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首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing >An Improved Topography-Coupled Kernel-Driven Model for Land Surface Anisotropic Reflectance
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An Improved Topography-Coupled Kernel-Driven Model for Land Surface Anisotropic Reflectance

机译:一种改进的地形耦合核驱动模型,用于陆地表面各向异性反射率

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摘要

The semiempirical kernel-driven model is commonly used for global surface reflectance characterization because of its simplicity and underlying physical meaning. However, the current kernel-driven reflectance models assume that the terrain is flat and homogeneous, and can induce significant errors in the surface reflectance estimation and subsequent parameter retrievals over rugged terrain. In this study, an improved topography-coupled kernel-driven (TCKD) reflectance model with the correction of diffuse skylight effects was proposed based on the diffused-equivalent slope model (dESM) and RossThick-LiTransit (RTLT) kernel-driven model. The TCKD model & x2019;s accuracy and effectiveness were evaluated using surface reflectance simulated by the radiosity approach and the Moderate Resolution Imaging Spectroradiometer (MODIS) data. Against simulated data, the results show that the TCKD model can accurately capture the distortion of the reflectance shape and hemispherical distribution caused by the topographic effects. Compared to MODIS data, the TCKD model has an overall better performance than the RTLT model across different spatial scales and land cover types. When the mean slope is larger than 35 & x00B0; at the 500-m resolution, the TCKD model & x2019;s near-infrared (NIR) root-mean-square error (RMSE) and the regression slope of the fitting line are 0.037 and 0.752, respectively, whereas those of the RTLT model are 0.049 and 0.645. Neglecting the diffuse skylight in the TCKD model can also lead to great bias in the reflectance retrievals. When the mean slope is 31 & x00B0;, as the ratio of diffuse skylight varies from 0 to 1, the NIR RMSE of the TCKD model decreases from 0.012 to 0.005, whereas that increases from 0.012 to around 0.02 if the diffuse skylight effects are neglected. These preliminary results demonstrate that the TCKD model is capable of improving the fitting ability of the kernel-driven model over rugged terrain and provides potentials for better retrieving and interpreting land surface parameters such as land surface albedo in mountainous areas.
机译:半透镜核驱动模型通常用于全局表面反射率表征,因为其简单性和潜在的物理意义。然而,目前的内核驱动的反射模型假设地形是平坦的,并且可以在表面反射率估计和随后的参数检索在坚固的地形上引起显着的误差。在该研究中,基于扩散当量斜率模型(DESM)和ROSSTHICK-LITRANSIT(RTLT)内核驱动模型,提出了一种改进的地形耦合核驱动(TCKD)反射模型,其校正弥补漫射天窗效应。使用通过通过光学性方法和中度分辨率成像分光辐射计(MODIS)数据模拟的表面反射率来评估TCKD模型和X2019; S的精度和有效性。针对模拟数据,结果表明,TCKD模型可以精确地捕获由地形效果引起的反射形状和半球分布的变形。与MODIS数据相比,TCKD模型具有比不同空间尺度和陆地覆盖类型跨越RTLT模型的更好的性能。当平均斜率大于35&x00b0时;在500米的分辨率下,TCKD模型和X2019;近红外(NIR)根均方误差(RMSE)和配料线的回归斜率分别为0.037和0.752,而RTLT模型的近似是0.049和0.645。忽视TCKD模型中的漫反射天窗也可能导致反射率检索中的大偏差。当平均斜率为31&x00b0;,随着漫射天窗的比例从0到1的比例变化,TCKD模型的NIR RMSE从0.012降低到0.005,而如果漫反射天际效应被忽略,则从0.012增加到约0.02。 。这些初步结果表明,TCKD模型能够提高内核驱动模型在坚固的地形上的拟合能力,并提供更好地检索和解释山区土地表面参数的潜在潜在的潜力。

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    Chinese Acad Sci State Key Lab Remote Sensing Sci Inst Remote Sensing & Digital Earth Beijing 100101 Peoples R China|Univ Chinese Acad Sci Coll Resources & Environm Beijing 100049 Peoples R China;

    Chinese Acad Sci State Key Lab Remote Sensing Sci Inst Remote Sensing & Digital Earth Beijing 100101 Peoples R China|Univ Chinese Acad Sci Coll Resources & Environm Beijing 100049 Peoples R China;

    Chinese Acad Sci State Key Lab Remote Sensing Sci Inst Remote Sensing & Digital Earth Beijing 100101 Peoples R China|Univ Chinese Acad Sci Coll Resources & Environm Beijing 100049 Peoples R China;

    Chinese Acad Sci State Key Lab Remote Sensing Sci Inst Remote Sensing & Digital Earth Beijing 100101 Peoples R China;

    Chinese Acad Sci State Key Lab Remote Sensing Sci Inst Remote Sensing & Digital Earth Beijing 100101 Peoples R China;

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  • 正文语种 eng
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  • 关键词

    Anisotropic reflectance; composite sloping terrain; diffuse skylight; kernel-driven model; rugged terrain; topographic effects;

    机译:各向异性反射率;复合倾斜地形;弥漫性天窗;内核驱动的模型;崎岖的地形;地形效果;

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