评估基于地球静止卫星的方法,以填补NDVI在北极轨道卫星观测中的差距
Han-Sol Ryu1, Sung-Joo Yoon1, Jinyeong Kim1
1Underwater Survey Technology 21, Incheon 21999, Republic of Korea.
Sensors (Basel, Switzerland)
|March 14, 2026
概括
这项研究将地球静止卫星数据与北极轨道卫星观测相结合,以改善植被监测. 综合方法提高了标准化差异植被指数 (NDVI) 数据的空间完整性,特别是在易于出现云层的地区.
科学领域:
- 地球观测 地球观测
- 遥感 遥感 遥感 遥感
- 植物生长监测 植物生长监测
背景情况:
- 极地轨道卫星为植被监测提供了有价值的规范差异植被指数 (NDVI) 数据.
- NDVI的时间连续性通常受到云层覆盖和卫星重访时间的限制.
- 地静止卫星提供更高的时间分辨率,但在空间分辨率上有所不同.
研究的目的:
- 评估使用地球静止卫星数据以提高Sentinel-2 NDVI的空间完整性的可行性.
- 开发一种方法来整合地球静止 (GOCI-II) 和极轨 (Sentinel-2) NDVI数据.
- 评估使用静止地数据填补云缺口的有效性.
主要方法:
- 一个数据驱动的转换框架将GOCI-II NDVI (250 m) 转换为类似MSI的NDVI (10 m).
- 交叉传感器集成的重点是保持空间模式,而不是严格的超分辨率.
- 云空隙填补实验利用暂时相邻的转换NDVI场景.
主要成果:
- 地静态衍生的NDVI成功捕获了Sentinel-2 NDVI的广泛空间组织和现场规模变化.
- 云填空实验显示,在转换的NDVI场景中,存在一致的变化模式.
- 观察到对比度降低和大小依赖偏差,受分辨率差异的影响.
结论:
- 整合地球静止和极轨观测显示了增强NDVI空间连续性的实际潜力.
- 这种方法可以改善经常受到云层覆盖影响的地区的植被监测.
- 进一步研究减少依赖于解决方案的偏见是有必要的.
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