Ayub Sugara, A. H. Lukman, A. W. Rudiastuti, A. Anggoro, M. F. Hidayat, Feri Nugroho, A. M. Muslih, A. Suci, Rifi Zulhendri, Marissa Rahmania
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引用次数: 1
Abstract
The mangroves' aboveground biomass significantly contributes to the global carbon cycle or economic and ecological values. This makes knowledge about the spatial extent of the mangroves indispensable for policymakers. The sequence of mangroves’ condition range also requires remote sensing data to update the geographical information and synthesize carbon stock in Bengkulu. Therefore, this study aims to create a spatial distrribution of mangroves and evaluate their carbon stock in Bengkulu City using Sentinel-2 imagery. The semi-empirical method uses Sentinel-2 imagery through NDVI to appraise and picture the mangroves' aboveground carbon stock. An allometric equation was used to compute the mangroves' aboveground carbon stock from field measurements. Non-linear regression was used to establish a connection between the NDVI calculated from the Sentinel-2 imagery and the mangroves' aboveground biomass measured in the field, which was subsequently used for aboveground carbon estimation. The results showed that mangroves mapping could derive overall accuracy of 89.09%, where the high-density class existed in 135.12 Ha of total area. It was also discovered that Sentinel-2 imagery could estimate mangroves carbon stock up to 61%. The carbon stock estimation based on the imagery has a value of 16.3992 – 115.134 t C/ha, while that of field survey data ranges from 19.69 to 326.06 t C/ha. These results showed that Sentinel-2B spectral data is functional and has a good chance of being able to predict carbon stock.
Keywords : Carbon; mangroves; NDVI; remote sensing; sentinel-2B
Copyright (c) 2022 Geosfera Indonesia and Department of Geography Education, University of Jember
This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License
红树林的地上生物量对全球碳循环或经济和生态价值有重要贡献。这使得有关红树林空间范围的知识对决策者来说是必不可少的。红树林状况范围的序列还需要遥感数据来更新地理信息并合成明古鲁的碳储量。因此,本研究旨在创建明古鲁市红树林的空间分布,并使用Sentinel-2图像评估其碳储量。半经验方法通过NDVI使用Sentinel-2图像来评估和描绘红树林的地上碳储量。通过实地测量,使用异速生长方程计算红树林的地上碳储量。使用非线性回归来建立根据Sentinel-2图像计算的NDVI与现场测量的红树林地上生物量之间的联系,随后用于地上碳估算。结果表明,红树林测绘的总体准确率为89.09%,其中高密度类别占总面积的135.12公顷。人们还发现,哨兵2号的图像可以估计红树林的碳储量高达61%。基于图像的碳储量估计值为16.3992–115.134 t C/ha,而实地调查数据的值为19.69至326.06 t C/ha。这些结果表明,Sentinel-2B光谱数据是有效的,很有可能预测碳储量。关键词:碳;红树林;NDVI;遥感;sentinel-2B版权所有(c)2022 Geosfera Indonesia和詹伯大学地理教育系本作品根据知识共享署名共享类似4.0的国际许可证获得许可