时空谱互补观测数据的融合重建方法研究
发布时间：2018-10-08 10:22
【摘要】：随着空间信息观测技术的提高,人们已经可以利用各种不同的观测方式获取地表空间信息。但是在观测过程中,由于观测方式本身的限制、观测环境的影响和观测平台故障等多方面因素的影响,大量的空间观测数据中都存在空间不连续的现象。这种“空间缝隙”为空间观测数据的后续使用带来了严重影响。因此,如何消除观测数据中的无效信息,获得空间无缝的空间观测数据是一个具有重要意义的研究课题。 本文从时间信息互补、光谱信息互补、空间信息互补多个角度出发,研究了： (1)基于谱段互补信息的遥感数据融合重建方法 针对高光谱或多光谱遥感影像中由与某一谱段传感器故障或噪声等因素引起的观测信息空间不连续问题,利用影像数据中的光谱冗余信息,寻找多波段数据间的相似性,在此基础上建立多波段数据间的关系,消除离群点现象的影响对空间不连续区域进行重建。 (2)基于时相互补信息的遥感数据融合重建方法 针对遥感影像中由观测环境和传感器故障等因素引起的观测信息空间不连续问题,在对多时相数据的差异性进行分析的基础上,建立多时相数据相似信息提取方法,克服复杂场景变化和离群点等因素带来的负面影响,结合时域补充信息对空间不连续区域进行融合。 (3)基于空间互补信息的点-面融合方法 由于遥感数据观测范围广但反演精度受限于多种因素,传统的地表观测数据精度虽高但观测点往往过于离散难。针对此问题,本文拟通过分析遥感成像过程中各因素的相互作用,建立站点-遥感数据之间的关联模型,研究基于地统计学的站点-遥感数据融合方法,并将其应用于京津冀地区大气污染物监测。
[Abstract]:With the improvement of spatial information observation technology, people can obtain surface spatial information by various observation methods. However, in the observation process, because of the limitation of the observation mode itself, the influence of the observation environment and the fault of the observation platform, there is spatial discontinuity in a large number of spatial observation data. This space gap has a serious impact on the subsequent use of space observation data. Therefore, how to eliminate the invalid information in the observation data and obtain the spatial observation data seamlessly is an important research topic. This paper starts from the complementary of time information, spectral information and spatial information. In this paper: (1) remote sensing data fusion and reconstruction based on spectral complementary information is applied to the observation of hyperspectral or multispectral remote sensing images caused by sensor fault or noise in a certain spectral segment. Discontinuity of information space, The spectral redundancy information in image data is used to search for the similarity between multi-band data. Based on this, the relationship between multi-band data is established, and the spatial discontinuous region is reconstructed by eliminating the influence of outliers. (2) the method of remote sensing data fusion reconstruction based on time-complementary information is aimed at the spatial discontinuity of observation information caused by observation environment and sensor fault in remote sensing image. Based on the analysis of the difference of multitemporal data, a method of extracting similar information from multitemporal data is established to overcome the negative effects of complex scene changes and outliers, etc. The spatial discontinuous region is fused with time domain supplementary information. (3) the point-surface fusion method based on spatial complementary information is difficult to discrete because of the wide observation range of remote sensing data and limited inversion accuracy due to many factors. In order to solve this problem, through analyzing the interaction of various factors in the process of remote sensing imaging, this paper proposes to establish the correlation model of site-remote sensing data, and to study the method of site-remote sensing data fusion based on geostatistics. It is applied to the monitoring of air pollutants in Beijing, Tianjin and Hebei.
【学位授予单位】：武汉大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：TP751
本文编号：2256417
[Abstract]:With the improvement of spatial information observation technology, people can obtain surface spatial information by various observation methods. However, in the observation process, because of the limitation of the observation mode itself, the influence of the observation environment and the fault of the observation platform, there is spatial discontinuity in a large number of spatial observation data. This space gap has a serious impact on the subsequent use of space observation data. Therefore, how to eliminate the invalid information in the observation data and obtain the spatial observation data seamlessly is an important research topic. This paper starts from the complementary of time information, spectral information and spatial information. In this paper: (1) remote sensing data fusion and reconstruction based on spectral complementary information is applied to the observation of hyperspectral or multispectral remote sensing images caused by sensor fault or noise in a certain spectral segment. Discontinuity of information space, The spectral redundancy information in image data is used to search for the similarity between multi-band data. Based on this, the relationship between multi-band data is established, and the spatial discontinuous region is reconstructed by eliminating the influence of outliers. (2) the method of remote sensing data fusion reconstruction based on time-complementary information is aimed at the spatial discontinuity of observation information caused by observation environment and sensor fault in remote sensing image. Based on the analysis of the difference of multitemporal data, a method of extracting similar information from multitemporal data is established to overcome the negative effects of complex scene changes and outliers, etc. The spatial discontinuous region is fused with time domain supplementary information. (3) the point-surface fusion method based on spatial complementary information is difficult to discrete because of the wide observation range of remote sensing data and limited inversion accuracy due to many factors. In order to solve this problem, through analyzing the interaction of various factors in the process of remote sensing imaging, this paper proposes to establish the correlation model of site-remote sensing data, and to study the method of site-remote sensing data fusion based on geostatistics. It is applied to the monitoring of air pollutants in Beijing, Tianjin and Hebei.
【学位授予单位】：武汉大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：TP751
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