Platform for starters in the geo sector

200 courses, 20 online supports, 60 moocs,

10 work to work trajectories,

30 trainees

MOOC: Glacier Mapping using Earth Observation Satellites

Description

This remote sensing online course is about helping you understand glacier and snow cover mapping using Earth Observation satellites. Initially we focus on the basic principles, i.e. how snow interacts with the electromagnetic radiation. Then we proceed on the specific methodologies that will allow you to map glaciers and snow covered areas using multispectral satellite images. From the practical side, we also focus our learning on how to perform these methods in ESA’s SNAP software. We also provide ready-to-use XML files for the SNAP GPT!

Currently, 10 percent of the land surface on Earth is covered by glacial ice, including glaciers, ice sheets and the ice sheets of Greenland and Antarctica. This percentage is unfortunately decreasing due to climate change. Areas filled with glaciers cover more than 15 million square kilometers, while storing about 75 percent of the world’s fresh water.

Glaciers are an essential part of our living environment and especially the cryosphere. Although not everyone is familiar with glaciers, they are considered very important natural regions that must be preserved and monitored. Scientists analyzing glaciers can better model and understand climate and it changes and delves into Earth’s long-forgotten climate history!

Remote sensing images acquired from different platforms (satellite, aircraft) using sensors operating in different spectral regions (visible, infrared, microwave) have been widely used to study glaciers, e.g. to measure ice thickness, surface speeds and changes in surface height over time. Remote sensing techniques have been used for spectral characterization of various snow and ice planes, preliminary inventory of glaciers, including the size of the sky and the position of large crevasses, and for mapping and monitoring glacier variations, particularly at the glacier edges and endpoint location.

The images below are different timestamps of the same area. On the left you have the natural color (as you would see it with your own eyes) and on the right you see the result of an index called NDGI (Normalized Difference Glacier Index).

Multi-temporal Sentinel 2 image data allows to map the glacier frame and area, as well as the study of the spectral features of snow and ice in the spatial resolution of 10 m – 20 m.

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