文章基本信息

标题：Automated Modelling of Multimodal Data Processes in Remote Sensing
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作者：Juan Dávila ; Juan Dávila ; Marek B. Zaremba 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2015
卷号：48
期号：3
页码：1918-1923
DOI：10.1016/j.ifacol.2015.06.367
语种：English
出版社：Elsevier
摘要：Abstract Automated monitoring of bio-geophysical phenomena, especially those occurring in large areas, requires the use of models obtained from remote sensing data. The interaction of multiple components in the optical data flow and the non-ergodicity of the acquisition process can seriously affect the precision of the models. In order to effectively deal with this situation, we are proposing an iterative semi-supervised learning framework that combines regression analysis leading to the final set of models with an iterative classification process, based on support vector machines (SVM) that generates data sets associated with each statistical modality. This paper presents an application of the proposed method in modeling the concentration of water pollutants, particularly chlorophyll-a, in inland waters using multimodal satellite data sets.
关键词：KeywordsMultimodalityremote sensingbio-geophysical modelingsemi-supervised learning