A coarse pixel-scale ground “truth” dataset based on global in situ site measurements to support validation and bias correction of satellite surface albedo products
A coarse pixel-scale ground “truth” dataset based on global in situ site measurements to support validation and bias correction of satellite surface albedo products
复制标题
DOI：
10.5194/essd-16-161-2024
复制
发表时间：
2024-01
影响因子：
11.4
通讯作者：
Fei Pan;Xiaodan Wu;Qicheng Zeng;R. Tang;Jingping Wang;Xingwen Lin;D. You;Jianguang Wen;
中科院分区：
文献类型：
--
作者：
Fei Pan;Xiaodan Wu;Qicheng Zeng;R. Tang;Jingping Wang;Xingwen Lin;D. You;Jianguang Wen;
抽象的。来自全球稀疏分布网络的现场测量是验证或纠正卫星产品偏差的重要参考数据来源。然而，由于原位测量和卫星测量之间的空间尺度存在巨大差异，除了原位站点的下垫面绝对均匀这一事实之外，两者无法进行比较。相反，现场测量需要放大才能与卫星像素相匹配。基于升级模型，我们还提出了由于广泛分布的空间异质性而导致原位观测普遍缺乏空间代表性的考虑，并基于稀疏分布的观测网络中416个原位站点的地面测量，开发了粗像素尺度的地面“真相”数据集。此外，我们还全面评估了具有不同空间代表性的站点的数据集的有效性。结果表明，当原位测量足迹小于卫星像素大小时，在验证中使用该数据集优于在异质表面上卫星和原位测量之间的直接比较。与空间异质性较强的区域相比，用于验证或偏差校正的参考数据的准确性可提高 17.09%。然而，随着空间异质性的减少，该数据集的改进程度呈现出下降的趋势。在全球范围内，像素尺度的地面“真相”数据集总体上提高了像素尺度参考数据的准确性，总体相对均方根误差（RRMSE）与原位单点测量相比降低了6.04%。我们的结果表明，原位单点测量在粗像素尺度（即公里尺度）捕获表面空间变异信息的能力有限。我们提供的数据集融合了地面观测的时间信息和高分辨率数据的空间信息，是验证和校正异质表面全球表面反照率产品的宝贵资源。据我们所知，该数据集的独特之处在于提供了具有最广泛空间分布和最长时间序列的粗略像素级地面“真相”。该数据集可通过 https://doi.org/10.5281/zenodo.8008454 公开获取（Pan 等人，2023）。
Abstract. In situ measurements from sparsely distributed networks worldwide are a critical source of reference data for validating or correcting biases in satellite products. However, due to the substantial difference in spatial scales between in situ and satellite measurements, the two cannot be compared except for the fact that the underlying surface of in situ sites is absolutely homogeneous. Instead, the in situ measurements needed to be upscaled to be matched with the satellite pixels. Based on the upscaling model, we also proposed the consideration that in situ observation generally lacks spatial representativeness due to the widely distributed spatial heterogeneity, and we have developed a coarse pixel-scale ground “truth” dataset based on ground measurements of 416 in situ sites from the sparsely distributed observation networks. Furthermore, we thoroughly assessed the effectiveness of the dataset at sites with different degrees of spatial representativeness. The results demonstrate that using this dataset in validation outperforms the direct comparison between satellite and in situ site measurements over heterogeneous surfaces when in situ measurement footprints are less than satellite pixel size. The accuracy of the reference data employed for validation or bias correction can be boosted by 17.09 % over the regions with strong spatial heterogeneity. However, the degree of improvement with this dataset displays a decreasing trend with the reduction in spatial heterogeneity. At a global scale, the pixel-scale ground “truth” dataset enhances the accuracy of pixel-scale reference data in general, with the overall relative root-mean-square error (RRMSE) decreasing by 6.04 % compared to in situ single-site measurements. Our results suggest that in situ single-site measurements are limited in their ability to capture surface spatial variability information at a coarse pixel scale (i.e., the kilometer scale). The dataset we provided, which merges temporal information from ground-based observations and spatial information from high-resolution data, represents a valuable resource for validating and correcting worldwide surface albedo products over heterogeneous surfaces. To the best of our knowledge, this dataset is unique in providing a coarse pixel-scale ground “truth” with the widest spatial distribution and longest time series. The dataset is publicly available through https://doi.org/10.5281/zenodo.8008454 (Pan et al., 2023).