Estimating changes to global snow resources using MODIS data in Google Earth Engine

Darri Eyþórsson, Doctoral Graduate Student in Environmental Engineering gives the lecture Estimating changes to global snow resources using MODIS data in Google Earth Engine.

Abstract

Snow Cover Frequency (SCF), the proportion of snow covered days per year, is a key estimate of the availability of snow resources from remote sensing. SCF is an important environmental variable as it can e.g. be used to indicate growing season length and habitat suitability, furthermore SCF is an important geophysical feature as snow cover will reflect most of the inbound solar radiation. Google Earth Engine (GEE) is a petabyte scale data warehouse (> 17 petabytes of remote sensing data) that enables analysis and visualization of all archived data from various satellites/sensors. GEE is available to the academic community free of charge and has been referenced in more than 4000 publications in the fields for remote sensing and GIS to date.