I. Introduction
Learn about the purpose and the contents of this training module.
II. Physical snow characteristics determined from space
This chapter explains the science behind satellite-based snow observations and is separated into different parts according to specific regions of the electromagnetic spectrum.
III. Snow detection using the MODIS instrument
Here you can get a better understanding of snow cover detection algorithm used to create MODIS snow products.
IV. Snow water equivalent in GlobSnow-2 datasets
In this chapter you can learn how snow water equivalent (SWE) is derived for northern hemisphere using the sophisticated assimilation technique developed by GlobSnow project.
V. Building climatological time series of snow cover data
Learn how to fill the gaps in satellite-based observations, how to extract data for particular location and how to asses the accuracy of remote-sensing products using contingency table statistics.
VI. Snow cover days in the Baltic States derived from satellite measurements
The case study from the Baltic States. You will find the examples of annual and monthly snow cover days (SCD) climatology calculated using MODIS data from 2000 to 2013 and validated against the in-situ measurements.
VII. Snow water equivalent in the Baltic States based on satellite measurements
The case study from the Baltic States. You will find the examples of annual and monthly snow water equivalent (SWE) climatology based on GlobSnow data and validation results from comparison with ground measurements.
VIII. Advantages and limitations of satellite-based snow data
A list of advantages and limitations of satellite-based snow observations.
IX. Applications
In this chapter you will find the examples and application areas of satellite-based snow products.
X. Summaryand references
Summary gives a short overview and the main points to take. In references you will find a list of documents which can help you to learn more about the snow detection from satellites.
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