A method for constructing a reference dataset for the validation of remote sensing products
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摘要: 遥感产品真实性检验是遥感产品质量评估的必要环节,确保了遥感产品应用的可靠性和有效性。针对现有遥感产品真实性检验缺乏区域级以上的大范围工程化参考数据集的现状,提出了基于交叉验证的真实性检验参考数据集构建方法,利用已验证精度的Landsat8 OLI数据,构建了中国范围内分幅、分时管理的参考数据集,最终建立年度最优参考数据集,形成的参考数据集具备了易于检索、易于更新、可以大范围构建的特点。按照中心波长匹配了ZY1E高光谱的7个波段,投入到ZY1E影像的反射率真实性检验生产中,通过计算地表真值数据与自动评级结果的混淆矩阵,得到总体精度达到了87%,Kappa系数达到0.83,结果满足了工程化应用的要求。提出的参考数据集构建方法为大范围、工程化的遥感产品真实性检验提供了技术支持。Abstract: The validation of remote sensing products (RSPs) is necessary for the quality assessment of RSPs in order to ensure the reliable and effective application of RSPs. However, the existing validation of RSPs lacks large-scale engineering reference datasets above the regional level. In view of this fact, this study proposed a cross-validation-based method for constructing a reference dataset for RSP validation. First, a reference dataset of China organized by sheet and time was constructed using the Landsat8 OLI data whose accuracy had been verified. Then, the annual optimal reference dataset, which was easy to retrieve and update and enabled large-scale construction, was formed finally. After seven bands of the ZY1E hyperspectrum were matched according to the center wavelength, the reference dataset was used to verify the reflectance of ZY1E images. The calculation of the confusion matrix between ground truth (GT) data and automatic rating results yielded an overall accuracy of 87% and a Kappa coefficient of 0.83, meeting the requirements for engineering applications. The method for constructing a reference dataset proposed in this study provides technical support for large-scale, engineering-oriented RSP validation.
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Key words:
- validation /
- cross-validation /
- reference dataset /
- engineering application
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