衛星遙測應用於環境評估之研究

Abstract

隨著衛星遙測科技的進步，科學家可更有效率的監測與評估自然環境的變化。在各項環境監測中，全球氣候變遷與水資源議題廣受矚目，其所造成的影響廣泛而深遠，水資源議題(例如洪水、乾旱、水質)與全球氣溫升高均造成嚴重的災害與難以估計的損失。本文應用衛星於環境監測與評估分為三個部份，第一部分是以SPOT衛星監測員山子分洪隧道出口海域水質變化，評估分洪對於該海域水質的影響。研究中提出水體表面反射率反算程序，此程序適用於小區域尺度的遙測應用。傳統海域水質監測多以單變量模式建立推估式，然而水中所含物質例如懸浮顆粒、有機溶解物質與藻類等同時影響水體的光譜反射特性，吾人提出多變量模式可更有效推估水質變數，且符合水質變數物理特性，推估結果明顯優於單變量模式，最後繪製水質變數海域分布圖，供決策單位使用。第二部份，探討土地利用變遷對於週遭空氣溫度改變的評估。普遍而言，土地利用變遷趨勢反映區域環境生態特性，然而土地利用變遷影響週遭空氣溫度，本文以AVHRR影像推估地表溫度，提出新的方式評估AVHRR像元內土地利用類別比例對空氣溫度的影響。第三部份是評估乾旱造成林地植生生理特性改變的監測，使用SPOT衛星計算植生指標，提出以植生指標所定義的林地乾旱等級；同時以NOAA衛星探討林地於植生指標與地表溫度特徵空間的季節變動特性。環境評估須大量資料綜合評估，然而衛星資料提供決策者快速而全面的資訊，為決策與防治程序中有效率的工具之一。

With the fast advancement of remote sensing technology, efficient and timely monitoring of environmental changes has become a reality. Among all kinds of environmental monitoring, climate changes and water resources are of most concern due to their extensive and potentially devastating impact. In this dissertation, feasibilities of three types of environmental monitoring – coastal water quality monitoring, effect of landcover changes on ambient air temperature, and forest drought monitoring using remote sensing techniques are investigated. A multivariate water quality estimation model which can take into consideration the combined effect of various seawater constituents on water surface reflectance was proposed. The multivariate model was found to be superior to traditional univariate models. Changes in coverage ratio of individual landcover types within a NOAA pixel affect the NOAA-pixel average air temperature. Forest drought monitoring involves drought classification using NDVI derived from SPOT images. Seasonal variations of NDVI and ambient air temperature were assessed using multispectral SPOT images and NOAA thermal images.