泥炭地的多变量建模和碳储量估算:来自印度尼西亚卡普亚斯湿地泥炭性质、有机岩石学和遥感分析的限制

Ferian Anggara , Alfu Afkar Anniffari , Muhammad Nicco A'raaf Al Danny , Aldian Fahrialam , Gayatri Indah Marliyani , Agung Setianto , Aulia Agus Patria
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引用次数: 0

摘要

泥炭地碳储量是泥炭分布与总碳量的对应关系;然而,影响这一过程的各种相互作用因素似乎更为复杂,难以概括。本研究利用遥感分析(UAV、Landsat 8和9图像以及DEM)约束,结合原位泥炭厚度测量、泥炭性质和有机岩石学,改进了西加里曼丹卡普阿斯湿地碳储量的估算。我们展示了一个关于圆顶泥炭地分布和地形及其最近状况的新发现:原始泥炭地和改变泥炭地。泥炭有两种类型,即挖苦泥炭和挖苦泥炭。泥炭类型与其性质相对应,控制着总碳量。卡普阿斯湿地的总碳储量为221.08 MtC。本研究基于高程和泥炭类型的模型,以及基于泥炭厚度和河流的模型两种多变量建模方法之间的差异仅为1.59%,具有较好的精度水平,而单变量建模方法与多变量建模方法之间的差异约为6.42% - 8.14%。因此,本研究估计的模型误差为±7%,使总碳储量在205.6 MtC - 236.56 MtC之间,其中221.08 MtC为最佳估计值。我们的研究表明,每种泥炭类型在泥炭的物理、化学和生物特性方面都具有独特的特征。这些差异将影响碳的数量,在估算碳储量时应考虑到这一点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Multivariable modelling and carbon stored estimation in peatland: Constraints from peat properties, organic petrology, and remote sensing analysis in the Kapuas Wetland, Indonesia

Multivariable modelling and carbon stored estimation in peatland: Constraints from peat properties, organic petrology, and remote sensing analysis in the Kapuas Wetland, Indonesia
Carbon stores in peatlands are correspondence of peat distribution and amount of total carbon; however, various interacting factors are involved affecting this process seem to be more complicated and difficult to generalize. This study improved the estimation of the amount of carbon stored in Kapuas Wetland, West Kalimantan using combined remote sensing analysis (UAV, Landsat 8 and 9 imageries and DEM) constraints with in-situ peat thickness measurements, peat properties and organic petrology. We demonstrated a novel finding on distribution and topography of domed peatland as well as their recent conditions: pristine and altered peatlands. Two types of peats were identified, sapric and hemic peats. Peat types correspond to their properties and control the amount of total carbon. The total carbon stored in the Kapuas Wetland contributes to a carbon pool of 221.08 MtC. The difference between two multivariable modelling approaches: a) elevation and peat types-based model, and b) peat thickness and river-based model in this study is only 1.59 %, showing a good level of precision, while single variable modelling approach shows difference around 6.42 %–8.14 %, compared to multivariable modelling approaches. Thus, this study presents an estimated modelling error of ±7 %, making total carbon stored ranging from 205.6 MtC – 236.56 MtC, with 221.08 MtC as the best estimation. Our study suggests that each peat type has unique characteristics in both physical, chemical and biological properties of the peat. These differences will influence the amount of carbon, which should be considered for estimating the amount of carbon stored.
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