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Global Land Surface Emissivity Estimation From AMSR2 Observations

机译:基于AMSR2观测值的全球陆地表面发射率估算

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A reliable estimate of emissivity is critical for a wide range of applications for the atmosphere, the biosphere, the lithosphere, the cryosphere, and the hydrosphere. This study uses three years (August 2012 to July 2015) of data from the Advanced Microwave Scanning Radiometer-2 sensor that is onboard the Global Change Observation Mission 1st Water satellite to explore estimates of instantaneous global land emissivity. A method is adopted to remove the known inconsistency in penetration depths between microwave brightness temperatures and infrared-based ancillary data that could cause differences between day and night emissivity estimates. After removing the diurnal atmospheric effects, the resulting retrieved cloud-free land emissivities realistically represent well-known large-scale features. As expected, the polarization differences of estimated emissivities show noticeable seasonal variations over the deciduous woodland and grassland regions due to changes in vegetation density. The potential of estimated emissivities for high-latitude snow detection and freeze/thaw state identification is also demonstrated.
机译:对于大气,生物圈,岩石圈,冰冻圈和水圈的广泛应用,可靠的发射率估算至关重要。这项研究使用了三年(2012年8月至2015年7月)来自高级微波扫描辐射计2传感器的数据,该传感器安装在全球变化观测团第一水卫星上,用于探索瞬时全球陆地发射率的估计值。采用了一种方法来消除已知的微波亮度温度与基于红外的辅助数据之间的穿透深度不一致的问题,这种不一致可能导致昼夜发射率估计之间存在差异。消除昼夜大气影响后,所得的无云土地发射率实际上代表了众所周知的大规模特征。正如预期的那样,由于植被密度的变化,估计的发射率的极化差异显示出在落叶林地和草地上的明显季节性变化。还展示了高纬度积雪和冻结/融化状态识别的估计发射率的潜力。

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