A dark cloud over Kiev on the 9th of June

=> These days, Mireille Huc is spending a lot of time to enhance the cloud shadow detection method applied to time series. Our MACCS method tends to forget some shadows when they are partly hidden under the cloud. We will explain in a future article the defects of the present method and how we will mitigate them. When checking our results, we found out a very particular case, on June the 9th in 2015, on the time series acquired near Kiev with SPOT5 (Take5).  The images are shown below : 

 

The dark zone in the image center was not classified as a cloud shadow, as shown by the quicklook. Because it is not a cloud shadow, the sun is in the South-East direction, and the shadows are cast to the North-West. It does not look like the footprint of a flooding, or of a forest fire, and there was no solar eclipse on that day… 

In fact, a close up on the SWIR image, which is sensitive to the thermal emission by high temperatures, shows that it is a black smoke cloud, due to a fire at the North East of the cloud.  Duckduckgo gave us the answer, it was the fire of a fuel depot (which caused some casualties). Our multi-temporal methods pour cloud detection and aerosol estimates is disturbed by this dark cloud. The surface reflectance drops and then increases again, the drop is not detected as a shadow, but the subsequent increase is interpreted as a cloud. The aerosols are also inaccurately estimated, since usually, an increase of the aerosol quantity causes an increase of the reflectance, but here, the aerosol are so absorbing that the reflectance decreases. 

Plus d'actualités

BIOMASS, the third launched satellite mission designed at CESBIO !

After SMOS in 2009, and VENµS in 2017, the CESBIO Laboratory is very proud to see its third proposed mission, Biomass, reach orbit. As always, it has been a long journey from the idea, at the beginning of the century, to the selection in 2013 as the seventh Earth Explorer Mission by ESA, to the […]

Satellite Stereoscopy for Water Resource Monitoring?

=> In arid or semi-arid regions, where irrigation is widespread, monitoring agricultural water resources is essential to anticipate shortages. These resources may come from large dams, small reservoirs, or groundwater aquifers. This is the case in the state of Telangana, in South India, where numerous large dams (shown in cyan blue in the figure below) […]

La stéréoscopie par satellite pour le suivi des ressources en eau ?

=> Dans les régions arides ou semi-arides, où l’irrigation est généralisée, le suivi de la ressource en eau agricole est primordial pour anticiper les pénuries. Cette ressource peut-être l’eau de grands barrages, de petits réservoirs ou provenant de l’aquifère. C’est le cas de l’état du Télangana, en Inde du Sud, où de nombreux grands barrages […]

Rechercher