Artificial neural networks for assessing forest fire susceptibility in Türkiye

Deep learning allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction. These methods have dramatically improved the state-of-the-art in speech recognition, visual object recognition, object detection and many other domains such as drug discovery and genomics. Deep learning discovers intricate structure in large data sets by using the backpropagation algorithm to indicate how a machine should change its internal parameters that are used to compute the representation in each layer from the representation in the previous layer. Deep convolutional nets have brought about breakthroughs in processing images, video, speech and audio, whereas recurrent nets have shone light on sequential data such as text and speech.

Recent bursts in the incidence of large wildfires worldwide have raised concerns about the influence climate change and humans might have on future fire activity. Comparatively little is known, however, about the relative importance of these factors in shaping global fire history. Here we use fire and climate modeling, combined with land cover and population estimates, to gain a better understanding of the forces driving global fire trends. Our model successfully reproduces global fire activity record over the last millennium and reveals distinct regimes in global fire behavior. We find that during the preindustrial period, the global fire regime was strongly driven by precipitation (rather than temperature), shifting to an anthropogenic-driven regime with the Industrial Revolution. Our future projections indicate an impending shift to a temperature-driven global fire regime in the 21st century, creating an unprecedentedly fire-prone environment. These results suggest a possibility that in the future climate will play a considerably stronger role in driving global fire trends, outweighing direct human influence on fire (both ignition and suppression), a reversal from the situation during the last two centuries.