| 姓名 |
古培榮(Guillermo Esquivel)
查詢紙本館藏 |
畢業系所 |
國際永續發展碩士在職專班 |
| 論文名稱 |
利用衛星遙測技術辨識 Fonseca灣中懸浮物與混濁度在時間與空間上的模式
(Use of Remote Sensing to identify Spatial and Temporal Patterns of Turbidity and Suspended Solids in TheGulf of Fonseca.)
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| 相關論文 | |
| 檔案 |
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| 摘要(中) |
開發中國家長久以來掙扎於環境永續與經濟發展中謀求平衡。政府和所有公民的期望，就是努力發展經濟，以提供人民及未來子孫更好的生活水準。然而這樣的信念，造成人為活動小從個體漁業，大至全國性政策的擬定與執行，在對自然資源的取用上，都以經濟發展為重心，未意識到其對環境平衡已造成重大的影響與災害。本論文以中美州變化情況最顯著的Fonseca海灣為例。Fonseca海灣由蕯爾瓦多、宏都拉斯及瓜地馬拉三個國家共有，其特性為土地使用的多變性。從城市發展擴大、農業建設、漁業、物流以及海洋運輸等，這些人為活動對入海口生態體系直接或間接地造成影響，已有事實証明此區之海洋生態體系已遭受污染。若能瞭解Fonseca海灣生態體系之運作模式，對於謀求避免污染的方法，以及辨視、處理、預防其對環境造成的重大影響，都能具有關鍵性的作用。
本研究運用衛星遙測技術為工具，從空間分佈以及時間變化上，辨視Fonseca海灣中污染的情況。研究目標有二，第一，利用Landsat 7 ETM+以及In situ measurements，從空間分佈上，研究選定的水質檢測指標（混濁度及懸浮物）。空間分佈的分析主要依據歷史資料之線性回歸統計模型。本研究的結果顯示，混濁度及懸浮物分別和Landsat 7 ETM+拍攝出之Band3與Band4之合成影象具有相關性。相關係數分別為，混濁度0.73以及懸浮物0.74。研究目標二，從時間上分析水質檢測指標，觀察期間由2004至2010年共七年。此標準化之過程是為了找到其他年度間也具有類以的基礎性關係。研究中同時考量到每年乾溼兩季之季節性之差異，以及觀察連續性乾季及連續性溼季之水質檢測指標表現。
本研究發現，藉由中解析度成像衛星(Moderate-resolution Satellite) 和In situ measurements，對應分析(mapping)混濁度模式及懸浮物之組成是可行的。透過對指標做季節性之分析，我們可以結論出，季節性改變是混濁度及懸浮物之變化最顯著的影響因素。在乾季期間，研究發現Bay of San Bernardo以及Bay of La Union出現最高程度的污染；另，本區人類水產活動頻繁，如蝦類之養殖，以及市政府廢水排放均在此區域。另一個重要結論為，透過七年間對水質混濁度和懸浮物之觀察，無相關證據顯示出漸進式的污染情況，這表示在蕯爾瓦多La Union港口進行之養殖類撈補，並未對混濁度和懸浮物模式造成長久的影響。測量撈補活動對海灣環境的影響需要更進一步的研究，我們可以透過在短時間距中拍攝的衛星影像觀察，以及研究補蝦產業在宏都拉和尼加拉瓜對當地海岸造成的影響。
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| 摘要(英) |
Developing Nations are always in a constant struggle to achieve subsistence both, governments and citizens dream about reaching economical development to offer to the present generation better life standards and to the future generations, better opportunities. In this quest for well being human practices at all scales, from artisanal fishery to Nationwide Policies, Plans and Strategies explodes any available natural resources to achieve that goal and must of the times there is no awareness on how affects the environment and natural equilibrium. The Gulf of Fonseca is one of the most dynamic spots on Central America, shared by three countries; El Salvador, Honduras and Nicaragua is scenario of constant land use changes, increase of urban developments, establishment of aquaculture industries at big scale, industrial fishery, logistics and marine transport. All these activities generate direct and indirect impacts to this estuarine ecosystem an undeniable fact is that pollution is already present in this marine ecosystem. Understanding how this ecosystem works is a key element to know how to preserve them from pollutants agents, to know how to identify, treat and prevent a major environmental impact. The approach of this thesis is the use of Remote Sensing as a tool to identify how contaminants behave in spatial distribution as well as time variations. This study has two major aims, the first one is to investigate spatial patterns in selected water quality indicators (Turbidity and Total Suspended Solids), by using Landsat 7 ETM+ and in situ measurements, the second aim is to determine temporal variations patterns in order to identify whether or not there is a factor that progressively affect to the environment or a permanent impact. To analyze spatial patterns based on previous studies a linear regression statistical model was performed, our results shows that Turbidity and Total Suspended Solids are correlated with the combination of Band 3 and 4 from the Landsat 7 ETM+, with a correlation coefficient of 0.73 for Turbidity and 0.74 for suspended solids. The second aim was to perform a Temporal Analysis within a time observation period of 7 years, from 2004 to 2010, for this a process of normalization was performed for apply the founded relationships to the rest of the years. Variations of the rainy season and dry season where considered for each year seasonal, also variation of rainy season through every consecutive year was observed, as well as dry season behavior. Conclusions on this study lead us to believe that mapping Turbidity Patterns and Suspended Solids concentrations is feasible, by the use of a moderate resolution satellite and in situ measurements. Through the seasonal change analysis we can conclude that the most predominant factors on variations of these patterns are change of seasons, during the dry season we can find the highest pollution levels in the Bay of San Bernardo and the Bay of La Union, this is also product of anthropogenic activities such as shrimp aquaculture and municipal waste water discharges to the Gulf. Another important conclusion is that there is no evidence of a progressive behavior on pollution by turbidity or suspended solids through the 7 years of observation, which means that the dredging works during the development of the port of La Union at El Salvador has no permanent impact on the turbidity and suspended solids patterns.
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| 關鍵字(中) |
★ 混濁度
★ 遙感探測
★ 回歸模組 |
關鍵字(英) |
★ Linear regression
★ Satellite Remote Sensing
★ Turbidity
★ Landsat 7 ETM+.
★ normalization of radiance images
★ Gulf of Fonseca |
| 論文目次 |
CHINESE ABSTRACT摘要 i
ABSTRACT ii
ACKNOWLEDGEMENTS iv
LIST OF FIGURES vii
LIST OF TABLES ix
Chapter I Introduction 1
1.1 Introduction 1
1.2 Hypothesis 4
Chapter II Literature Review 6
2.1 Turbidity definition 6
2.2 Causes of turbidity 7
2.3 Turbidity effects on sea and fresh water 8
2.4 Total Suspended Solids (TSS) 10
2.5 Total suspended solids effects on sea and fresh water 10
2.6 Relationship between Total suspended solids and Turbidity 11
2.7 Use of remote sensing as a tool to measure Water Quality 12
Chapter III Study Area 15
3.1 General description of the Gulf of Fonseca 15
3.2 Study Area Location 16
Chapter IV Data 20
4.1 Water Quality Samples 20
4.2 Remote Sensed Data 23
4.3 Satellite Images for temporal Analysis 28
4.3 Spatial data used 31
Chapter V Methodology 36
5.1 Image Preprocessing 36
5.1.1 Fill Gaps 37
5.2 Radiance Calculation 41
5.3 Turbidity and Total Suspended Solids Transformation 43
5.3.1 In situ measurement 43
5.3.2 Regression Analysis 44
5.3.3 Turbidity and Total Suspended Solids Calculation 48
5.4 Normalization for Temporal Analysis Methodology 48
5.4.1 Normalization 48
5.4.2 Turbidity and Total Suspended Solids Calculation for Temporal Analysis 49
5.5 Temporal Change Analysis 51
Chapter VI Results and Discussion 54
6.1 Linear Regression Results 54
6.1.1 Turbidity Linear Model 54
6.1.2 Total Suspended Solids Linear Model 58
6.2 Turbidity Map 62
6.3 Total Suspended Solids Map 63
6.4 Temporal Analysis 68
Chapter VII Conclusions and Recommendations 88
7.1 Conclusions 88
7.1.1 Linear Model 88
7.1.2 Maps of Turbidity and Total Suspended Solids 88
7.1.3 Temporal Analysis 89
7.2 Recommendations 91
7.2.1 Linear model regression analysis recommendations: 91
7.2.2 Temporal Analysis Recommendation 91
REFERENCES 93
APPENDIX 1 96
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| 參考文獻 |
APPENDIX 1
Water Quality Monitoring Report, August 2005 CEPA
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| 指導教授 |
陳繼藩(Chi-Farn Chen Ph.D.)
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審核日期 |
2011-7-15 |
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