The methods research of deriving bamboo information based on IKONOS image

Zheng Guo; Hong Jiang; Jian Chen; Miaomiao Cheng

doi:10.1117/12.832981

30 October 2009 The methods research of deriving bamboo information based on IKONOS image

Zheng Guo, Hong Jiang, Jian Chen, Miaomiao Cheng

Proceedings Volume 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications; 74982D (2009) https://doi.org/10.1117/12.832981
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

Bamboo is an important forest resource at sub-tropical regions in China, which continuous expansion has taken place in China during the last 20 years. Monitoring its distribution has important significance. It provide a possibility that we can extract accurate information among vegetation types as result of detailed texture features, patterns, optical information can be obtained from IKONOS image. In this paper, Anji Country in Zhejiang province was selected, deriving bamboo information from IKONOS image by using Iterative Self-Organizing Data Analysis Technique(ISODATA) classify method, Decision Tree method based on NDVI and texture and Object-oriented classification algorithm based on texture and spectral bands were discussed. The results showed that Decision Tree method based on NDVI and texture demonstrated high accuracy (Kappa=0.7428). Additional, Object-oriented classification algorithm based on texture and spectral bands suggested the highest user's accuracy 93% and producer's 78% at deriving bamboo information, which can be adapted to deriving bamboo information from IKONOS image at subtropical regions in China.

Citation Download Citation

Zheng Guo, Hong Jiang, Jian Chen, and Miaomiao Cheng "The methods research of deriving bamboo information based on IKONOS image", Proc. SPIE 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications, 74982D (30 October 2009); https://doi.org/10.1117/12.832981

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KEYWORDS

Vegetation

Earth observing sensors

High resolution satellite images

Image classification

Spatial resolution

Remote sensing

Algorithm development

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