scholarly journals Spatialtemporal Patterns of MODIS Active Fire/Hotspots in Chiang Rai, Upper Northern Thailand and the Greater Mekong Subregion Countries During 2003-2015

2021 ◽  
pp. 121-131
Author(s):  
Chidsanuphong Chart-asa
Keyword(s):  
Forest Fires ◽  
Temporal Analysis ◽  
Northern Thailand ◽  
Open Burning ◽  
Active Fire ◽  
Haze Pollution ◽  
Administrative Unit ◽  
Radiative Power ◽  
In Fire ◽  
Current Monitoring

For the past decade, smoke-haze pollution from forest fires and open burning has been a yearly recurring problem over Chiang Rai and other provinces in Upper Northern Thailand, along with other countries in the Greater Mekong Sub-region. Remote-sensing active fire/ hotspot data are currently used for monitoring the forest fires and open burning in the sub-region. This study aimed to extend the current monitoring work by performing spatial and temporal analysis to examine the patterns, either globally or locally, of MODIS active fires/hotspots during the critical smoke-haze pollution periods from January to April in 2003-2015. Fire radiative power was used as a weight attribute for each active fire/hotspot. Administrative unit maps were used for aggregating data and creating spatial weight matrices. Results indicated that for all the years over the investigated period and based on detected locations, active fires/hotspots were overall clustered spatially across provincial, interprovincial, and international scales. Their density patterns were locally variable for each year, but the high concentrated zones, in terms of both fire counts and fire radiative powers, were consistently bounded in the hilly and mountainous areas, confirming that the forest fires and open burning problem keeps recurring in certain areas. When aggregated by administrative unit, the administrative boundaries with high active fires/hotspots, in terms of both fire counts and fire radiative powers, were spatially clustered, either globally or locally, but there was only an increasing trend of the clustering intensity in fire radiative powers, implying that the forest fires and open burning problem have become more severe in particular areas. These findings could be useful for further reviewing and strengthening current measures and plans of fire and smoke haze pollution management.

scholarly journals Twenty-first century droughts have not increasingly exacerbated fire season severity in the Brazilian Amazon

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
R. Libonati ◽  
J. M. C. Pereira ◽  
C. C. Da Camara ◽  
L. F. Peres ◽  
D. Oom ◽  
...  
Keyword(s):  
Forest Fires ◽  
Brazilian Amazon ◽  
First Century ◽  
Fire Season ◽  
Fire Intensity ◽  
Amazon Forest ◽  
Active Fire ◽  
Fire Activity ◽  
Twenty First Century ◽  
In Fire

AbstractBiomass burning in the Brazilian Amazon is modulated by climate factors, such as droughts, and by human factors, such as deforestation, and land management activities. The increase in forest fires during drought years has led to the hypothesis that fire activity decoupled from deforestation during the twenty-first century. However, assessment of the hypothesis relied on an incorrect active fire dataset, which led to an underestimation of the decreasing trend in fire activity and to an inflated rank for year 2015 in terms of active fire counts. The recent correction of that database warrants a reassessment of the relationships between deforestation and fire. Contrasting with earlier findings, we show that the exacerbating effect of drought on fire season severity did not increase from 2003 to 2015 and that the record-breaking dry conditions of 2015 had the least impact on fire season of all twenty-first century severe droughts. Overall, our results for the same period used in the study that originated the fire-deforestation decoupling hypothesis (2003–2015) show that decoupling was clearly weaker than initially proposed. Extension of the study period up to 2019, and novel analysis of trends in fire types and fire intensity strengthened this conclusion. Therefore, the role of deforestation as a driver of fire activity in the region should not be underestimated and must be taken into account when implementing measures to protect the Amazon forest.

Spatio-Temporal Typology of Land and Forest Fire in Sumatra

2016 ◽  
Vol 4 (1) ◽  
pp. 83 ◽  
Author(s):  
Israr Albar ◽  
I. Nengah Surati Jaya ◽  
Bambang Hero Saharjo ◽  
Budi Kuncahyo
Keyword(s):  
Forest Fires ◽  
Geographic Location ◽  
Temporal Analysis ◽  
Forest Area ◽  
Single Linkage ◽  
Active Fire ◽  
Linkage Method ◽  
Spatio Temporal ◽  
Key Indicators ◽  
Typology Analysis

<p>The characteristic of land and forest fires occurred in Indonesia are varied widely, following the variation of time within a year and geographic location. This paper describes how the spatio-temporal of forest and land fire typology was developed. The main objective of this study was to develop a spatio-temporal typology of forest and land fire by considering several key indicators that directly related to the density of active fire occurrence, such as percentage of forest area (x<sub>1</sub>), population density (x<sub>2</sub>), ratio of forest area to population (x<sub>3</sub>), ratio of plantation area to population (x<sub>4</sub>), ratio of agriculture area to population (x<sub>5</sub>), GRDP (x<sub>6</sub>), population growth (x<sub>7</sub>), deforestation growth (x<sub>8</sub>), plantation growth (x<sub>9</sub>) and dry agriculture growth (x<sub>10</sub>) as well as  MODIS-based fire hotspot. The typology analysis was performed using clustering techniques with Euclidean distance dissimilarity measure, where the grouping process was drawn with single linkage method. The temporal analysis showed that the highest occurrence of the fire hotspot was mainly found in the third quarter. It was found that the forest and land fire typology could be developed into three classes using variables x<sub>6</sub> and x<sub>7</sub> with overall accuracy of 78.15% or x<sub>1</sub>-x<sub>6</sub>-x<sub>7</sub> with overall accuracy of 78.8%.  No accuracy improvement was obtained when the typology was developed using five variables x<sub>1</sub>-x<sub>3</sub>-x<sub>4</sub>-x<sub>6</sub>-x<sub>7.</sub><em></em></p>

scholarly journals A Deep Learning Approach to Downscale Geostationary Satellite Imagery for Decision Support in High Impact Wildfires

Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 294
Author(s):  
Nicholas F. McCarthy ◽  
Ali Tohidi ◽  
Yawar Aziz ◽  
Matt Dennie ◽  
Mario Miguel Valero ◽  
...  
Keyword(s):  
Deep Learning ◽  
Decision Support ◽  
Real Time ◽  
Forest Fires ◽  
Wildland Fire ◽  
Fire Spread ◽  
Low Earth Orbit ◽  
Practical Implementation ◽  
Spatiotemporal Resolution ◽  
Active Fire

Scarcity in wildland fire progression data as well as considerable uncertainties in forecasts demand improved methods to monitor fire spread in real time. However, there exists at present no scalable solution to acquire consistent information about active forest fires that is both spatially and temporally explicit. To overcome this limitation, we propose a statistical downscaling scheme based on deep learning that leverages multi-source Remote Sensing (RS) data. Our system relies on a U-Net Convolutional Neural Network (CNN) to downscale Geostationary (GEO) satellite multispectral imagery and continuously monitor active fire progression with a spatial resolution similar to Low Earth Orbit (LEO) sensors. In order to achieve this, the model trains on LEO RS products, land use information, vegetation properties, and terrain data. The practical implementation has been optimized to use cloud compute clusters, software containers and multi-step parallel pipelines in order to facilitate real time operational deployment. The performance of the model was validated in five wildfires selected from among the most destructive that occurred in California in 2017 and 2018. These results demonstrate the effectiveness of the proposed methodology in monitoring fire progression with high spatiotemporal resolution, which can be instrumental for decision support during the first hours of wildfires that may quickly become large and dangerous. Additionally, the proposed methodology can be leveraged to collect detailed quantitative data about real-scale wildfire behaviour, thus supporting the development and validation of fire spread models.

scholarly journals Drone Swarms in Fire Suppression Activities: A Conceptual Framework

Drones ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 17
Author(s):  
Elena Ausonio ◽  
Patrizia Bagnerini ◽  
Marco Ghio
Keyword(s):  
Technological Development ◽  
Fire Suppression ◽  
Water Flow Rate ◽  
Cellular Automata Model ◽  
Fire Propagation ◽  
Active Fire ◽  
Fire Front ◽  
Main Factors ◽  
Mediterranean Scrub ◽  
In Fire

The recent huge technological development of unmanned aerial Vehicles (UAVs) can provide breakthrough means of fighting wildland fires. We propose an innovative forest firefighting system based on the use of a swarm of hundreds of UAVs able to generate a continuous flow of extinguishing liquid on the fire front, simulating the effect of rain. Automatic battery replacement and extinguishing liquid refill ensure the continuity of the action. We illustrate the validity of the approach in Mediterranean scrub first computing the critical water flow rate according to the main factors involved in the evolution of a fire, then estimating the number of linear meters of active fire front that can be extinguished depending on the number of drones available and the amount of extinguishing fluid carried. A fire propagation cellular automata model is also employed to study the evolution of the fire. Simulation results suggest that the proposed system can provide the flow of water required to fight low-intensity and limited extent fires or to support current forest firefighting techniques.

Modelling the effects of distance on the probability of fire detection from lookouts

2006 ◽  
Vol 15 (2) ◽  
pp. 197 ◽  
Author(s):  
Francisco Castro Rego ◽  
Filipe Xavier Catry
Keyword(s):  
Forest Fires ◽  
Detection System ◽  
Fire Detection ◽  
Fast Response ◽  
Fire Loss ◽  
Detection Function ◽  
Related Factors ◽  
New Approach ◽  
Forest Fire Management ◽  
In Fire

In the management of forest fires, early detection and fast response are known to be the two major actions that limit both fire loss and fire-associated costs. There are several inter-related factors that are crucial in producing an efficient fire detection system: the strategic placement and networking of lookout towers, the knowledge of the fire detection radius for lookout observers at a given location and the ability to produce visibility maps. This study proposes a new methodology in the field of forest fire management, using the widely accepted Fire Detection Function Model to evaluate the effect of distance and other variables on the probability that an object is detected by an observer. In spite of the known variability, the model seems robust when applied to a wide variety of situations, and the results obtained for the effective detection radius (13.4 km for poor conditions and 20.6 km for good conditions) are in general agreement with those proposed by other authors. We encourage the application of the new approach in the evaluation or planning of lookout networks, in addition to other integrated systems used in fire detection.

scholarly journals Fractal properties of forest fires in Amazonia as a basis for modelling pan-tropical burnt area

2014 ◽  
Vol 11 (6) ◽  
pp. 1449-1459 ◽  
Author(s):  
I. N. Fletcher ◽  
L. E. O. C. Aragão ◽  
A. Lima ◽  
Y. Shimabukuro ◽  
P. Friedlingstein
Keyword(s):  
Forest Fires ◽  
Large Scale ◽  
Fire Spread ◽  
Small Scale ◽  
Burnt Area ◽  
Active Fire ◽  
Fractal Properties ◽  
Dynamic Global Vegetation Models ◽  
Vegetation Models ◽  
Global Vegetation

Abstract. Current methods for modelling burnt area in dynamic global vegetation models (DGVMs) involve complex fire spread calculations, which rely on many inputs, including fuel characteristics, wind speed and countless parameters. They are therefore susceptible to large uncertainties through error propagation, but undeniably useful for modelling specific, small-scale burns. Using observed fractal distributions of fire scars in Brazilian Amazonia in 2005, we propose an alternative burnt area model for tropical forests, with fire counts as sole input and few parameters. This model is intended for predicting large-scale burnt area rather than looking at individual fire events. A simple parameterization of a tapered fractal distribution is calibrated at multiple spatial resolutions using a satellite-derived burnt area map. The model is capable of accurately reproducing the total area burnt (16 387 km2) and its spatial distribution. When tested pan-tropically using the MODIS MCD14ML active fire product, the model accurately predicts temporal and spatial fire trends, but the magnitude of the differences between these estimates and the GFED3.1 burnt area products varies per continent.

scholarly journals Production of peroxy nitrates in boreal biomass burning plumes over Canada during the BORTAS campaign

2016 ◽  
Vol 16 (5) ◽  
pp. 3485-3497 ◽  
Author(s):  
Marcella Busilacchio ◽  
Piero Di Carlo ◽  
Eleonora Aruffo ◽  
Fabio Biancofiore ◽  
Cesare Dari Salisburgo ◽  
...  
Keyword(s):  
Boreal Forest ◽  
Forest Fire ◽  
Biomass Burning ◽  
Forest Fires ◽  
Chemical Mechanism ◽  
Fire Emissions ◽  
Fire Plumes ◽  
Peroxy Nitrates ◽  
In Fire ◽  
The Impact

Abstract. The observations collected during the BOReal forest fires on Tropospheric oxidants over the Atlantic using Aircraft and Satellites (BORTAS) campaign in summer 2011 over Canada are analysed to study the impact of forest fire emissions on the formation of ozone (O3) and total peroxy nitrates ∑PNs, ∑ROONO2). The suite of measurements on board the BAe-146 aircraft, deployed in this campaign, allows us to calculate the production of O3 and of  ∑PNs, a long-lived NOx reservoir whose concentration is supposed to be impacted by biomass burning emissions. In fire plumes, profiles of carbon monoxide (CO), which is a well-established tracer of pyrogenic emission, show concentration enhancements that are in strong correspondence with a significant increase of concentrations of ∑PNs, whereas minimal increase of the concentrations of O3 and NO2 is observed. The ∑PN and O3 productions have been calculated using the rate constants of the first- and second-order reactions of volatile organic compound (VOC) oxidation. The ∑PN and O3 productions have also been quantified by 0-D model simulation based on the Master Chemical Mechanism. Both methods show that in fire plumes the average production of ∑PNs and O3 are greater than in the background plumes, but the increase of ∑PN production is more pronounced than the O3 production. The average ∑PN production in fire plumes is from 7 to 12 times greater than in the background, whereas the average O3 production in fire plumes is from 2 to 5 times greater than in the background. These results suggest that, at least for boreal forest fires and for the measurements recorded during the BORTAS campaign, fire emissions impact both the oxidized NOy and O3,  but (1 ∑PN production is amplified significantly more than O3 production and (2) in the forest fire plumes the ratio between the O3 production and the ∑PN production is lower than the ratio evaluated in the background air masses, thus confirming that the role played by the ∑PNs produced during biomass burning is significant in the O3 budget. The implication of these observations is that fire emissions in some cases, for example boreal forest fires and in the conditions reported here, may influence more long-lived precursors of O3 than short-lived pollutants, which in turn can be transported and eventually diluted in a wide area.

Evaluation of critical atmospheric patterns for the occurrence of forest fires in a climate change context in the northwest of Argentine Patagonia.

2021 ◽  
Author(s):  
Verónica Dankiewicz ◽  
Matilde M. Rusticucci ◽  
Soledad M. Collazo
Keyword(s):  
Climate Change ◽  
Forest Fires ◽  
Fire Hazard ◽  
Fire Danger ◽  
Fire Season ◽  
Historical Period ◽  
Fire Weather Index ◽  
Mitigation And Adaptation ◽  
Argentine Patagonia ◽  
In Fire

&lt;p&gt;Forest fires are a global phenomenon and result from complex interactions between weather and climate conditions, ignition sources, and humans. Understanding these relationships will contribute to the development of management strategies for their mitigation and adaptation. In the context of climate change, fire hazard conditions are expected to increase in many regions of the world due to projected changes in climate, which include an increase in temperatures and the occurrence of more intense droughts. In Argentina, northwestern Patagonia is an area very sensitive to these changes because of its climate, vegetation, the urbanizations highly exposed to fires, and the proximity of two of the largest and oldest National Parks in the country. The main objective of this work is to analyze the possible influence of climate change on some atmospheric patterns related to fire danger in northwestern Argentine Patagonia. The data were obtained from two CMIP5 global climate models CSIRO-Mk3-6-0 and GFDL-ESM2G and the CMIP5 multimodel ensemble, in the historical experiment and two representative concentration pathways: RCP2.6 and RCP8.5. The data used in this study cover the region's fire season (FS), from September to April, and were divided into five periods of 20 years each, a historical period (1986-2005), which was compared with four future periods: near (2021-2040), medium (2041-2060), far (2061-2080) and very far (2081-2100). The statistical distribution of the monthly composite fields of the FS was studied for some of the main fire drivers: sea surface temperature in the region of the index EN3.4 (SST EN3.4), sea level pressure anomalies &amp;#8203;&amp;#8203;(SLP), surface air temperature anomalies (TAS), the Antarctic Oscillation Index (AOI) and monthly accumulated precipitation (PR). In addition, the partial correlation coefficient was calculated to determine the independent contribution of each atmospheric variable to the Fire Weather Index (FWI), used as a proxy for the mean FS danger. As a result, we observed that SST EN3.4 is the only one that could indicate a reduction in fire danger in the future, although no variable presented a significant contribution to the FWI with respect to the others. In the RCP8.5 scenario, greater fire danger is projected by the TAS, the PR, the SLP, and relative by the AOI, while in the RCP2.6 scenario, only the TAS shows influence leading to an increase, which would be offset by the opposite influence of SST EN3.4 for the same periods in this scenario. In conclusion, in RCP8.5 it could be assumed that there is a trend towards an increase in fire danger given the influence in this sense of most of the variables analyzed, but not in RCP2.6 where there would be no significant changes.&lt;/p&gt;

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