Our current research and development includes space data retrieval for determination of atmospheric concentration of greenhouse gases, particularly, carbon dioxide CO­₂, water vapour H₂O, methane CH₄ and carbon monoxide CO. We also perform modeling and simulation, statistical analysis and correlations of space data by using line-by-line radiative transfer model. Space observation data is applied to match with computer simulated (synthetic) data by changing the relevant parameters like concentration of a gas, nadir angle deviation, integration time, surface Albedo, altitude, etc. If there is a match under specific criteria between synthetic and real spectral data, then the retrieval is complete. The obtained information is further analysed, interpreted by using geolocation data with help of Google Earth and STK toolkit.

Another project that ECG team works on is a new method of cloud scene detection. As water vapour and droplets H₂O are significant contributors for greenhouse effect, the detection of the cloud scenes plays a significant role for observation of dynamics of the climate change. Conventional methods analyse 2D image masking in determination of the cloud scenes. Our new proposed techniques employ Radiance Enhancement (RE) and Shortwave upwelling Radiative Flux (SWupRF) in determination of the clouds scenes. These two techniques show their efficiency by comparing space spectral radiance with 2D imaging. Additional advantage is that the data from space micro-spectrometer is periodic due to rotation of the nano-satellite around the Earth. Therefore, these techniques enable us continuous monitor of the same areas multiple times.