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Retrieval of subpixel snow-covered area and grain size from imaging spectrometer data

机译:从成像光谱仪数据中检索亚像素积雪区域和粒度

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摘要

We describe and validate an automated model that retrieves subpixel snow-covered area and effective grain size from Airborne Visible/ Infrared Imaging Spectrometer (AVIRIS) data. The model analyzes multiple endmember spectral mixtures with a spectral library of snow, vegetation, rock, and soil. We derive snow spectral endmembers of varying grain size from a radiative transfer model; spectra for vegetation, rock, and soil were collected in the field and laboratory. For three AVIRIS images of Mammoth Mountain, California that span common snow conditions for winter through spring, we validate the estimates of snow-covered area with fine-resolution aerial photographs and validate the estimates of grain size with stereological analysis of snow samples collected within 2 h of the AVIRIS overpasses. The RMS error for snow-covered area retrieved from AVIRIS for the combined set of three images was 4%. The RMS error for snow grain size retrieved from a 3 x 3 window of AVIRIS data for the combined set of three images is 48 Am, and the RMS error for reflectance integrated over the solar spectrum and over all hemispherical reflectance angles is 0.018.
机译:我们描述并验证了一种自动模型,该模型可从机载可见/红外成像光谱仪(AVIRIS)数据中检索亚像素积雪覆盖的区域和有效晶粒尺寸。该模型使用雪,植被,岩石和土壤的光谱库分析了多个端元光谱混合物。我们从辐射传输模型推导了不同粒度的雪谱最终成员。在野外和实验室收集了植被,岩石和土壤的光谱。对于加利福尼亚州猛mm山的三张AVIRIS图像,这些图像跨越冬季到春季的常见降雪条件,我们使用高分辨率的航空照片验证了积雪面积的估计,并通过对2个范围内收集的雪样进行了立体分析验证了颗粒大小的估计AVIRIS天桥的h。对于三个图像的组合,从AVIRIS检索到的积雪区域的RMS误差为4%。从三个图像的组合集的AVIRIS数据的3 x 3窗口中检索到的雪粒大小的RMS误差为48 Am,在太阳光谱和所有半球反射角上积分的反射率的RMS误差为0.018。

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