基于形态属性剖面的遥感数据分类:十年进展

IF 16.2 1区地球科学 Q1 GEOCHEMISTRY & GEOPHYSICS IEEE Geoscience and Remote Sensing Magazine Pub Date : 2021-09-01 DOI:10.1109/MGRS.2021.3051859

D. S. Maia, M. Pham, E. Aptoula, Florent Guiotte, S. Lefèvre

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引用次数: 7

摘要

形态属性轮廓(APs)是遥感影像空间光谱像元分析的重要方法之一。自十年前引入土地覆盖分类以来，许多研究都对最新技术做出了贡献，不仅关注它们在更广泛任务中的应用，而且关注它们的性能改进和扩展到更复杂的地球观测数据。

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Classification of Remote Sensing Data With Morphological Attribute Profiles: A decade of advances

Morphological attribute profiles (APs) are among the most prominent methods for spatial–spectral pixel analysis of remote sensing images. Since their introduction a decade ago to tackle land cover classification, many studies have been contributed to the state of the art, focusing not only on their application to a wider range of tasks but also on their performance improvement and extension to more complex Earth observation data.

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来源期刊

IEEE Geoscience and Remote Sensing Magazine Computer Science-General Computer Science

CiteScore

20.50

自引率

2.70%

发文量

期刊介绍： The IEEE Geoscience and Remote Sensing Magazine (GRSM) serves as an informative platform, keeping readers abreast of activities within the IEEE GRS Society, its technical committees, and chapters. In addition to updating readers on society-related news, GRSM plays a crucial role in educating and informing its audience through various channels. These include:Technical Papers,International Remote Sensing Activities,Contributions on Education Activities,Industrial and University Profiles,Conference News,Book Reviews,Calendar of Important Events.