RESUMO
Active fires are considered to be the key contributor to, and critical consequence of, climate change. Quantifying the occurrence frequency and regional variations in global active fires is significant for assessing carbon cycling, atmospheric chemistry, and postfire ecological effects. Multiscale variations in fire occurrence frequencies have still never been fully investigated despite free access to global active fire products. We analyzed the occurrence frequencies of Visible Infrared Imaging Radiometer Suite (VIIRS) active fires at national, pan-regional (tropics and extratropics) to global scales and at hourly, monthly, and annual scales during 2012-2017. The results revealed that the accumulated occurrence frequencies of VIIRS global active fires were up to 12,193 × 104 , yet exhibiting slight fluctuations annually and with respect to the 2014-2016 El Niño event, especially during 2015. About 35.52% of VIIRS active fires occurred from July to September, particularly in August (13.06%), and typically between 10:00 and 13:00 Greenwich Mean Time (GMT; 42.96%) and especially at 11:00 GMT (17.65%). The total counts conform to a bimodal pattern with peaks in 5°-11°N (18.01%) and 5°-18°S (32.46%), respectively, alongside a unimodal distribution in terms of longitudes between 15°E and 30°E (32.34%). Tropical annual average of active fire (1,496.81 × 104 ) accounted for 75.83%. Nearly 30% were counted in Brazil, the Democratic Republic of the Congo, Indonesia, and Mainland Southeast Asia (MSEA). Fires typically occurred between June (or August) and October (or November) with far below-average rainfall in these countries, while those in MSEA primarily occurred between February and April during the dry season. They were primarily observed between 00:00 and 02:00 GMT, between 12:00 and 14:00 within each Zone Time. We believed that VIIRS global active fires products are useful for developing fire detection algorithms, discriminating occurrence types and ignition causes via correlation analyses with physical geographic elements, and assessment of their potential impacts.
Assuntos
Incêndios , Sudeste Asiático , Brasil , República Democrática do Congo , IndonésiaRESUMO
Large wildfires can cover millions of hectares of forest every year worldwide, causing losses in ecosystems and assets. Fire simulation and modeling provides an analytical scheme to characterize and predict fire behavior and spread in several and complex environments. Spatial dynamics of large wildfires can be analyzed using satellite active fire data, a cost-effective way to acquire information systematically worldwide. The simulated growth of three large wildland fires from the USA, Chile and Spain with different fire spread pattern, duration and size has been compared to satellite active fire data. Additionally, a new approach to reinitialize fire simulations in near real-time and predict a more accurate fire spread is shown in this work. Discrepancies between the simulated fire growth and satellite active data were measured spatially and temporally in the three fires, increasing along the fire duration. The reinitialization approach meaningfully improved the accuracy of fire simulations in all case studies. Satellite active fire data showed a high potential to be used in real fire incidents, improving fire monitoring and simulation and, therefore, supporting the decision-making process of the fire analyst. The reinitialization approach could be applied by using the current satellite active fire data such as MODIS or VIIRS as well as Unmanned Aerial Vehicles or GPS locations from suppression resources.