基于主动微波遥感数据和光学遥感数据的干旱区绿洲棉花地表多尺度土壤湿度反演研究

The project is focused on the multi-scale soil moisture estimation in a cotton field of the arid region, using the multi-polarization, multi-angle ASAR data and TM, MODIS optical remote sensing data. Firstly, characteristics of the bare soil backscattering is simulated based on the AIEM (Advance Integrated Equation Model) model, in combination of the measured data, the optimal mode of the ASAR data to estimate soil moisture will be given, then, the model to estimate soil moisture will be built based on multi-polarization, multi-angle ASAR mode. Secondly, the backscattering character of the cotton field is simulated based on the michigan microwave canopy scattering (MMICS) model and water-cloud model, the relation between canopy scattering of cotton, the two-way vegetation transmissivity and the multi-polarization multi-angle ASAR data, optical remote sensing data will be built. The model to estimate soil moisture in a cotton area will be built based on the fusion of SAR and optical remote sensing data, removing the influence of the canopy scattering in soil moisture estimation. Finally, the estimation results of the multi-scale soil moisture in a bare soil and in a cotton field will be compared using the measured data, to study the scale problem in soil moisture estimation, and providing theoretical basis for the multi-scale soil moisture estimation in arid area with a high precision.

本项目以干旱区棉花地多尺度土壤湿度遥感反演为目标，利用多极化、多角度C波段ASAR数据和TM、MODIS光学卫星数据。首先，基于AIEM模型模拟裸露地表后向散射特征，结合试验数据，寻找ASAR数据裸地土壤湿度反演的最佳模式，建立基于不同模式ASAR数据土壤湿度反演模型,并比较反演精度。其次，利用“水云”模型和MIMICS模型模拟分析，探讨棉花地后向散射特征，寻找C波段棉花冠层散射、双程透过率与多角度、多极化ASAR数据或两种尺度光学遥感数据光谱特征之间的关系，去除冠层散射对土壤湿度反演的影响，建立融合ASAR和光学遥感数据的棉花覆盖地表土壤湿度反演模型。最后，利用遥感数据和实测数据比较裸露和棉花覆盖地表多尺度土壤湿度反演结果，探讨土壤湿度反演的尺度问题，为干旱区高精度、多尺度土壤湿度反演提供理论基础。

本项目研究了干旱区棉花覆盖地表土壤湿度主动微波遥感反演方法。首先利用全极化雷达数据进行研究区地表分类，提取研究区棉花覆盖地表，进而进行土壤湿度反演研究。对于苗期棉花覆盖地表，视为裸地，利用多角度RADARSAT-2微波遥感数据，基于AIEM模型模拟，去除粗糙度影响，建立了裸土土壤湿度反演方法。对于棉花覆盖地表，基于“水-云”模型，结合AIEM模型，确定了“水-云”模型关键参数，利用多时相RADARSAT-2数据去除粗糙度对后向散射影响，利用光学遥感数据去除植被覆盖对后向散射影响，建立了基于多时相、多角度主动微波遥感数据和光学遥感数据的棉花覆盖地表土壤湿度反演半经验模型。利用Landsat-8 OLI 和MODIS 两种不同尺度分辨率光学遥感数据，反演了干旱区棉花覆盖地表土壤湿度。为干旱区高精度土壤湿度多源遥感数据反演提供技术基础。