The doctor looked at the newborn LOS and said: Natus Vincere. LOS was destined to greatness.

The idea of Brazilian Detection System for Ocean Oil Spill arises. LOS looked at RIOSS and said: I am your father.

Our star collaborator, the Geophysics undergrad student, started collaborating in the RIOSS Project.

Laysla Possebom starts the SAR image database, which will be the basis for testing the classifying algorithms.

In December 2019, after the oil spill that occurred on the coast of northeastern Brazil, the research group obtains funding through the additive term granted by CNPq to the INCT-Petroleum Geophysics coordinated by Prof. Dr. Miltton Porsani. Prof. Porsani invites Prof. André Cunha Lima to create a research group (BROIL) in the area of remote sensing in order to study oil slicks in the ocean. The team is then formed by professors and researchers Dr. Milton Porsani (UFBA), Dr. André Cunha Lima(UFBA), Dr. Carlos Lentini(UFBA), Dr. Luís Felipe Mendonça(UFBA), Dr. Rodrigo Vasconcelos(UEFS), Dr. Garcia Vivas(UFBA), Dr. José Marques(UFBA) and Dr. Marcus Silva(UFPE).

RIOSS consolidated as a strong branch at BROIL. The BROIL project brought new collaborators and the science made RIOSS even stronger.

The first image segmentation analysis were created. The bases for the classification algorithm have been defined.

In 2020, under the coordination of Prof. André Cunha Lima and vice coordination of Prof. Carlos Lentini, the BROIL team wins the call for proposals 06/2020 of CNPq entitled: DETECTION, CONTROL AND PREVENTIVE REMEDIATION OF OIL AND FUEL TRANSPORTATION ACCIDENTS OVER THE OFF THE BRAZILIAN COAST. With this funding, several national and international researchers are brought into the BROIL research group, with participation from other renowned institutions. The following researchers join the group: Dr. Ademir Xavier Silva (UFRJ), Dr. Fabrice Hernandes(IRD/France), Dr. Mainara Gouveia (Post-Doc), Dr. Patricia Genovez (PUC/RJ), Dr. Paulo Henrique R. Calil (HZG/Germany), Dr. Rui Caldeira(OOM/Portugal) Dr. Sidnei Santanna (INPE).

The random forest equations generated great results in the classification of oil spills in SAR images from the sentinel satellite. With an efficiency greater than 93%.

The system was autonomous: performing daily search for SAR data, from Sentinel-1 Satellite, pre-processing the images and running the oil spill classifier algorithm.