The multi-source remote sensing data integration and fusion to recognize uninhabited islands

Zhijun Liu; Bo Du; Chenxing Wang

doi:10.1117/12.832410

30 October 2009 The multi-source remote sensing data integration and fusion to recognize uninhabited islands

Zhijun Liu, Bo Du, Chenxing Wang

Proceedings Volume 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications; 74980E (2009) https://doi.org/10.1117/12.832410
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

Many uninhabited islands are far away from the mainland and a lot of management difficulties are caused by above factors. In order to know the situation of the uninhabited islands clearly and timely, it's necessary to use the remote sensing to recognize the uninhabited islands. This paper discusses the remote sensing recognition methods of the relevant characteristics of uninhabited islands based on a wide range of remote sensing data fusion and integration. The first method is using the combination of TM band data to recognize uninhabited islands. The second method is using the spot image data to compare with the spatial island layer to recognize uninhabited islands. The results show that they are effective methods for us to recognize the uninhabited islands and the time could be saved. By contrast, the first method is a useful complement to location the uninhabited islands but is difficult to get the accurate area. The second method is important means to get the relatively accurate area of the uninhabited islands. The high resolution imagery is very useful to recognize the small uninhabited islands and the relatively accurate area could be calculated by overlapped the spatial island layers.

Citation Download Citation

Zhijun Liu, Bo Du, and Chenxing Wang "The multi-source remote sensing data integration and fusion to recognize uninhabited islands", Proc. SPIE 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications, 74980E (30 October 2009); https://doi.org/10.1117/12.832410

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