The Landsat program provides the longest continuous record of satellite earth observations. Landsat spatial, spectral, and temporal resolutions allow for imagery to be processed at sufficient spatial and temporal detail that is optimal for field scale land surface monitoring, management, and research. Landsat data is available for Landsat 5, 7, 8, and composites of 4/5/7/8 using top of atmosphere or at surface reflectance data.
Normalized Difference Snow Index (NDSI) provides information on snow cover. It typically ranges from -1 to1 with values from 0.5 to 1 representing snow coverage. Information on snow coverage and depth is an important resource in water resource management, planning, and forecasting. Monitoring snow extent using satellite imagery is useful for understanding snow depletion and recession rates, evaluating snow extent relative to long term average conditions, and is a useful drought metric.
NDSI is calculated as the normalized difference between a visible band (VIS) and short wave infrared band 1 (SWIR1) following the formula NDSI = (VIS-SWIR1)/(VIS+SWIR1) (Crane and Anderson, 1984; Dozier, 1984). Here the VIS wavelength is the green band. This method is effective at separating clouds and snow since snow is highly reflective in VIS wavelengths and absorptive in the SWIR1 wavelength while clouds are highly reflective in both (Hall et al., 2001).
Short Wave Infrared 1 (SWIR1): 1.55-1.75 μm
Green: 0.52-0.60 μm
Period of Record
Crane, R. G., and Anderson, M. R., 1984, Satellite discrimination of snow/cloud surfaces. International Journal of Remote Sensing, 5(1), 213 223.
Dozier, J., 1984, Spectral signature of alpine snow cover from the Landsat Thematic Mapper. Remote Sensing of Environment, 28.9-22.
Hall, D. K., Riggs, G. A., Salomonson, V. V., Barton, J. S., Casey, K., Chien, J. Y. L., … & Tait, A. B. (2001). Algorithm theoretical basis document (ATBD) for the MODIS snow and sea ice-mapping algorithms. Nasa Gsfc, 45.
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