摘要
森林环境的多变性导致该地区的卫星遥感图像测量数据易产生偏差。以优化森林遥感图像的监测效果为目的,在污染误差模型的支持下,设计了一种森林遥感图像测量数据偏差影响分析方法。利用污染误差模型调整森林遥感图像,降低因测量数据出现观测异常而产生的影响。运用随机函数多项拟合过程生成包含配准误差的新遥感图像,并对新图像进行几何精矫正,从而确定不同多光谱波段配准误差对图像测量数据偏差的影响。分析实验数据可知,遥感图像的配准误差会监测效果产生明显的影响,且影响程度会随着误差大小的变化而变化,证明上述方法能够有效实现对森林遥感图像测量数据偏差的影响分析。
The variability of forest environment leads to the deviation of satellite remote sensing image measurement data in this area. In order to optimize the monitoring effect of forest remote sensing image, a deviation impact analysis method of forest remote sensing image measurement data was designed with the support of pollution error model. Firstly, the pollution error model was applied to adjust the forest remote sensing image in order to reduce the impact caused by data error. Secondly, according to the multiple fitting process of random function, a new remote sensing image containing registration error was generated. Then, the newly generated image was geometrically corrected. Finally, the influence of registration error in different multispectral bands on the deviation of image measurement data was determined. The results show that the registration error directly determines the image monitoring effect, and the registration error can be effectively reduced by using this method.
作者
朱发财
许济金
ZHU Fa-cai;XU Ji-jin(School of Computing and Information Science,Fuzhou Institute of Technology,Fuzhou Fujian 350506,China;Digital Fujian Internet of Vehicles Lab,Fuzhou Institute of Technology,Fuzhou Fujian 350506,China;College of Mechanical and Electrical Engineering,Fujian Agriculture and Forestry University,Fuzhou Fujian 350002,China)
出处
《计算机仿真》
北大核心
2021年第11期62-66,共5页
Computer Simulation
基金
数字福建车联网实验室开放课题(Kfkt2018008)。
关键词
污染误差模型
森林遥感图像
测量数据
配准误差
Pollution error model
Forest remote sensing image
Measurement data
Registration error
