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Introduction

Coastal habitats are dynamic and diverse ecosystems that are crucial for biodiversity and ecosystem functioning. However, these habitats are under increasing pressure from human activities, climate change, and natural disasters. Monitoring and managing coastal habitats require accurate and up-to-date information on their spatial distribution and health. Traditional methods of habitat mapping and classification are often time-consuming, labor-intensive, and costly.

Recent advances in remote sensing technologies, such as drones, offer new opportunities for rapid and cost-effective monitoring of coastal habitats. Drones, also known as unmanned aerial vehicles (UAVs), can capture high-resolution images and data that can be used to classify and map coastal habitats with high accuracy. This thesis aims to explore the potential of using drones for coastal habitat classification and mapping.

Chapter 1: Introduction
1.1 Introduction
1.2 Background of study
1.3 Problem Statement
1.4 Objective of study
1.5 Limitation of study
1.6 Scope of study
1.7 Significance of study
1.8 Structure of the Thesis
1.9 Definition of terms

Chapter 2: Literature Review
2.1 Introduction to coastal habitats
2.2 Traditional methods of habitat classification
2.3 Remote sensing technologies for habitat mapping
2.4 Applications of drones in habitat classification
2.5 Challenges and limitations of drone-based habitat mapping
2.6 Case studies of drone-based habitat classification
2.7 Advances in image processing and machine learning algorithms
2.8 Accuracy assessment of drone-based habitat mapping
2.9 Future trends in drone technology for habitat classification
2.10 Summary of key findings

Chapter 3: Research Methodology
3.1 Study area selection
3.2 Drone selection and data collection
3.3 Image processing and data analysis
3.4 Ground truthing and validation
3.5 Classification algorithm development
3.6 Accuracy assessment
3.7 Data interpretation and visualization
3.8 Ethical considerations

Chapter 4: Discussion of Findings
4.1 Overview of study results
4.2 Comparison with traditional methods
4.3 Accuracy assessment and validation
4.4 Implications for habitat management and conservation
4.5 Limitations and challenges encountered
4.6 Recommendations for future research
4.7 Policy implications
4.8 Conclusions

Chapter 5: Conclusion and Summary
5.1 Summary of key findings
5.2 Contribution to knowledge
5.3 Practical implications
5.4 Recommendations for further research
5.5 Conclusion

Thesis Overview:
Coastal habitats are essential ecosystems that face increasing threats from human activities and climate change. Monitoring and managing these habitats require accurate and up-to-date information on their spatial distribution and health. This thesis explores the use of drones for coastal habitat classification and mapping, aiming to provide a cost-effective and efficient alternative to traditional methods. The literature review discusses the current state of remote sensing technologies for habitat mapping, highlighting the potential of drones in this field. The research methodology outlines the steps involved in data collection, image processing, and classification algorithm development. The discussion of findings presents the results of the study, including accuracy assessments and implications for habitat management. The conclusion summarizes the key findings and provides recommendations for further research in this area.

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