The present study was undertaken in the Chenab basin, western Himalayas to explore the effect of shadow on atmospherically and topographically corrected normalized difference snow index (NDSI) values. The research was conducted using the Landsat-8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) datasets of two time periods i.e., February 2015 and February 2018. Our results suggested that total snow cover area (SCA) computed using NDSI from raw satellite images, under estimated SCA (viz. 10,938.66 and 7739.97 Km²); relative to atmospherically corrected (AC) (14,819.01 and 11,199.7 Km²) and topographically corrected (TC) (14,882.07 and 11,188.18 Km²) images during both the time periods (i.e., 2015 and 2018, respectively). This is mainly due to the non-identification of snow pixels in the shadow regions of raw imageries. Maximum SCA lies in the higher NDSI range in case of AC and TC images, unlike raw image where maximum SCA lies in lower NDSI range for both sunlit and shadow test sites. In the sunlit and shadow terrains, minimum NDSI values were found to be higher for TC images as compared to AC images, except few observations which exhibited similar values for both AC and TC images. In case of maximum NDSI values, most of the observations exhibited similar values for both AC and TC images, except few observations which depicted higher maximum NDSI value in AC images as compared to TC images in both the terrains. This observation ascertains the narrow range of NDSI values for TC images as compared to AC images, which could be attributed to reduced background reflection and low atmospheric scattering in the TC images. Comparison among shadow and sunlit snow terrains, reveals low values of minimum and maximum NDSI in the shadow site, which is ascertained by significant (p < 0.001) t-values of means difference between shadow and sunlit terrains. Moreover, snow surface temperature (SST) values computed for both the time periods, reveal low SST values for shadow sites (t-values −5.1 and − 10.57 for minimum SST, and − 9.1 and − 12.61 for maximum SST for the years 2015 and 2018, respectively) as compared to sunlit sites, and this observation validates that minimum amount of solar radiation reaches the shadow sites. Thus, it is concluded that AC and TC are helpful for delineation of snow pixels under shadow, but shadow has a significant impact on the spectral reflectance of snow, even in the AC and TC images. The influence of shadow should be taken into account for accurate estimation of physical properties and broadband albedo of the snow.

本研究在喜马拉雅山西部的 Chenab 盆地进行，以探索阴影对大气和地形校正的归一化差异雪指数 (NDSI) 值的影响。该研究是使用两个时间段（即 2015 年 2 月和 2018 年 2 月）的 Landsat-8 Operational Land Imager (OLI) 和热红外传感器 (TIRS) 数据集进行的。我们的结果表明，使用 NDSI 计算的总积雪面积 (SCA)原始卫星图像，低于估计的 SCA（即 10,938.66 和 7739.97 Km ²）；相对于大气校正 (AC) (14,819.01 和 11,199.7 Km ² ) 和地形校正 (TC) (14,882.07 和 11,188.18 Km ^{2 )}) 两个时间段（即分别为 2015 年和 2018 年）的图像。这主要是由于未识别原始图像阴影区域中的雪像素。对于 AC 和 TC 图像，最大 SCA 位于较高的 NDSI 范围内，这与原始图像不同，对于阳光照射和阴影测试站点，最大 SCA 位于较低的 NDSI 范围内。在阳光照射和阴影地形中，发现 TC 图像的最小 NDSI 值高于 AC 图像，除了少数观察结果显示 AC 和 TC 图像的值相似。在最大 NDSI 值的情况下，大多数观测在 AC 和 TC 图像中都表现出相似的值，除了少数观测表明 AC 图像中的最大 NDSI 值高于两个地形中的 TC 图像。与 AC 图像相比，该观察确定了 TC 图像的 NDSI 值范围较窄，这可归因于 TC 图像中背景反射减少和大气散射低。比较阴影和阳光照射的雪地地形，揭示了阴影地点的最小和最大 NDSI 值较低，这由显着性 (p  < 0.001) t 值表示阴影和阳光照射地形之间的差异。此外，计算两个时间段的雪面温度 (SST) 值显示阴影位置的 SST 值较低（2015 年和 2015 年的最小 SST 的 t 值 -5.1 和 - 10.57，以及 - 9.1 和 - 12.61 的最大 SST 和2018，分别）与阳光照射的地点相比，这一观察结果证实了到达阴影地点的太阳辐射量最少。因此，可以得出结论，AC和TC有助于描绘阴影下的雪像素，但阴影对雪的光谱反射率有显着影响，即使在AC和TC图像中也是如此。为了准确估计雪的物理特性和宽带反照率，应考虑阴影的影响。