This web app aims to demonstrate the visualization of multi-temporal information. The semantically enriched Earth Observation (EO) time series information was obtained from Sentinel-2 Semantic Earth Observation Data and Information Cube for Austria (Sen2Cube.at), which is the world’s first prototype of a semantic EO data cube.
The approach of visualization used this application is slightly different from traditional ways.
In the first case of yearly vegetation in Salzburg from 2016-2021, users can visualize the presence or absence of vegetation in selected years and the selected threshold percentage in one layer. This is challenging in GIS softwares like ArcGIS Pro and QGIS because the RGB channel can handle only 3 bands. Users can select any year(s) and the resulting layer will be pixels that were vegetated in the selected year(s) but not in the unselected years.
Let us consider that there are only two years, 2016 and 2017, and following are the pixel values
for those two years.
And consider the user takes 20%
as the threshold.
If the user selects both 2016 and 2017, those pixels that were vegetated in both the years
with threshold greater or equal to 20% will be displayed. But if the user selects 2017 but not
2016, those pixels that were vegetated in both 2016 and 2017 with 20% threshold will not be
displayed. Only the pixels that were vegetated exclusively in 2017 will be displayed.
Both
the
conditions are illustrated in the image below with red representing vegetated pixels and
white representing non-vegetated pixels.
In addition to this, the user can also compare two maps side by side by selecting different
years.
The same principle works in the case of water occurrence in Syria-Turkey border region.
This web app demonstrates the visualization of semantically enriched EO time series data from
Sen2Cube.at.
Two use cases, one about yearly vegetation changes in Salzburg, Austria from
2016-2021 and
another about monthly water occurrence in 2022 for the border region of Syria and Turkey are
shown as examples.
Any other similar kind of information can be pre processed and
visualized using the
same workflow.
Before exploring the visualizations, please make sure to go through the 'About' section on extreme right of the navigation bar, to see how the system works
Vegetation observed per pixel in Salzburg region
