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研究生(外文):Yuan-Fong Su
論文名稱(外文):Application of Remote Sensing Techniques to Environmental Assessment
指導教授(外文):Ke-Sheng Cheng
外文關鍵詞:environment monitoring and assessmentremote sensingwater qualitymultivariate modelandcover changeair temperaturedrought
  • 被引用被引用:1
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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.
Abstract i
摘要 ii
Contents iii
List of Tables v
List of Figures vi
Chapter 1 Introduction 1
1.1 Environmental monitoring and remote sensing techniques 1
1.2 Objectives 3
1.3 Structure 4
References 4
Chapter 2 Water quality monitoring using remotely sensed data 7
2.1 Introduction 7
2.2 Study area and materials 12
2.3 Retrieval of reflectance 15
2.4 Water quality estimation model assessment 26
2.5 Conclusions 35
References 38
Chapter 3 Assessing the effect of landcover changes on air temperature using remote sensing images 43
3.1 Introduction 43
3.2 Energy exchange between the land surface and the atmosphere 46
3.3 Study area and remote sensing data set 49
3.4 Land surface temperature estimation using NOAA images 49
3.5 Estimating the landcover-specific surface temperatures 54
3.6 Pixel-average air temperature estimation 61
3.7 Effect of landcover types on ambient air temperatures 65
3.8 Conclusions 72
References 73
Chapter 4 Forest Drought Monitoring 77
4.1 Introduction 77
4.2 Study Area and Materials 80
4.3 Drought indices 86
4.4 Results and discussion 90
4.4.1 Drought classification using SPOT image 91
4.4.2 Comparison between NDVI values derived from SPOT and AVHRR 95
4.4.3 Using AVHRR images for drought assessment 100
4.5 Conclusions 108
References 110
Chapter 5 Summary and future work 113
簡歷 115
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