The result of a new study by the geographers of Lomonosov Moscow State University is an algorithm that allows remotely and automatically assess the state of steppe and desert landscapes affected by fires.
Now the scientists will be able to indirectly determine the intensity of a fire and the degree of damage from it. The method is especially useful for hard-to-reach areas where jettisoned stages of space rockets fall.
According to Anna Sharapova, the project manager, a researcher at the Faculty of Geography of Moscow State University, there are quite a few algorithms and various coefficients that can be used to find areas affected by fire in space images. However, these so-called spectral indices are suitable mainly for forest regions.
The geographers of Moscow State University went further in their work. They managed to find spectral indices for assessing the semideserts and steppes of Kalmykia and Central Kazakhstan. For this purpose, Landsat 8 satellite images were used.
In Central Kazakhstan, steppe fires are quite common. They are caused by natural phenomena and human activities, including the fall of the stages of launch vehicles launched from the Baikonur cosmodrome.
"Due to contact with vegetation of metal fragments of a jettisoned stage heated in the upper layers of the atmosphere or as a result of the interaction of the residual amount of guaranteed propellant reserves, fires occur that can spread to various territories," explained Ivan Semenkov, senior researcher at the Faculty of Geography, Lomonosov Moscow State University.
As part of the new study by the geographers of Moscow State University, algorithms have been developed that allow to find the affected territories in an automated mode and, by indirect signs, determine the intensity of the past fire. Thus, the scientists succeeded in identifying the area of fire with an accuracy of 98.5% after the fall of the first stage of the “Soyuz” launch vehicle. For the fall zone of the "Proton" rocket stage, the data accuracy was 99.4%.
According to the authors of the work, new algorithms in the future will help to automatically monitor the state of steppes and deserts. Comparing during the expeditions the "age" of a fire and the state of vegetation on the ground, the scientists will try to create a model for predicting the self-healing of ecosystems affected by fire.