Mangrove forests are highly productive ecosystems and play an important role in the global carbon cycle. We used Shuttle Radar Topography Mission (SRTM) elevation data to estimate mangrove above-ground biomass (AGB) in Sabah, Malaysian northern Borneo. We developed a tree-level approach to deal with the substantial temporal discrepancy between the SRTM data and the mangrove’s field measurements. We predicted the annual growth of diameter at breast height and adjusted the field measurements to the SRTM data acquisition year to estimate the field AGB. A canopy height model (CHM) was derived by correcting the SRTM data with ground elevation. Regression analyses between the estimated AGB and SRTM CHM produced an estimation model (R²: 0.61) with a root mean square error (RMSE) of 8.24 Mg ha⁻¹ (RMSE%: 5.47). We then quantified the mangrove forest loss based on supervised classification of multitemporal Landsat images. More than 25,000 ha of mangrove forest had disappeared between 2000 and 2015. This has resulted in a significant decrease of about 3.96 million Mg of mangrove AGB in Sabah during the study period. As SRTM elevation data has a near-global coverage, this approach can be used to map the historical AGB of mangroves, especially in Southeast Asia, to promote mangrove carbon stock conservation.

中文翻译：

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使用SRTM和Landsat影像估算2000年至2015年马来西亚北部婆罗洲因森林砍伐造成的红树林地上生物量损失

红树林是高产的生态系统，在全球碳循环中发挥着重要作用。我们使用航天飞机雷达地形任务（SRTM）海拔数据估算了马来西亚婆罗洲北部沙巴的红树林地上生物量（AGB）。我们开发了一种树级方法来处理SRTM数据与红树林的野外测量之间的巨大时间差异。我们预测了乳房高度处直径的年增长量，并将野外测量值调整为SRTM数据采集年，以估计野外AGB。通过用地面标高校正SRTM数据，得出树冠高度模型（CHM）。估计的AGB和SRTM CHM之间的回归分析产生了估计模型（R ²：0.61），均方根误差（RMSE）为8.24 Mg ha ^-1（RMSE％：5.47）。然后，我们根据多时相Landsat影像的监督分类对红树林的损失进行了量化。在2000年至2015年之间，超过25,000公顷的红树林消失了。这导致沙巴州在研究期间显着减少了396万毫克的红树林AGB。由于SRTM高程数据具有近乎全球的覆盖范围，因此该方法可用于绘制红树林的历史AGB，尤其是在东南亚，以促进红树林碳储量的保存。