Improved linear interpolation method for the estimation of snow-covered area from optical data

Abstract

Spatially well-distributed information on the regional fraction of snow-covered area (SCA) is important to snow hydrology during the melting season. One approach for regional SCA estimation using visible and near-infrared reflectances is based on linear interpolation between reference reflectances for full snow cover and snow-free conditions. We present an improved method for National Oceanographic and Atmospheric Administration/Advanced Very High Resolution Radiometer (NOAA/AVHRR) imagery with (1) an automated determination of reference reflectances by distinguishing wet and dry snow conditions and, on the other hand, near melt-off and totally melt-off conditions and (2) an employment of Normalized Difference Vegetation Index (NDVI) to avoid overestimations due to vegetation cover at the end of the melting season. The study site covers the area of Finland, which serves as an example of the Eurasian boreal coniferous forest zone. Finnish drainage basins are used as areal calculation units in order to produce feasible information for hydrological models. Since the frequent cloudiness in the northern latitudes reduces the availability of optical data, we developed a technique to generate reference reflectances for basins that were obscured at the actual moment of data retrieval. For a basin without a reference value, the proper values were derived from a basin of the same characteristics; the similarity was described with a special Forest Sparseness Index generated from AVHRR data. The linear interpolation method with the additional features was tested for AVHRR imagery during melting period 2000. Validation against a comprehensive network of ground observations at snow courses and weather stations indicated good performance.