通过更高的空间分辨率卫星图像提高印度尼西亚帝汶岛桉树种植园地面碳储量的估算精度

Q3 Social Sciences
R. Sadono, Emma Soraya
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引用次数: 0

摘要

桉树种植园是减缓气候变化过程中碳储存的重要贡献者,该种植园是在帝汶岛半干旱生态系统的土地恢复计划中建立的。为确保准确估算这些种植园的地面碳储量,必须不断将地面测量与遥感技术结合起来。因此,本研究旨在比较两幅空间分辨率极高的图像(即 Pleiades-1B 2021 和 Pléiades Neo 2022,像素尺寸分别为 2 x 2 m 和 1.2 x 1.2 m)的地上碳储量估算。采用归一化差异植被指数来识别桉树,并将密度分为低、中、高三个等级。结果表明,Pléiades Neo 图像在识别桉树方面优于 Pleiades-1B 图像,在估算地上碳储量方面也更为准确。不过,在提高准确性和为获得最高空间分辨率图像而增加成本之间需要权衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhancing the estimation accuracy of above-ground carbon storage in Eucalyptus urophylla plantation on Timor Island, Indonesia, through higher spatial-resolution satellite imagery
Eucalyptus urophylla plantation is an important contributor to carbon storage in climate change mitigation, established due to a land rehabilitation program in the semi-arid ecosystem in Timor Island. To ensure an accurate estimate of the above-ground carbon storage of these plantations, it is important to continuously combine ground measurement with remote sensing technology. Therefore, this study aimed to compare the above-ground carbon storage estimation of two very high spatial resolution images, namely Pleiades-1B 2021 and Pléiades Neo 2022 with pixel sizes of 2 x 2 m and 1.2 x 1.2 m, respectively. The normalized difference vegetation index was employed to identify the eucalyptus trees and classify the density into low, moderate, and high. The results showed that Pléiades Neo imagery provided superior eucalyptus tree identification to Pleiades-1B imagery and was more accurate in estimating above-ground carbon storage. However, there is a trade-off between increasing this accuracy and incurring a higher cost to achieve the highest spatial resolution image. 
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来源期刊
Journal of Degraded and Mining Lands Management
Journal of Degraded and Mining Lands Management Environmental Science-Nature and Landscape Conservation
CiteScore
1.50
自引率
0.00%
发文量
81
审稿时长
4 weeks
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