The Triple Sensor monitoring approach permits to view and compare the accuracy of citizen-sourced, satellite and conventional ground station data on water and climate for a specific location and time period. Demonstration of this approach was developed under the Afrialliance EU Horizon 2020 Coordination and Support Action project. Click here to access the active web-based demo: http://afrialliance.itc.utwente.nl/triplesensor/ and land on the demo-page below.
This web-based demo illustrates the technique for rainfall observations (July 2015) near Dano in southwest Burkina Faso, a research area of West African Afrialliance partner WASCAL. Citizen locations were extracted from the Open access Global Water Point Data Exchange portal (https://www.waterpointdata.org/). Citizen names were adapted and reported rain data were generated for demo purposes. Observed meteorological in-situ station data were obtained from https://wascal.org/ and CHIRPS2 satellite rainfall data was used as open access remotely sensed precipitation and obtained from https://www.chc.ucsb.edu/data/chirps.
The method can be applied to any region, project area or location of interest and can be practiced on many typical climate, weather or water resources and continuous or discrete biophysical observation data (e.g. time series of meteorological soil, soil moisture, water surface or levels, the state of vegetation or crop conditions, health conditions, etc.).
Triple Sensor collocation is a statistical data analysis technique used to validate three independent observations at a location, when e.g. the true value is unknown. With this you can judge, which water or climate observation, i.e. your citizen observation, conventional near-by station data or a remotely sensed satellite look-up is most reliable. The method is derived from statistical covariance analysis on three data sources; it yields errors and correlations and permits to rank the reliability of the datasets, i.e. it determines the best performing dataset on the locations. More application test and use cases are currently developed in Kenya, Ethiopia and the Netherlands.
Please click here to get the Demonstration Toolbox software and documentation https://filetransfer.itc.nl/pub/52n/AfriAlliance.
We invite interested persons to contact Chris Mannaerts (c.m.m.mannaerts@utwente.nl) a/o Bas Retsios (v.retsios@utwente.nl) for more information and exploration of further collaboration.