Published July 29, 2021 | Version v1

Random Forest fused MODIS and Landsat snow cover from spectral mixture analysis in the Sierra Nevada, USA

Authors/Creators

Description

This data is snow cover fraction from the Snow Covered Area and Grain Size (SCAG) model for Landsat OLI and Terra MODIS and well as a 2-stage random forest model to fuse the 2 datasets for improved temporal/spatial resolution. There are 170 scenes in 2001 to 2012. It was used in the a publication for Remote Sensing of the Environment titled: Multi-sensor fusion using random forests for daily fractional snow cover at 30 m, doi: to be assigned.

Inputs: [YYYYMMDD is year month day of month, $num is 5 or 7 for Landsat platform, $sens is sensor TM or ETM+]

Landsat.zip:

Snow cover from Landsat: SSN.p042r034_YYYYMMDD.Landsat$num-$sens.canopyadjusted_mask.v01.tif 

 

MODIS.zip:

Snow cover from MODIS: SSN.SN_W$YYYYMMDD_$YYYYMMDD.Terra-MODIS.snow_cover_percent.v01.tif

 

Predictors.zip 

Static predictors (see RSE publication Table 2): SouthernSierraNevada*.tif [* here is the variable name]

Outputs [ [YYYYMMDD is year month day of month]

ProbabilityNot0Not100.zip

SSN.prob.btwn.YYYYMMDD.v3.tif - from classification random forest, probability of being between 0 and 100

 

Probability100fSCA

SSN.pro.hundred.YYYYMMDD.v3.tif - from classification random forest, probability of being 100

 

RegressionResult.zip

SSN.regression.YYYYMMDD.v3.tif - from prediction random forest

 

Final_Downscaled.zip

SSN.downscaled.YYYYMMDD.v3.3e+05.tif - final product (combination of classification and prediction)

Files

Final_Downscaled.zip

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