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Spatial mapping of mangrove carbon stocks in mixed aquaculture-industrial landscapes of Kendal regency via Sentinel-2
 
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Universitas Negeri Semarang
 
These authors had equal contribution to this work
 
 
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Wahid Akhsin Budi Nur Sidiq   

Universitas Negeri Semarang
 
 
 
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ABSTRACT
Based on the Master Plan for the Acceleration and Expansion of Indonesia's Economic Development Kendal Regency is positioned as the industrial gateway to the Semarang Metropolitan Region. through the development of the Kendal Industrial Park. The development of the area was carried out by removing approximately 42-210 hectares of mangrove (2015-2024), so that one of its functions as a carbon absorber and storage medium is reduced. Calculations of the potential carbon stock of existing mangroves are needed as a baseline for identifying the impact of industrial area expansion. The objective of this study is to produce a baseline of carbon sequestration potential from mangrove . Research data using Sentinel-2 MSI Level-2A and field survey data measuring AGC parameters. The research method utilized multispectral random forest classification, spectral transformation, and AGC carbon stock calculations. The results showed that the mangrove at the study site covered an area of 492.37 hectares, of which approximately 393.75 hectares were in an industrial zone with a very high mapping accuracy of 0.91. The AGC measurement results in the field had an average of 31.83 tons/hectare for the predictor group and 31.83 tons/hectare for the validator group. The correlation results of 11 vegetation indices with AGC show that the GNDVI (r=0.543), SAVI (r=0.512) and EVI (r=0.504) indices have a very high to high correlation, while the MDI (r=0.143) and WFI (r=0.222) indices had the lowest correlations. The results of carbon stock calculations based on vegetation indices show an average value of 688,990.21 tons, with the highest calculation results produced by the MDI index with a value of 1,234,201.39 tons and the GNDVI index producing the lowest estimated value of approximately 434,494.73 tons. The AGC potential mapping model results with the highest accuracy were obtained from the SAVI (r=0.76), EVI (r=0.75), and ARVI (r=0.75). Conclusion: The use of appropriate vegetation indices, such as GNDVI, SAVI, EVI, and ARVI, can provide accurate information regarding the potential carbon stock in mangrove. Recommendation: future studies should involve all minor species compositions at the study site. The results of this study support the achievement of SDGs Point 11 (Sustainable cities and communities) and Point 13 (Climate action).
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