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Elsevier

Remote Sensing Techniques for Blue Carbon and Coastal Ecosystem Monitoring

  • 1 Edición - 1 de noviembre de 2026
  • Última edición
  • Editores: Uzair Aslam Bhatti, Sibghat Ullah Bazai, Muhammad Aamir
  • Idioma: Inglés

Remote Sensing Techniques for Blue Carbon and Coastal Ecosystem Monitoring offers a comprehensive exploration of cutting-edge remote sensing technologies for the effective monito… Leer más

Descripción

Remote Sensing Techniques for Blue Carbon and Coastal Ecosystem Monitoring offers a comprehensive exploration of cutting-edge remote sensing technologies for the effective monitoring and conservation of blue carbon ecosystems, including mangroves and seagrass beds. In the face of increasing threats from emerging contaminants such as plastics, pharmaceuticals, and pollutants, this book highlights the vital role these ecosystems play in carbon sequestration and climate change mitigation. Combining satellite imagery, UAV-based sensing, hyperspectral techniques, and ecological models with GIS integration, it provides both theoretical insights and practical case studies from around the world.

Essential for students, researchers, practitioners, and policymakers, this guide equips readers with the tools necessary to assess ecosystem health, inform management strategies, and support sustainable coastal development in a rapidly changing environment.

Puntos claves

  • Offers a comprehensive overview of remote sensing technologies, including satellite imagery, UAV systems, and hyperspectral sensing for monitoring blue carbon ecosystems
  • Provides practical approaches and tools for assessing ecosystem health, supporting conservation, and informing management strategies
  • Includes case studies from around the world that illustrate successful applications of remote sensing techniques in coastal ecosystem monitoring and pollution assessment

De interès para

Students and researchers specializing in coastal and marine ecosystems, ecology, and climate change mitigation

Índice

Part I: Basics of Blue Carbon and Remote Sensing

1. Introduction to Blue Carbon Ecosystems

2. Emerging Contaminants in Coastal Ecosystems

3. Foundations of Remote Sensing for Coastal Ecosystem

4. Monitoring Geographic Ecological Land Processing

Part II: Mapping and Monitoring Blue Carbon Ecosystems

5. UAV and Drone-Based Remote Sensing for Coastal Contaminant Monitoring

6. Remote Sensing Data Collection Methods in Mangrove Ecosystems

7. Remote Sensing Applications in Mangrove & Blue Carbon Monitoring

8. Environmental Monitoring Using Spatio-temporal Patterns of Contaminants

9. Impact of Emerging Contaminants on Mangrove Ecosystems

10. Intelligent Deep Learning Methods for Ecological Land-change Monitoring

11. Segmentation Models in Agricultural Image Classification

12. Geospatial Data Integration for Coastal Ecosystems

13. Case Studies in Mangrove Monitoring Using Remote Sensing

14. Monitoring Coastal Ecosystem Health with UAVs & Drones

15. Challenges in Remote Sensing of Coastal Ecosystems

Part III: Quantifying Carbon and Verifying Impact

16. Blue Carbon Sequestration in Mangroves
Part IV: Future Horizons and Global Impact

17. Emerging Trends & Technologies in Remote Sensing

18. Future Directions in Mangrove & Blue Carbon Monitoring

Detalles del producto

  • Edición: 1
  • Última edición
  • Publicado: 1 de noviembre de 2026
  • Idioma: Inglés

Sobre los editores

UB

Uzair Aslam Bhatti

Uzair Aslam Bhatti has focused his research on applying machine learning to medical and signal processing problems, with a strong interest in the broader applications of artificial intelligence. He has published nearly 60 academic papers, more than 50 of which are indexed in SCI and EI. During his PhD at Hainan University, he received two Best Research Paper Awards and a Chinese Government Scholarship.

As a Postdoctoral Researcher at the School of Geography (Remote Sensing and Signal Processing), Nanjing Normal University, he published 11 papers in two years as first author (9 SCI journals and 2 conference papers), including articles in leading SCI journals such as IEEE Transactions on Geoscience and Remote Sensing (IF 8.1) and Chemosphere (IF 9.1). His contributions, including 10 SCI papers and two CCF B-level conference papers as first author, earned him recognition as an Excellent Postdoctoral Candidate by Nanjing Normal University.

He has also participated in major projects funded by the National Natural Science Foundation of China, the National Key R&D Program, and the Hainan Provincial Major Science and Technology Program.

Afiliaciones y experiencia
Associate Professor, College of Information and Communication Engineering, Hainan University, Haikou, China

SB

Sibghat Ullah Bazai

Sibghat Ullah Bazai received the Ph.D. degree in information technology with a specialization in cyber security from Massey University, Auckland, New Zealand. Currently, he is an Assistant Professor with the Department of Computer Engineering, Faculty of Information and Communication Technology, Balochistan University of Information Technology, Engineering, and Management Sciences (BUITEMS). His research interests include the application of cybersecurity and privacy in computer-aided diagnosis, disease identification using deep learning, local language sentiment corpus design, and smart city planning. He also serves as a Guest Editor and a Reviewer for special issues in journals, such as MDPI, Hindawi, CMC, PLOS One, and Frontier. He was a recipient of the HEC HRDI-UESTP Faculty Ph.D. Scholarship
Afiliaciones y experiencia
Balochistan University of Information Technology, Engineering, and Management Sciences (BUITEMS), Pakistan

MA

Muhammad Aamir

Muhammad Aamir received the Bachelor of Engineering degree in computer systems engineering from the Mehran University of Engineering and Technology Jamshoro, Sindh, Pakistan, in 2008, the Master of Engineering degree in software engineering from Chongqing University, Chongqing, China, in 2014, and the Ph.D. degree in computer science and technology from Sichuan University, Chengdu, China, in 2019.,He is currently an Associate Professor with the Department of Computer Science, Huanggang Normal University, Huanggang, China. His research interests include pattern recognition, computer vision, image processing, deep learning, and fractional calculus
Afiliaciones y experiencia
Associate Professor, Department of Computer Science, Huanggang Normal University, Huanggang, China