Assessment of mangrove cover and biomass with remote sensing technologies to conserve Gulf of Khambhat, Gujarat, India

Nilima R. Chaube, Yashraj Jain, Seema Mahajan

Article ID: 9831
Vol 7, Issue 2, 2024

VIEWS - 6 (Abstract) 4 (PDF)

Abstract


Natural resource conservation is vital for maintaining ecosystems that support biodiversity, regulate climate, and provide essential resources for human well-being. As ecosystems face growing pressures from deforestation, pollution, and climate change, remote sensing has become a key tool for monitoring and protecting these environments. Through satellite imagery, LiDAR, and aerial photography, remote sensing offers detailed insights into land cover changes, habitat degradation, and forest health, enabling data-driven conservation strategies. Mangroves play a crucial role in natural resource conservation by protecting coastlines from erosion, reducing the impacts of storms, and providing habitat for diverse marine species. They also act as significant carbon sinks, helping to mitigate climate change while supporting fisheries and local livelihoods. Specifically, for mangroves, remote sensing plays a critical role in assessing ecosystem health, species composition, and disturbances like illegal logging and coastal erosion, supporting effective conservation and restoration efforts to ensure their sustainability. The study of mangroves in the Gulf of Khambhat, Gujarat, emphasizes the critical role of mangrove ecosystems in biodiversity conservation, coastal protection. Leveraging remote sensing techniques such as microwave (ALOS PALSAR-2-L band with 25 m resolution) and optical (multi-spectral) (Sentinel-2 MSI with 10m resolution), the research integrates the mangrove and non-mangrove delineation, change detection to offer insights into natural resource conservation of mangroves and Above Ground Biomass (AGB) estimation. In this study the area of mangroves obtained is 94.94 km2 from L-band SAR data (25 m resolution and 2020), 98.55 km2 from Optical data (10m resolution and 2020) while the Forest Survey of India Report (2021) illustrate 101.53 km2 mangrove area at Gulf of Khambhat, India. The accuracy of the area of mangroves obtained from remote sensing is 93.50 % from L-band SAR) and 97.06 % from Optical data (Sentinel-2 MSI) with respect to area reported in Forest Survey of India Report (2021). These results are crucial for loss and recovery monitoring of mangrove forest, to enable targeted conservation efforts. This study offers a comprehensive approach to conserving natural resources by enhancing the accuracy of biomass mapping and ecosystem monitoring, ensuring effective conservation strategies for the biodiversity-rich mangrove regions of the Gulf of Khambhat.


Keywords


mangroves; remote sensing; Above Ground Biomass (AGB); Support Vector Machine (SVM) classification

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DOI: https://doi.org/10.24294/nrcr9831

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