摘要
土壤线是计算垂直干旱指数(perpendicular drought index,PDI)以及各种植被指数过程中的重要参数,准确地估算土壤线至关重要。在基于遥感图像的土壤线估计中,用于估计土壤线的像元通常假设为裸土点,而此假设常常无法满足。针对该情况,文章利用基于土壤线的水含量估计误差,构造目标函数正则项修正土壤线。首先提出了交叉迭代框架,将土壤线估计和水含量估计放在同一框架下,用水含量估计误差修正土壤线,再用改进的土壤线估计水含量,迭代交叉优化求解;然后,为了验证该算法的有效性,在9幅Landsat8时间序列影像上估计土壤线和水含量,并分析水含量估计值与实测值的一致性以及改进的垂直干旱指数(modified perpendicular drought index,MPDI)与实测水含量的负相关性。结果表明,负相关性和水含量估计精度都得到了提高,证明了该文土壤线提取的有效性。
Soil line is an important parameter,which is used to calculate the perpendicular drought index(PDI)and various vegetation indices,so the accurate estimation of soil line is crucial.The pixels used to estimate soil lines are usually assumed to be bare soil points,but this assumption is often impossible to be satisfied.Therefore,using the estimation error of water content based on soil line,the objective function regularization term is constructed to correct the soil line.A cross iterative framework is presented,the estimation of soil line and water content are placed under the same framework,the soil line is corrected by the error of water content estimation,and the water content is estimated by the improved soil line,achieving the cross iterative optimization solution.To verify the validity of the proposed algorithm,soil line and water content are estimated on nine Landsat8 time series images,the consistency between the estimated water content and the measured data,and the negative correlation between the modified perpendicular drought index(MPDI)and the measured water content are analyzed.The improvement of negative correlation and estimation accuracy of water content proves the validity of soil line extraction.
作者
方帅
周亚楠
董张玉
FANG Shuai;ZHOU Yanan;DONG Zhangyu(School of Computer and Information, Hefei University of Technology, Hefei 230601, China;Anhui Province Key Laboratory of Industry Safety and Emergency Technology, Hefei 230601, China)
出处
《合肥工业大学学报（自然科学版）》
CAS
北大核心
2020年第11期1492-1499,共8页
Journal of Hefei University of Technology：Natural Science
基金
国家自然科学基金资助项目(61472380)
中央高校基本科研业务费专项资金资助项目(JD2017JGPY0011,JZ2017HGBZ0930)。
