The following link will take you to 3 interactive Case Studies

EO4SAS Interactive Case Studies

The case studies are hosted on “Voila” and implemented in Jupyter notebooks in the Cloud (there is no need to install anything on your computer).  Please note that the case studies take several seconds to load as they pre-process the relevant data to allow you to interact with it!

The case studies themselves are straightforward to use; the following paragraphs describe what each case study is showing.

Case Study 1: Investigating Areas Around Sand Dams to Understand Sand Occurrence & Vegetation Health 

Sand is extracted from the riverbeds of Kenya’s semi-arid and arid areas, particularly to the south and east of Nairobi, to support the construction industry. This extraction has the potential to cause adverse effects to the surrounding environment if too much is extracted, or the extraction itself is harmful, e.g., by reducing biodiversity.  

This case study focuses on sand dams for an area covering approximately 50 km x 100 km, including the intersection between Kitui, Machakos and Makueni, using the free-to-access Copernicus EO satellite data to develop a land classification model using a pre-trained Neural Network model. It uses ‘snapshots’ dates from November 2019 to December 2020, selected due to their relatively low cloud coverage, and allows seasonal changes to be observed during the year, i.e., the influence of the wet and dry seasons. 

Case Study 2: On-land Sand Extraction  

Sand dams are not the only type of sand extraction taking place in Kenya, and Case Study 2 focuses on the on-land extraction of historic sand deposits rather than the extraction of sand flowing down rivers. The chosen location is Nakuru county, with sites in Nakuru and north of Bahati being known extraction sites; the northern site is surrounded by fields and trees, while the eastern site is surrounded by housing.

This Case Study used additional satellite sensors and data to Case Study 1: 

• High spatial resolution commercial optical imagery, from GeoEye-1 and Pléiades to both compare to the Sentinel land classification and to see what further insights can be seen with the higher resolution [not available in the online visualisation due to licencing restrictions].   
• Visible Infrared Imaging Radiometer Suite (VIIRS) Night–time imagery to look at the night–time economic activity around extraction sites.  
• Sentinel-1 processed using an interferometric technique to derive a Digital Elevation Model (DEM) to measure changes in heights and support quantifying the amounts extracted. 

These techniques allow the following series of products and insights to be developed.

Case Study 3: Waterline Extraction  

Case Study 3 focused on the extraction of sand from the land-water boundary. We concentrated on Lake Victoria as the user engagement discussions revealed (anecdotally) this had been prolific previously in Homa Bay locations.  A technique was used to identify the suspended particulate matter in the water, where changes in the turbidity of the water may indicate that sand extraction for the shoreline or even dredging has taken place.