Fusion algorithm for the information of lake boundary integration from multi-temporalremote sensing images

Abstract

为了有效改善遥感影像提取湖泊边界信息的可靠性和精度,减少人为误差,提出了一种利用多时相遥感影像提取边界信息的加权平均融合算法以及误差的域法修正处理方法.结果表明,该方法能有效融合各时相影像信息,提高湖泊边界信息提取的可靠性,并且对融合时相变化较大的湖泊边界都有一定的普适性.通过融合算法提取的呼伦湖面积为1928.35km²,修正后的面积为1929.85km².通过利用地统计学理论对算法的验证及误差分析,得出相对误差空间变异拟合模型的块金方差与基台值之比都小于25%,具有很强的空间相关性,修正后的数据空间相关性要优于融合数据,空间变程也得到了有效地降低,显示修正后的数据对半方差函数理论模型的拟合程度更好.;For improving the reliability and accuracy of lake boundary integration information from remote sensing images andreducing human error, this paper put forwards a weighted average algorithm for integrating of the border information extracted byusing the multi-temporal remote sensing images, and a processing approach of error interzone correction which can integrate thevarious temporal information effectively and improve the reliability of extracting the lake border information. According to thisfusion algorithm the area of Lake Hulun is 1928.35km². Using the geostatistics theory to validate the errors, the area is 1929.85km².The results illuminated that the ratio of nugget to sill is less than 25%, and the spatial correlation of the corrected data is superior tothat of the integrated data. Furthermore the spatial variation range has been reduced effectively, and the extent of fitting thetheoretical model is better in the corrected data than the original data.