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Journal of Geo-information Science >

2011 , Vol. 13 >Issue 3: 409 - 417

DOI: https://doi.org/10.3724/SP.J.1047.2011.00409

ARTICLES

Optimal Segmentation Scale Selection and Evaluation for Multi-layer Image Recognition and Classification

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  • 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    2. GraduateUniversity of Chinese Academy of Sciences, Beijing 100049, China

Received date: 2010-10-20

  Revised date: 2011-05-23

  Online published: 2011-06-15

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Abstract

With the rapid increase of remote sensing image storage, it becomes more critical for the quick and effective information extraction from remote sensing imagery. As a widely-used method, object-based image analysis (OBIA) has been rapidly developed from the beginning of this century, but the automatic procedure for land use mapping is still problematic facing with geographical complexity. Regarding to the complex feature contents in the imagery of costal zones, this paper presents a method of optimal segmentation scale extraction and an object-based multi-layer classification procedure. The proposed approach mainly contains three parts: segmentation, optimal scale generation and multi-level classification. First, we select the high resolution images as the data source, segment the imagery with series of scale parameters. Then choose the appropriate scales with the curve of local variance (LV) variation. Variation in heterogeneity is explored by evaluating LV plotted against the corresponding scale in order to get different types of the landuse/cover with their own extraction scales. Finally, we classify the image with multi-features, including spectral, shape, texture and spatial relationship. This paper selects the coastal area of Zhuhai, Guangdong Province as the experiment zone, the classification results show that overall accuracy and Kappa index of the new method are better than those of the traditional pixel-based classifiers and object-oriented classifiers based on the single-level segmentation.

Key words： local variance; optimal segmentation scale; multi-level classification; precision evaluation

Cite this article

LI Qin, GAO Xizhang, ZHANG Tao, LIU Kun, GONG Jianming . Optimal Segmentation Scale Selection and Evaluation for Multi-layer Image Recognition and Classification[J]. Journal of Geo-information Science, 2011 , 13(3) : 409 -417 . DOI: 10.3724/SP.J.1047.2011.00409

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