移动生态监测平台多光谱数据处理的数学模型

… ЧернецкаяИ.ВМатематическаямодельобработки, С. В. Спевакова, А. Г. Спеваков, И. В. Чернецкая, Svetlana S. Spevakova, A. Spevakov, Irina V. Chernetskaya
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引用次数: 0

摘要

研究的目的是对多光谱数据处理过程进行数学论证,以检测局部环境污染区域,并有可能对污染物进行分类。方法。基于多维特征函数和泛函方程的随机系统应用理论的基本原理被用作基本的数学工具。在确定污染物时,使用反映物体服从朗伯定律的能力的标准。为了解决目标分类问题,采用了二元逻辑回归的方法。采用统计学分析方法对研究结果进行评价。结果。得到的部分数学模型使我们能够考虑到影响移动环境监测平台在自动模式下运行的许多因素。证实对当地环境污染区域进行远程分析的可能性,具有确定碳氢化合物、磷酸盐离子等污染物的可能性,以及查找未经许可的建筑场所和生活垃圾的可能性。在确定所选对象的参数时,由于对不同光谱范围内获得的数据进行了处理,其精度特性提高了1,3倍。考虑到有限光谱范围内的输入数据量,降低了参考对象的分辨率,在不影响分类精度的前提下,将分类算法的计算复杂度降低了1.1倍。结论。建立了一个数学模型,用于处理自主移动环境监测平台多光谱设备运行期间在多个光谱范围内获得的数据和图像,从而可以从移动平台识别设备视场中的物体,从而获得相对于所使用的坐标系的空间参考的工作场景物体的详细图像。其显著特点是提高了局部污染区域坐标计算的精度,提高了基于不同光谱范围内扩散反射率特征对目标进行分类的可靠性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mathematical Model of Multispectral Data Processing for a Mobile Ecology Monitoring Platform
   The purpose of research is a mathematical justification of the process of processing multispectral data in order to detect local environmental pollution zones with the possibility of classifying the pollutant.   Methods. The fundamentals of the applied theory of stochastic systems based on equations for multidimensional characteristic functions and functionals are used as a basic mathematical apparatus. When determining a contaminant, a criterion reflecting the ability of objects obeying Lambert's law is used. To solve the problem of object classification, approaches using binary logistic regression are applied. Statistical methods of analysis were used to evaluate the results of the study.   Results. The obtained partial mathematical models allow us to take into account many factors affecting mobile environmental monitoring platforms operating in automatic mode. Substantiate the possibility of remote analysis of local environmental pollution zones, with the possibility of determining pollutants such as hydrocarbons, phosphate ions, etc., as well as searching for unauthorized locations of construction and household garbage. They increase the accuracy characteristics by 1,3 times when determining the parameters of selected objects due to the processing of data obtained in various spectral ranges. They contribute to reducing the computational complexity of the classification algorithm by 1,1 times, taking into account the volume of input data in a limited spectral range and reducing the resolution of the reference object, while not affecting the accuracy of classification.   Conclusion. A mathematical model has been developed for processing data and images obtained in several spectral ranges during the operation of a multispectral device for an autonomous mobile environmental monitoring platform, which makes it possible to identify objects in the field of view of the device from a mobile platform, to obtain a detailed image of working scene objects with spatial reference relative to the coordinate system used, a distinctive feature of which is to increase the accuracy of calculating the coordinates of local zones pollution, and increasing the reliability of the classification of objects based on the characteristics of diffusive reflectivity in various spectral ranges.
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