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

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 impactFunding for this study was provided by CONAFOR/CONACYT Projects “CO2-2014-3-252620” and “CO-2018-2-A3-S-131553” for the development and enhancement of a Forest Fire Danger Prediction System for Mexico, funded by the Sectorial Fund for forest research, development and technological innovation “Fondo Sectorial para la investigación, el desarrollo y la innovación tecnológica forestal”S

Temporal patterns of active fire density and its relationship with a satellite fuel greenness index by vegetation type and region in Mexico during 2003-2014

Background: Understanding the temporal patterns of fire occurrence and their relationships with fuel dryness is key to sound fire management, especially under increasing global warming. At present, no system for prediction of fire occurrence risk based on fuel dryness conditions is available in Mexico. As part of an ongoing national-scale project, we developed an operational fire risk mapping tool based on satellite and weather information. Results: We demonstrated how differing monthly temporal trends in a fuel greenness index, dead ratio (DR), and fire density (FDI) can be clearly differentiated by vegetation type and region for the whole country, using MODIS satellite observations for the period 2003 to 2014. We tested linear and non-linear models, including temporal autocorrelation terms, for prediction of FDI from DR for a total of 28 combinations of vegetation types and regions. In addition, we developed seasonal autoregressive integrated moving average (ARIMA) models for forecasting DR values based on the last observed values. Most ARIMA models showed values of the adjusted coefficient of determination (R2 adj) above 0.7 to 0.8, suggesting potential to forecast fuel dryness and fire occurrence risk conditions. The best fitted models explained more than 70% of the observed FDI variation in the relation between monthly DR and fire density. Conclusion: These results suggest that there is potential for the DR index to be incorporated in future fire risk operational tools. However, some vegetation types and regions show lower correlations between DR and observed fire density, suggesting that other variables, such as distance and timing of agricultural burn, deserve attention in future studiesAntecedentes: Una adecuada planificación del manejo del fuego requiere de la comprensión de los patrones temporales de humedad del combustible y su influencia en el riesgo de incendio, particularmente bajo un escenario de calentamiento global. En la actualidad en México no existe ningún sistema operacional para la predicción del riesgo de incendio en base al grado de estrés hídrico de los combustibles. Un proyecto de investigación nacional actualmente en funcionamiento, tiene como objetivo el desarrollo de un sistema operacional de riesgo y peligro de incendio en base a información meteorológica y de satélite para México. Este estudio pertenece al citado proyecto Resultados: Se observaron en el país distintas tendencias temporales en un índice de estrés hídrico de los combustibles basado en imágenes MODIS, el índice “dead ratio” (DR), y en las tendencias temporales de un ìndice de densidad de incendios (FDI), en distintos tipos de vegetación y regiones del país. Se evaluaron varios modelos lineales y potenciales, incluyendo términos para la consideración de la autocorrelación temporal, para la predicción de la densidad de incendios a partir del índice DR para un total de 28 tipos de vegetación y regiones. Se desarrollaron además modelos estacionales autoregresivos de media móvil (ARIMA en inglés) para el pronóstico del índice DR a partir de los últimos valores observados. La mayoría de los modelos ARIMA desarrollados mostraron valores del coeficiente de determinación ajustado (R2 adj) por encima de 0.7 to 0.8, sugiriendo potencial para ser empleados para un pronóstico del estrés hídrico de los combustibles y las condiciones de riesgo de ocurrencia de incendio. Con respecto a los modelos que relacionan los valores mensuales de DR con FDI, la mayoría de ellos explicaron más del 70% de la variabilidad observada en FDI. Conclusiones: Los resultados sugirieron potencial del índice DR para ser incluido en futuras herramientas operacionales para determinar el riesgo de incendio. En algunos tipos de vegetación y regiones se obtuvieron correlaciones más reducidas entre el índice DR y los valores observados de densidad de incendios, sugiriendo que el papel de otras variables tales como la distancia y el patrón temporal de quemas agrícolas debería ser explorado en futuros estudiosFunding for this work was provided by CONAFOR-CONACYT Project 252620 “Development of a Fire Danger System for Mexico.” This work was also cofinanced by the Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria and European Social Fund (Dr. E. Jiménez grant)S

Severe meteorological events in northern Mato Grosso between june 1999 and september 2003

As part of ongoing prescribed burnings experiments, an automatic weather station(AWS) was installed in a site at the Fazenda Caiabi (9o 58' S; 56o 21' W), Alta Floresta, MT, in June 1999; this AWS continues operational up to the present. The Terra Firme forest at the site was slashed in May 1999 and burned in August 1999; thereafter, the burned site, with 4 ha, was abandoned and a natural regrowt occurred, with the AWS measuring continuously the incident solar radiation, the air temperature and the rainfall. With some descontinuities, the reflected solar radiation, the net radiation, the wind direction and velocity, and the air moisture content were also measured. Further, since August 2002, CPTECs ETA Regional 40 x 40 km numerical weather prediction variables are being recorded for the site, with the purpose of comparing them with the AWS measurements. This study identifies and analyses the severe rainfall and temperature decreases ("friagens") events that occurred during the period between May 1999 and September 2003 at the site mentioned

Rainfall climatology (1976-2004) and severe meteorological events in Northern Mato Grosso

Severe meteorological events usually interfere both with natural and human systems, thus causing the most diverse problems and, even, disasters. Among these events, e.g., the rains above 100 mm/day may cause floods and the collapse of hill sides in urban areas.The sudden and strong decrease of the temperature, besides the well known agricultural and cattle raising effects, may induce the fall of the tree leaves in the non-deciduous Terra Firme Amazon forest; also, it may cause acute pulmonary sicknesses in less resistant persons. The cloudiness may affect the development of the plants. On the other hand, the persistence during several days of stagnations of warm and dry air masses increases the air pollution and the fire risks, while it also decreases the atmospheric visibility. Thus, the knowledge of these phenomena, as well as their predictability, is of utmost importance for a region. Thus, this work presents the severe rain, low temperature and high cloudiness events measured through an automatic weather station (AWS) located at the Fazenda Caiabi (9 deg 58 min S; 56 degr 21 min W), Alta Floresta, Mato Grosso, Brazilian Amazon. Also, during the period between May 30, 1999 and September 15, 2003, the stagnation of warm and dry air masses periods were also determined. Further, after August 2002, CPTECs ETA Regional 40 x 40 km numerical weather prediction model outputs were recorded for the site, and compared with the values actually measured using the AWS. The monthly averages for the period mentioned are analyzed. In addition, the monthly rain climatology for the period 1976 2003, that is, since the opening of the Fazenda trhrough the slashing and burning of the forest, was obtained from daily measurements over the whole period. Summarizing for the AWS period, the lowest daily minimum temperature measured was 7.9 C, followed by 11.2 C; all other values were above 12 C. The highest rainfall recorded was 192.5 mm/day, followed by 125.0 and 103.6 mm/day; there were 22 values in the 50 to 100 mm/day range, while all others fell below 50 mm/day. Concerning the cloudiness, 110 days presented an accumulated daily incident solar energy flux below 12 MJ/m2 (very cloudy); the minimum was 1.92 MJ/m2, and there were 16 values below 5 MJ/m2.Pages: 891-90

Coordinación institucional para la realización de quemas prescritas y quemas controladas en México

En México, diversas instituciones gubernamentales, académicas y asociaciones civiles, han impulsado el manejo del fuego como una estrategia para minimizar los impactos negativos de los incendios forestales y maximizar sus efectos positivos. Entre sus propósitos están mantener la ocurrencia de estos eventos en el intervalo de variación de los regímenes naturales de fuego para cada ecosistema. Para realizar manejo del fuego se pueden llevar a cabo quemas prescritas y quemas controladas, que consisten en la aplicación intencional del fuego con objetivos concretos. En México se ha dado impulso recientemente a estas prácticas, pero a la fecha se cuenta con poca información sobre la coordinación entre las instituciones involucradas en su ejecución. Sin embargo, su generación es fundamental para mejorar el éxito de las mismas, a partir del principio del manejo adaptativo. En este trabajo se describe la heterogeneidad institucional involucrada en el desarrollo de cinco quemas controladas y prescritas, y se contrasta con la atención a un incendio forestal. En diferentes regiones del país se identificaron brigadistas de Conafor, brigadistas locales, académicos e integrantes de Organizaciones de la Sociedad Civil que desempeñan papeles distintos durante las quemas. Por ello, es necesario considerar la diversidad institucional existente en el país y la importancia de que dichas instituciones logren acuerdos que permitan a diferentes actores participar en la ejecución tanto de quemas prescritas, como controladas

Modeling and Mapping Forest Fire Occurrence from Aboveground Carbon Density in Mexico

Understanding the spatial patterns of fire occurrence is key for improved forest fires management, particularly under global change scenarios. Very few studies have attempted to relate satellite-based aboveground biomass maps of moderate spatial resolution to spatial fire occurrence under a variety of climatic and vegetation conditions. This study focuses on modeling and mapping fire occurrence based on fire suppression data from 2005−2015 from aboveground biomass—expressed as aboveground carbon density (AGCD)—for the main ecoregions in Mexico. Our results showed that at each ecoregion, unimodal or humped relationships were found between AGCD and fire occurrence, which might be explained by varying constraints of fuel and climate limitation to fire activity. Weibull equations successfully fitted the fire occurrence distributions from AGCD, with the lowest fit for the desert shrub-dominated north region that had the lowest number of observed fires. The models for predicting fire occurrence from AGCD were significantly different by region, with the exception of the temperate forest in the northwest and northeast regions that could be modeled with a single Weibull model. Our results suggest that AGCD could be used to estimate spatial fire occurrence maps; those estimates could be integrated into operational GIS tools for assistance in fire danger mapping and fire and fuel management decision-making. Further investigation of anthropogenic drivers of fire occurrence and fuel characteristics should be considered for improving the operational spatial planning of fire management. The modeling strategy presented here could be replicated in other countries or regions, based on remote-sensed measurements of aboveground biomass and fire activity or fire suppression records