Integration of Hyperspectral Imaging and Deep Learning for Sustainable Mangrove Management and Sustainable Development Goals Assessment
- Title
- Integration of Hyperspectral Imaging and Deep Learning for Sustainable Mangrove Management and Sustainable Development Goals Assessment
- Creator
- Ilamathi P.; Chidambaram S.
- Description
- Mangrove forests support biodiversity and provide valuable ecosystem services. Their conservation is important for maintaining these benefits. In addition to this, understanding and preserving these forests is important for the assessment of Sustainable Development Goals (SDGs) such as SDG 1,2,3,6,8,11,12,13,14 and15. This review paper explores how the integration of Hyperspectral Image (HSI) technology and Deep Learning (DL) algorithms is helpful in mangrove conservation and SDGs assessment. HSI in mangrove research allows detailed analysis of tree health, species types and environmental stress factors (includes salinity levels, waterlogging, soil erosion, pollution, habitat fragmentation, disturbances from human activities etc.) with enhanced spectral and spatial resolution. Combining DL algorithms like Convolutional Neural Network (CNN) with HSI data automates mangrove mapping, detects change in mangrove health, estimates carbon sequestration and manages ecological zone. Rich spectral information from HSI empowers DL algorithms to identify patterns and features for accurate and efficient classification tasks in both supervised and unsupervised methods. This review aims to comprehensively summarize the research efforts reported in monitoring mangrove ecosystems through varied remote sensing approaches, algorithms and their support towards SDGs assessment. HSI and DL together offer a powerful approach for researchers, environmentalists and climate activists working towards sustainable development objectives. This paper not only focuses on mangrove conservation but also addresses challenges associated with integrating technologies such as data processing complexities and the need for specialized expertise. This study outlines advancements in HSI technology, DL applications and future directions to drive sustainable management strategies for mangrove ecosystems. The Author(s), under exclusive licence to Society of Wetland Scientists 2025.
- Source
- Wetlands, Vol-45, No. 1
- Date
- 2025-01-01
- Publisher
- Springer Science and Business Media B.V.
- Subject
- Convolutional Neural Network (CNN); Deep Learning (DL); Hyperspectral Image (HSI); Mangrove ecosystems; Sustainable Development Goals (SDGs)
- Coverage
- Ilamathi P., Department of Electronics and Communication Engineering, CHRIST University, Bengaluru, India; Chidambaram S., Department of Electronics and Communication Engineering, CHRIST University, Bengaluru, India
- Rights
- Restricted Access
- Relation
- ISSN: 2775212
- Format
- Online
- Language
- English
- Type
- Review
Collection
Citation
Ilamathi P.; Chidambaram S., “Integration of Hyperspectral Imaging and Deep Learning for Sustainable Mangrove Management and Sustainable Development Goals Assessment,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/21253.