在热带森林环境中使用高分辨率的NICFI-Planet基底图测试了两个新的云掩盖算法
K M Ashraful Islam1,2, Shahriar Abir2, Robert Kennedy1
1College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, OR 97331, USA.
Sensors (Basel, Switzerland)
|December 31, 2025
概括
开发了两种新的云掩盖算法,用于使用谷歌地球引擎 (GEE) 上的NICFI-Planet图像进行高分辨率热带森林监测. 这些可重复的方法通过有效地去除云和影子来提高数据的可用性.
科学领域:
- 遥感 遥感 遥感 遥感
- 环境监测 环境监测
- 地理信息系统 地理信息系统
背景情况:
- 高分辨率的卫星图像,如谷歌地球引擎 (GEE) 上的NICFI-Planet集合,对于精细的热带森林监测至关重要.
- 卫星数据中的持续云层,阴影和雾显著降低了其用于准确环境分析的实用性.
- 现有的云掩盖方法可能无法针对NICFI-Planet等特定数据集进行优化,或可能需要广泛的标记数据.
研究的目的:
- 开发和介绍两个简单,完全可复制的云掩盖算法,适用于谷歌地球引擎上的NICFI-Planet图像收集.
- 评估这些算法在多种多样的热带三角洲红树林环境中的性能和适用性.
- 提供可以轻松应用的操作工具,而不需要标记样本.
主要方法:
- 算法A:一种使用蓝色和近红外光谱带的值方法.
- 算法B:一种来自Sentinel-2的统计值方法,每带有截止值.
- 这两种算法都在谷歌地球引擎 (GEE) 中端到端实现,用于操作使用,并在桑达尔班,比迪亚达里三角洲和艾耶瓦迪三角洲进行了测试.
主要成果:
- 算法B有效地删除了大多数云和明亮水像素,但显示出过度掩盖雾和低对比度特征的倾向.
- 算法A保留了更多可用的像素,尽管它的性能因地区而异,在Sundarbans更保守,在印度和缅甸过度包容.
- 这两种算法都为需要标记数据的方法提供了切实可行的替代方案,GEE的实施确保了可重现性和一致性.
结论:
- 开发的云掩盖算法为热带森林监测中的NICFI-Planet数据提供了一个务实的,第一通解决方案.
- 算法的有效性可能因不同的环境条件而异,需要仔细考虑区域特征.
- 它们的简单,可共享的GEE代码有助于在不同地理区域实现一致的应用,提高了高分辨率卫星图像的可用性.
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