Remote sensing image classification development in the past decade

Yan Li; Li Yan; Jin Liu

doi:10.1117/12.832872

30 October 2009 Remote sensing image classification development in the past decade

Yan Li, Li Yan, Jin Liu

Proceedings Volume 7494, MIPPR 2009: Multispectral Image Acquisition and Processing; 74941D (2009) https://doi.org/10.1117/12.832872
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

Remote sensing image classification is a prerequisite for remote sensing applications, such as thematic mapping, urban planning, forest management, environment monitoring, disaster warning and assessment, military target recognition. Over the last decade there has been noticeable shift in remote sensing image classification with the extension of remote sensing imagery sources as well as the development of pattern recognition methods. This paper discusses the changes in remote sensing classification from two aspects: basic thought and new classification algorithms. The basic thought of remote sensing classification has changed from per-pixel multispectral-based approaches to multiscale object-based approaches. New classification algorithms include support vector machine, evolutionary algorithm, fuzzy clustering algorithm, as well as Artificial Neural Networks. At last this paper highlights the future research and application directions of remote sensing image classification.

Citation Download Citation

Yan Li, Li Yan, and Jin Liu "Remote sensing image classification development in the past decade", Proc. SPIE 7494, MIPPR 2009: Multispectral Image Acquisition and Processing, 74941D (30 October 2009); https://doi.org/10.1117/12.832872

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