Near Real-Time Automated Early Mapping of the Perimeter of Large Forest Fires from the Aggregation of VIIRS and MODIS Active Fires in Mexico

Abstract

In contrast with current operational products of burned area, which are generally available one month after the fire, active fires are readily available, with potential application for early evaluation of approximate fire perimeters to support fire management decision making in near real time. While previous coarse-scale studies have focused on relating the number of active fires to a burned area, some local-scale studies have proposed the spatial aggregation of active fires to directly obtain early estimate perimeters from active fires. Nevertheless, further analysis of this latter technique, including the definition of aggregation distance and large-scale testing, is still required. There is a need for studies that evaluate the potential of active fire aggregation for rapid initial fire perimeter delineation, particularly taking advantage of the improved spatial resolution of the Visible Infrared Imaging Radiometer (VIIRS) 375 m, over large areas and long periods of study. The current study tested the use of convex hull algorithms for deriving coarse-scale perimeters from Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) active fire detections, compared against the mapped perimeter of the MODIS collection 6 (MCD64A1) burned area. We analyzed the effect of aggregation distance (750, 1000, 1125 and 1500 m) on the relationships of active fire perimeters with MCD64A1, for both individual fire perimeter prediction and total burned area estimation, for the period 2012–2108 in Mexico. The aggregation of active fire detections from MODIS and VIIRS demonstrated a potential to offer coarse-scale early estimates of the perimeters of large fires, which can be available to support fire monitoring and management in near real time. Total burned area predicted from aggregated active fires followed the same temporal behavior as the standard MCD64A1 burned area, with potential to also account for the role of smaller fires detected by the thermal anomalies. The proposed methodology, based on easily available algorithms of point aggregation, is susceptible to be utilized both for near real-time and historical fire perimeter evaluation elsewhere. Future studies might test active fires aggregation between regions or biomes with contrasting fuel characteristics and human activity patterns against medium resolution (e.g., Landsat and Sentinel) fire perimeters. Furthermore, coarse-scale active fire perimeters might be utilized to locate areas where such higher-resolution imagery can be downloaded to improve the evaluation of fire extent and impact.

Análise de acurácia para o mapeamento de áreas queimadas utilizando uma cena VIIRS 1Km e classificação por Random Forest

“…Portanto, espera-se que esta banda seja mais sensível a perturbações causadas por incêndios e ao conteúdo de umidade na estrutura da vegetação, que é a variável mais importante que influencia a região no comportamento espectral no NIR (Jacquemoud et al, 2009;Jacquemoud, 2002). Em estudos utilizando VIIRS 375 m e 1Km, DaCamara et al, 2019, encontraram feições bastante descriminantes utilizando a banda M11 também correspondente com trabalhos de (Schepers et al, 2014) e (Briones-Herrera et al, 2020).…”

FIRED (Fire Events Delineation): An Open, Flexible Algorithm and Database of US Fire Events Derived from the MODIS Burned Area Product (2001–2019)

“…We attempted to scale the FIRED product to the entire globe, and found that our spatial and temporal parameters were inappropriate, particularly for the savanna biome where very high proximity of fires in space and time led to severe aggregation of events. This highlights a substantial need for global fire perimeter data [51], or development of an optimization approach that does not rely on these external data. This is a unique moment in the history of fire science, given the abundance of fire data across spatial scales, that requires the fire science community to better coordinate efforts on fire data harmonization challenges and opportunities.…”

FIRED (Fire Events Delineation): An open, flexible algorithm & database of US fire events derived from the MODIS burned area product (2001-19)

“…We attempted to scale the FIRED product to the entire globe and found that our spatial and temporal parameters were inappropriate, particularly for the savanna biome where very high proximity of fires in space and time led to severe aggregation of events. This highlights a substantial need for global fire perimeter data [51], or development of an optimization approach that does not rely on these external data. response on a daily scale [52].…”