ABSTRACT

This study validated SNAP-derived LAI from Sentinel-2 and its consistency with existing global LAI products. The validation and inter-comparison experiments were performed on two processing levels, i.e., Top-of-Atmosphere and Bottom-of-Atmosphere reflectances and two spatial resolutions, i.e., 10 m, and 20 m. These were chosen to determine their effect on retrieved LAI accuracy and consistency. The results showed moderate R ², i.e., ~0.6 to ~0.7 between SNAP-derived LAI and in-situ LAI, but with high errors, i.e., RMSE, BIAS, and MAE >2 m² m^–2 with marked differences between processing levels and insignificant differences between spatial resolutions. In contrast, inter-comparison of SNAP-derived LAI with MODIS and Proba-V LAI products revealed moderate to high consistencies, i.e., R ² of ~0.55 and ~0.8 respectively, and RMSE of ~0.5 m² m^–2 and ~0.6 m² m^–2, respectively. The results in this study have implications for future use of SNAP-derived LAI from Sentinel-2 in agricultural landscapes, suggesting its global applicability that is essential for large-scale agricultural monitoring. However, enormous errors in characterizing field-level LAI variability indicate that SNAP-derived LAI is not suitable for precision farming. In fact, from the study, the need for further improvement of LAI retrieval arises, especially to support farm-level agricultural management decisions.

摘要

这项研究验证了Sentinel-2的SNAP衍生LAI及其与现有全球LAI产品的一致性。验证和比对实验是在两个处理级别上进行的，即大气顶部和大气底部的反射率以及两个空间分辨率，即10 m和20 m。选择这些参数以确定它们对检索到的LAI准确性和一致性的影响。结果显示，在SNAP派生的LAI和原位 LAI之间，R ^2为中等 ，即〜0.6至 〜0.7，但具有较高的误差，即RMSE，BIAS和MAE> 2 m ²  m ^–2 在处理级别之间存在明显差异，而在空间分辨率之间则没有明显差异。相比之下，SNAP衍生的LAI与MODIS和Proba-V LAI产品的相互比较显示出中等至高度的一致性，即 R ² 分别为〜0.55和〜0.8，RMSE为〜0.5 m ²  m ^–2 和〜0.6 m ²  m ^–2， 分别。这项研究的结果对Sentinel-2的SNAP衍生的LAI在农业景观中的未来使用具有影响，表明其全球适用性对于大规模农业监测至关重要。但是，在表征田间水平LAI变异性方面存在巨大错误，这表明SNAP衍生的LAI不适合精确耕作。实际上，根据该研究，出现了进一步改善LAI检索的需求，特别是为了支持农场一级的农业管理决策。