The method, led by the researcher Aitor Bastarrika of the University of the Basque Country (UPV/EHU), is capable of detecting fires of less than 250 metres using data from various satellites.

Using data from two satellites that collect optical images, and from another four that measure high temperatures caused by fires, a publication led by Aitor Bastarrika of the UPV/EHU's Built Heritage Research Group, is proposing an algorithm to achieve the global mapping of burnt areas with a higher resolution.

Obtaining accurate, up-to-date information from fire-affected areas is essential not only to better understand air quality, biogeochemical cycles or climate, but also to contribute towards fire management. A few decades ago the mapping of burnt areas was done on the basis of the study of rural areas, but since the launch of Earth observation satellites, remote sensing has become a more practical option for locating burnt areas, as satellites make it easier to measure fire-affected areas, both regionally and globally.

Image resolution is the problem with respect to areas mapped by satellite. In fact, the resolution of global observations has so far been poor. “The omission error of current products is very high: many areas that are in fact burnt are not identified as such,” said Aitor Bastarrika, a researcher at the UPV/EHU. “Current systems use a pixel size of between 250 and 500 metres, so they do not detect fires of less than 250 metres. And in some ecosystems, fires of this size are very frequent.”

By using data from six different satellites, the study led by Aitor Bastarrika developed an algorithm to achieve a higher resolution. Firstly, they took advantage of the images captured by the two optical satellites of the Sentinel-2 constellation: they offer good spatial resolution of 10-20 metres, but with a low temporal frequency, as images of a specific location are only obtained every 5 days. Secondly, advantage was taken of MODIS products (derived from the Terra and Aqua satellites) and VIIRS (derived from the Suomi NPP and NOAA-20 satellites) products that detect active fires: they detect high temperature spots with a low spatial resolution of 375-1000 metres, but with a high frequency, as they collect data every day.

A proven algorithm in hundreds of areas

The algorithm developed by Bastarrika's team uses the data from the two active fire detection products and with them trains an optical imaging system with a view to producing a classification system. It then makes predictions of what has and has not been burnt. “In addition, these forecasts were tested in 576 areas around the world, in other words, the algorithm was analysed in all ecosystems where burnt areas are significant,” explained Bastarrika.

The algorithm developed by Bastarrika's team is not the only one; there are other similar proposals. However, the contribution by the UPV/EHU researchers is particularly important because the algorithm is designed to be applied on a global scale and to obtain results with a medium resolution. “Algorithms already exist for mapping specific areas at medium resolution, but our proposal can map burnt areas across the world, does so at an acceptable resolution and is up and ready for use.”

For the future, the aim is to create new products using this algorithm that has been developed. “Since up to now they have been prepared to use low-resolution systems, from now on the aim is to create products that deliver results at a medium level of resolution. Moving from low to medium resolution would make a great contribution towards identifying specific ecosystems and studying climate,” said Bastarrika.

Further information

Aitor Bastarrika is a lecturer in the UPV/EHU’s department of Mining Engineering and Metallurgy and Materials Science and a researcher in the Built Heritage Research Group. Bastarrika lectures at the Faculty of Engineering Vitoria-Gasteiz.