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韩 玲,张延成.光学与微波数据协同反演植被覆盖区土壤水分水资源与水工程学报[J].,2018,29(4):230-235
光学与微波数据协同反演植被覆盖区土壤水分
Synergistic inversion of soil moisture in vegetation-covered area based on optical and microwave data
  
DOI:10.11705/j.issn.1672-643X.2018.04.39
中文关键词:  土壤水分  植被含水量  水云模型  AIEM模型  协同反演
英文关键词:soil moisture  vegetation water content  water-cloud model  AIEM model  synergistic inversion
基金项目:国家重大高分专项(GFZX04040202-07)
作者单位
韩 玲,张延成 (长安大学 地质工程与测绘学院 陕西 西安 710054) 
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中文摘要:
      基于LandSat5 TM和ENVISAT-1 ASAR数据,通过水云模型剔除了植被层对雷达后向散射系数的影响,利用AIEM模型对黑河中游植被覆盖地表的土壤水分进行了反演。建立植被含水量(Mveg;水云模型中关键参数)与多种植被指数之间的响应关系,发现比值植被指数(RVI)反演的植被含水量精度较高(R2=0.71);去除植被影响后,利用AIEM模型建立LUT表,基于VV和VH极化的后向散射系数,通过查表法反演研究区的土壤水分。对比野外实测数据与反演结果,发现VV极化数据反演结果较好(R2=0.74)。考虑了植被覆盖层对后向散射系数的影响,该方法更适用于植被覆盖地表的土壤水分反演。
英文摘要:
      Based on Landsat5 TM and ENVISAT-1 ASAR data, the effect of vegetation on the backscatter coefficient was removed by water-cloud model, and the surface soil moisture in the middle reaches of Heihe River was simulated using AIEM model. By establishing the relationship between vegetation water content(Mveg; the key parameter of water-cloud model) and multiple vegetation indexes, it was found that the accuracy of vegetation water content inversion by RVI was higher (R2=0.71). After removing the vegetation effect, the LUT table was established with AIEM model, and the soil moisture is estimated by the look-up table method based on the VV and VH polarization backscattering coefficients. Comparing the inversion results with field measured data, the study suggests that the VV inversion result is better (R2=0.74). Considering the influence of vegetation on radar backscatter coefficient, the proposed method is more suitable for inversion of soil moisture in vegetation-covered area.
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