Validation of the Sentinel Simplified Level 2 Product Prototype Processor (SL2P) for mapping cropland biophysical variables using Sentinel-2/MSI and Landsat-8/OLI data
Validation of the Sentinel Simplified Level 2 Product Prototype Processor (SL2P) for mapping cropland biophysical variables using Sentinel-2/MSI and Landsat-8/OLI data
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DOI：
10.1016/j.rse.2019.03.020
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发表时间：
2019-05-01
影响因子：
13.5
通讯作者：
Goita, Kalifa
中科院分区：
文献类型：
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作者：
Djamai, Najib;Fernandes, Richard;Goita, Kalifa
利用Sentinel-2/MSI和Landsat-8/OLI数据估算叶面积指数(LAI)、植被覆盖率(FCover)和冠层含水率(CWC)的简化2级产品原型处理器(SL2P)在一个农业区得到了验证。在SMAP验证实验2016实地活动期间收集的现场数据被用作参考。SL2P处理器的性能在作物类型和生物物理变量之间有很大差异。在所有作物中，当使用MSI(叶面积指数的斜率(偏差)为0.70(-0.37)和0.42(-0.37 kg/m(2)或OLI(斜率(偏差)为0.59(-1.21)和0.24(-0.23 kg/m(2)数据时，SL2P低估了原位LAI和CWC的测量。在所有作物中，SL2P fCover估计的准确性更高(使用MSI的斜率(偏差)为0.99(1.84%)，使用OLI的斜率(偏差)为0.93(-3.75%))。由SL2P估算的生物物理变量与现场数据的RMSE分别为：LAI为0.98(1.63)，fCover为11.39%(10.95%)，CWC为0.66 kg/m(2)(0.96 kg/m2)。与使用相应传感器数据的SL2P估计相比，使用当地校准的植被指数模型通常获得略好的结果。从MSI和OLI获得的植被生物物理变量的不确定性度量与插入的现场数据时间序列相比，可以与用于交叉验证的结果相媲美，这表明使用插入的原位数据时间序列来验证在时间上采样稀疏的分米分辨率遥感产品的可能性。
The Simplified Level 2 Product Prototype Processor (SL2P) for estimating Leaf Area index (LAI), fraction of vegetation cover (fCover) and Canopy Water Content (CWC) from Sentinel-2/MSI and Landsat-8/OLI data was validated over an agricultural region. In-situ data collected during the SMAP Validation Experiment 2016 field campaign were used as a reference. SL2P processor performance varied substantially between crop type and biophysical variable. Over all crops, SL2P underestimated in-situ LAI and CWC measurements when using either MSI (slope (bias) of 0.70 (- 0.37) for LAI and 0.42 (- 0.37 kg/m(2)) for CWC) or OLI (slope (bias) of 0.59 (-1.21) for LAI and 0.24 (- 0.23 kg/m (2)) for CWC) data. The accuracy of SL2P fCover estimates, over all crops, was higher (slope (bias) of 0.99 (1.84%) using MSI and 0.93 (- 3.75%) using OLI). The RMSE between biophysical variables estimated using SL2P from MSI (OLI) in comparison to in-situ data was 0.98 (1.63) for LAI, 11.39% (10.95%) for fCover and 0.66 kg/m(2) (0.96 kg/m (2)) for CWC. Slightly better results are generally obtained using locally calibrated vegetation indices models, when compared to SL2P estimates using the corresponding sensor data. Uncertainty metrics of vegetation biophysical variables derived from both MSI and OLI, when compared to interpolated in-situ data time series, are found comparable to results obtained for cross-validation suggesting the possibility of using interpolated in-situ data time series for validating decametric resolution remote sensing products sparsely sampled in time.