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Refined mapping of tree cover at fine-scale using time-series Planet-NICFI and Sentinel-1 imagery for Southeast Asia (2016–2021)
Earth System Science Data ( IF 11.4 ) Pub Date : 2023-04-27 , DOI: 10.5194/essd-2023-143
Feng Yang, Zhenzhong Zeng

Abstract. High-resolution mapping of tree cover is indispensable for effectively addressing tropical forest carbon loss, climate warming, biodiversity conservation, and sustainable development. However, the availability of precise high-resolution tree cover map products remains inadequate due to the inherent limitations of mapping techniques utilizing medium-to-coarse resolution satellite imagery, such as Landsat and Sentinel-2 imagery. In this study, we have generated an annual tree cover map product at a resolution of 4.77 m for Southeast Asia (SEA) for the years 2016–2021 by integrating Planet-Norway’s International Climate & Forests Initiative (NICFI) imagery and Sentinel-1 Synthetic Aperture Radar data. we have also collected annual samples to assess the accuracy of our Planet-NICFI tree cover map products. The results show that our Planet-NICFI tree cover map products during 2016–2021 achieve high accuracy, with an overall accuracy of 0.867 ± 0.017 and a mean F1 score of 0.921, respectively. Furthermore, our tree cover map products exhibit high temporal consistency from 2016 to 2021. Compared to existing map products (FROM-GLC10, ESA WorldCover 2020 and 2021), our tree cover map products exhibit better performance, both statistically and visually. Yet, the imagery obtained from Planet-NICFI performs less in mapping tree cover in areas with diverse vegetation or complex landscapes due to insufficient spectral information. Nevertheless, we highlight the capability of Planet-NICFI datasets in providing quick and fine-scale tree cover mapping to a large extent. The consistent characterization of tree cover dynamics in SEA's tropical forests can be further applied in various disciplines. The annual Planet-NICFI V1.0 tree cover map products from 2016 to 2021 at 4.77 m resolution are publicly available at https://cstr.cn/31253.11.sciencedb.07173 (Yang and Zeng, 2023).

中文翻译:

使用东南亚时间序列 Planet-NICFI 和 Sentinel-1 图像(2016-2021 年)精细绘制精细比例的树木覆盖图

摘要。高分辨率的树木覆盖图对于有效解决热带森林碳流失、气候变暖、生物多样性保护和可持续发展是必不可少的。然而,由于利用中到粗分辨率卫星图像(例如 Landsat 和 Sentinel-2 图像)的制图技术存在固有局限性,因此精确的高分辨率树木覆盖图产品的可用性仍然不足。在这项研究中,我们通过整合 Planet-Norway 的国际气候与森林倡议 (NICFI) 图像和 Sentinel-1 Synthetic,生成了 2016-2021 年东南亚 (SEA) 分辨率为 4.77 m 的年度树木覆盖图产品孔径雷达数据。我们还收集了年度样本,以评估我们的 Planet-NICFI 树木覆盖图产品的准确性。0.867 ± 0.017 和平均 F1 分数分别为 0.921。此外,我们的树木覆盖图产品在 2016 年到 2021 年期间表现出很高的时间一致性。与现有地图产品(FROM-GLC10、ESA WorldCover 2020 和 2021)相比,我们的树木覆盖图产品在统计和视觉上都表现出更好的性能。然而,由于光谱信息不足,从 Planet-NICFI 获得的图像在绘制植被多样或景观复杂的地区的树木覆盖率时表现较差。尽管如此,我们还是强调了 Planet-NICFI 数据集在很大程度上提供快速和精细比例的树木覆盖映射的能力。SEA 热带森林中树木覆盖动态的一致特征可以进一步应用于各个学科。2016年至2021年年度Planet-NICFI V1.0树木覆盖图产品在4。
更新日期:2023-04-28
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