EARTH OBSERVATION

Earth observation and remote sensing techniques are revolutionizing the way we understand our planet

Anthropogenic activity is accelerating the degradation of Earth’s natural environment. Remote sensing has developed into a vital geospatial technology and has become an integral tool for understanding the Earth and managing human impact on it.

Earth Observation Aim: Support the Application and Monitoring of the Biomatrix

Contains modified Copernicus Sentinel data 2021, processed by ESA. Source of the data: Copernicus Open Access Hub.

 

Earth observation techniques support the Green Earth project through:

  • Detecting degraded areas, which are suitable to apply the biomatrix
  • Assessing the status of desertification in a particular location
  • Identifying the most appropriate time window to spread the mixture
  • Monitoring the success of the treatment once applied
  • Monitoring the climate of the treated areas to provide irrigation when necessary

 

Examples of suitable areas are displayed below.

 

Land Degradation Mapping – identifying suitable areas to apply the biomatrix

In order to find suitable areas to apply the treatment, first degraded land is identified through satellite imagery. Thereafter, unwanted areas are excluded, including water bodies, infrastructure and steep slopes. Furthermore, additional parameters (e.g. climatological and geophysical) are considered to further assess the suitability of the individually selected areas.

 

Contains modified Copernicus Sentinel data 2021, processed by ESA. Source of the data: Copernicus Open Access Hub.

Success Monitoring

Monitoring the success of our treatment areas from outer space

Assessing the success of the spread biomatrix is an important step in monitoring the biocrust development. Remote sensing techniques enable the observation of the success of the biomatrix. Hyperspectral data improves the accuracy of detecting the specific biological soil crust.

Examples of high resolution hyperspectral imagery of our developed crust (left to right: Crust 1 - RGB, SWIR, VNIR; Crust 2 - RGB, SWIR, VNIR):