Object-based analysis for forest inventory

Lu Wang; Erxue Chen; Zengyuan Li; Wanqiang Yao; Shiming Li

doi:10.1117/12.2031127

26 October 2013 Object-based analysis for forest inventory

Lu Wang, Erxue Chen, Zengyuan Li, Wanqiang Yao, Shiming Li

Proceedings Volume 8921, MIPPR 2013: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications; 89210O (2013) https://doi.org/10.1117/12.2031127
Event: Eighth International Symposium on Multispectral Image Processing and Pattern Recognition, 2013, Wuhan, China

Abstract

As widely used today, high resolution image becomes a useful data source for forest inventory because it can show detailed information of land-cover types which is so helpful in interpreting process. And in the application of high-resolution images, the toughest problem is to find the effective characteristics group to separate each class accurately. In this paper, we tried an object-based method to get the whole forest distribution of the study area. Combining segmentation and decision tree feature selection tool, we tried to find a convenient and effective way to select useful information from such many characteristics brought by ―super-pixels‖ after segmentation. Compared with the traditional pixel-based classification method, we found that object-based method was more appropriate not only for its nearly 10% higher classification accuracy but also providing with more detailed information lying in the image data that help.

Citation Download Citation

Lu Wang, Erxue Chen, Zengyuan Li, Wanqiang Yao, and Shiming Li "Object-based analysis for forest inventory", Proc. SPIE 8921, MIPPR 2013: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 89210O (26 October 2013); https://doi.org/10.1117/12.2031127

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