1. China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing 100083,China 2. AeroImgInfo Technology Co., Ltd., Beijing 100195, China
At present, the extraction accuracy of the forest fire area by synthetic aperture Radar (SAR) is mainly limited to the analysis of single pixel. However, the application study of object-oriented technology based on pixel sets as the analysis unit is less in dealing with SAR images. In this paper, a multi-scale segmentation algorithm based on fractal net evolution approach (FNEA) was applied to the span of ALOS PALSAR images. Through the application research, the forest fire region, which happened in 2009 and was located in the Middle East of Alaska, USA, was extracted. The application validation of the algorithm was verified by comparing the experiment results with the auxiliary data of monitoring trends in burn severity (MTBS) data. The experiment results show that the classification accuracies of one-static span and two-static spans based on object-oriented analysis are improved by 12.7% and 15.8% respectively, compared with precious research. The researches show that object-oriented technology can be effectively applied to the information extraction form SAR image, and SAR technology has potential application in forest fire monitoring.
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Decai JIANG, Wenji LI, Jingmin LI, Zhaofeng BAI. Extraction of the forest fire region based on the span of ALOS PALSAR by object-oriented analysis. Remote Sensing for Land & Resources, 2019, 31(4): 47-52.
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2019, Vol. 31 
