1.1地理資訊系統應用 2
1.1.2地理資訊系統發展趨勢 3
1.2 海洋地理資訊系統 4
1.3 海洋地理資訊系統之應用 7
1.4 研究動機與目的 10
第二章 資料來源 12
2.1 海表溫與葉綠素甲濃度 12
2.2 海表面風場 12
第三章 研究方法 14
3.1 特定區域單月份影像分析 14
3.2 特定範圍空間平均量之長期變化 15
3.3 經驗正交函數 15
3.4 經驗模態分解法 17
第四章 操作步驟與研究成果 19
4.1系統架構 19
4.2 空間分析 20
4.2.1 海表溫之空間分析 20
4.2.2 葉綠素甲濃度之空間分析 20
4.2.3海表面風場之空間分析 21
4.2.4疊圖分析 22
4.3時間範圍查詢 22
4.3.1 月平均海表溫分析 22
4.3.1 月平均葉綠素甲濃度分析 23
4.4 經驗正交函數分析 23
4.4.1海表溫EOF分析 23
4.4.2海表溫去除空間平均EOF分析 24
4.4.3海表溫去除時間平均EOF分析 24
4.4.4葉綠素甲濃度EOF分析 25
4.4.5葉綠素甲濃度去除空間平均EOF分析 25
4.4.6葉綠素甲濃度去除時間平均EOF分析 25
4.4.7海表面風場EOF分析 26
4.4.8海表面風場去除空間平均EOF分析 27
4.4.9海表面風場去除時間平均EOF分析 27
4.5 經驗模態分解法分析 28
4.5.1 葉綠素甲濃度去除空間平均EOF之EMD分析 28
第五章 結論 30
參考文獻 32

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