Applicability of category decomposition for the fusion of multi-resolution data

S. Takeuchi, A. Inanaga
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引用次数: 1

Abstract

The authors tested the applicability of the category decomposition method based on the linear mixture model for the fusion of multiple-resolution satellite data such as Landsat-TM and NOAA-AVHRR. The goal of the application of this method is to estimate the mixing ratio of different categories within one pixel of the lower-resolution data using the classification result of the higher-resolution data, which is considered to be useful for the extrapolation of the information from the higher-resolution data over the wider coverage of the lower-resolution data. The authors tested the estimation accuracy by two kinds of decomposition methods, the maximum likelihood estimation and the minimum distance estimation and also by the multiple regression method. The experimental results showed that the most adequate estimation was obtained by the category decomposition based on the minimum distance estimation.
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分类分解在多分辨率数据融合中的适用性
对基于线性混合模型的分类分解方法在Landsat-TM和NOAA-AVHRR等多分辨率卫星数据融合中的适用性进行了验证。该方法的应用目标是利用高分辨率数据的分类结果估计低分辨率数据的一个像素内不同类别的混合比例,这被认为有助于将高分辨率数据的信息外推到低分辨率数据的更大覆盖范围。采用最大似然估计和最小距离估计两种分解方法以及多元回归方法对估计精度进行了检验。实验结果表明,基于最小距离估计的分类分解方法得到了最充分的估计。
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期刊介绍: Remote Sensing Information is a bimonthly academic journal supervised by the Ministry of Natural Resources of the People's Republic of China and sponsored by China Academy of Surveying and Mapping Science. Since its inception in 1986, it has been one of the authoritative journals in the field of remote sensing in China.In 2014, it was recognised as one of the first batch of national academic journals, and was awarded the honours of Core Journals of China Science Citation Database, Chinese Core Journals, and Core Journals of Science and Technology of China. The journal won the Excellence Award (First Prize) of the National Excellent Surveying, Mapping and Geographic Information Journal Award in 2011 and 2017 respectively. Remote Sensing Information is dedicated to reporting the cutting-edge theoretical and applied results of remote sensing science and technology, promoting academic exchanges at home and abroad, and promoting the application of remote sensing science and technology and industrial development. The journal adheres to the principles of openness, fairness and professionalism, abides by the anonymous review system of peer experts, and has good social credibility. The main columns include Review, Theoretical Research, Innovative Applications, Special Reports, International News, Famous Experts' Forum, Geographic National Condition Monitoring, etc., covering various fields such as surveying and mapping, forestry, agriculture, geology, meteorology, ocean, environment, national defence and so on. Remote Sensing Information aims to provide a high-level academic exchange platform for experts and scholars in the field of remote sensing at home and abroad, to enhance academic influence, and to play a role in promoting and supporting the protection of natural resources, green technology innovation, and the construction of ecological civilisation.
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