Contrasting snow and ice albedos derived from MODIS, Landsat ETM plus and airborne data from Langjokull, Iceland

REMOTE SENSING OF ENVIRONMENT

卷:175

Article

Pope, Ed L.^1,2  Willis, Ian C.¹  Pope, Allen^1,3  Miles, Evan S.¹  Arnold, Neil S.¹  Rees, W. Gareth¹ 

[1] Univ Cambridge, Scott Polar Res Inst, Lensfield Rd, Cambridge CB2 1ER, England

[2] Univ Southampton, Natl Oceanog Ctr, Waterfront Campus, Southampton SO14 3ZH, Hants, England

[3] Univ Colorado, Natl Snow & Ice Data Ctr, 1540 30th St, Boulder, CO 80303 USA

关键词: Albedo measurement;    Landsat;    MODIS;    Snow;    Ice;    Glacier;    Ice cap;    Spatial scales;    FLAASH;    6S;   

DOI  :  10.1016/j.rse.2015.12.051

来源: Elsevier

【 摘 要 】

Surface albedo is a key parameter in the energy balance of glaciers and ice sheets because it controls the short-wave radiation budget, which is often the dominant term of a glacier's surface energy balance. Monitoring surface albedo is a key application of remote sensing and achieving consistency between instruments is crucial to accurate assessment of changing albedo. Here we take advantage of a high resolution (5 m) airborne multispectral dataset that was collected over Langjokull, Iceland in 2007, and compare it with near contemporaneous ETM+ and MODIS imagery. All three radiance datasets are converted to reflectance by applying commonly used atmospheric correction schemes: 6S and FLAASH. These are used to derive broadband albedos. We first assess the similarity of albedo values produced by different atmospheric correction schemes for the same instrument, then contrast results from different instruments. In this way we are able to evaluate the consistency of the available atmospheric correction algorithms and to consider the impacts of different spatial resolutions. We observe that FLAASH leads to the derivation of surface albedos greater than when 6S is used. Albedo is shown to be highly variable at small spatial scales. This leads to consistent differences associated with specific facies types between different resolution instruments, in part attributable to different surface bi-directional reflectance distribution functions. Uncertainties, however, still exist in this analysis as no correction for variable bi-directional reflectance distribution functions could be implemented for the ETM+ and airborne datasets. (c) 2016 Elsevier Inc. All rights reserved.

【 授权许可】

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