SUN Yonghua, GONG Huili, LI Xiaojuan, et al. Extracting Eco-hydrological Information of Inland Wetland from L-band Synthetic Aperture Radar Image in Honghe National Nature Reserve, Northeast China[J]. Chinese Geographical Science, 2011, 21(2): 241-248.
Citation: SUN Yonghua, GONG Huili, LI Xiaojuan, et al. Extracting Eco-hydrological Information of Inland Wetland from L-band Synthetic Aperture Radar Image in Honghe National Nature Reserve, Northeast China[J]. Chinese Geographical Science, 2011, 21(2): 241-248.

Extracting Eco-hydrological Information of Inland Wetland from L-band Synthetic Aperture Radar Image in Honghe National Nature Reserve, Northeast China

  • Publish Date: 2011-03-24
  • Taking a typical inland wetland of Honghe National Nature Reserve (HNNR), Northeast China, as the study area, this paper studied the application of L-band Synthetic Aperture Radar (SAR) image in extracting eco-hydrological information of inland wetland. Landsat-5 TM and ALOS PALSAR HH backscatter images were first fused by using the wavelet-IHS method. Based on the fused image data, the classification method of support vector machines was used to map the wetland in the study area. The overall mapping accuracy is 77.5%. Then, the wet and dry aboveground biomass estimation models, including statistical models and a Rice Cloudy model, were established. Optimal parameters for the Rice Cloudy model were calculated in MATLAB by using the least squares method. Based on the validation results, it was found that the Rice Cloudy model produced higher accuracy for both wet and dry aboveground biomass estimation compared to the statistical models. Finally, subcanopy water boundary information was extracted from the HH backscatter image by threshold method. Compared to the actual water borderline result, the extracted result from L-band SAR image is reliable. In this paper, the HH-HV phase difference was proved to be valueless for extracting subcanopy water boundary information.
  • 加载中
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Article Metrics

Article views(1230) PDF downloads(18) Cited by()

Proportional views
Related

Extracting Eco-hydrological Information of Inland Wetland from L-band Synthetic Aperture Radar Image in Honghe National Nature Reserve, Northeast China

Abstract: Taking a typical inland wetland of Honghe National Nature Reserve (HNNR), Northeast China, as the study area, this paper studied the application of L-band Synthetic Aperture Radar (SAR) image in extracting eco-hydrological information of inland wetland. Landsat-5 TM and ALOS PALSAR HH backscatter images were first fused by using the wavelet-IHS method. Based on the fused image data, the classification method of support vector machines was used to map the wetland in the study area. The overall mapping accuracy is 77.5%. Then, the wet and dry aboveground biomass estimation models, including statistical models and a Rice Cloudy model, were established. Optimal parameters for the Rice Cloudy model were calculated in MATLAB by using the least squares method. Based on the validation results, it was found that the Rice Cloudy model produced higher accuracy for both wet and dry aboveground biomass estimation compared to the statistical models. Finally, subcanopy water boundary information was extracted from the HH backscatter image by threshold method. Compared to the actual water borderline result, the extracted result from L-band SAR image is reliable. In this paper, the HH-HV phase difference was proved to be valueless for extracting subcanopy water boundary information.

SUN Yonghua, GONG Huili, LI Xiaojuan, et al. Extracting Eco-hydrological Information of Inland Wetland from L-band Synthetic Aperture Radar Image in Honghe National Nature Reserve, Northeast China[J]. Chinese Geographical Science, 2011, 21(2): 241-248.
Citation: SUN Yonghua, GONG Huili, LI Xiaojuan, et al. Extracting Eco-hydrological Information of Inland Wetland from L-band Synthetic Aperture Radar Image in Honghe National Nature Reserve, Northeast China[J]. Chinese Geographical Science, 2011, 21(2): 241-248.

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return