scholarly journals Fire spread prediction for deciduous forest fires in Northern Thailand

ScienceAsia ◽  
2013 ◽  
Vol 39 (5) ◽  
pp. 535 ◽  
Author(s):  
Agapol Junpen ◽  
Savitri Garivait ◽  
Sebastien Bonnet ◽  
Adisak Pongpullponsak
PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0256005
Author(s):  
Siriluck Thammanu ◽  
Hee Han ◽  
Dokrak Marod ◽  
Jamroon Srichaichana ◽  
Joosang Chung

This study aimed to investigate the structure of two deciduous forests and assess their above-ground carbon stock in order to promote community forest management (CFM) for REDD+ opportunities in the Ban Mae Chiang Rai Lum Community Forest in northern Thailand. A systematic sampling method was used to establish twenty-five sample plots of 40 m × 40 m (0.16 ha) each that were used to survey the entire 3,925 ha area of the community forest. Cluster analysis identified two different forest types: dry dipterocarp forest and mixed deciduous forest. It was determined that the above-ground carbon stock did not vary significantly between them. An analysis of carbon sequestration in the community forest indicates that carbon stock increased under CFM from 2007 to 2018 by an estimated 28,928 t C and participation in the carbon market would have yielded approximately US $339,730.43 or US $8.66 /ha/year to the community for that 10-year period. Projections for 2028 reflect that carbon stock will experience continual growth which indicates that maintaining CFM can increase carbon sequestration and reduce CO2 emissions. However, though further growth of carbon stock in the community forest is expected into 2038, that growth would be at a lesser rate than during the preceding decade. This suggests that CFM management should address forest utilization practices with a focus on maintaining long term carbon stock growth. Additional measures to address the impact of drought conditions and to safeguard against forest fires are required to sustain tree species’ growth and expansion in order to increase their carbon accumulation potential. Thailand’s community forest involvement in REDD+ and participation in its international carbon market could create more economic opportunities for local communities.


Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 294
Author(s):  
Nicholas F. McCarthy ◽  
Ali Tohidi ◽  
Yawar Aziz ◽  
Matt Dennie ◽  
Mario Miguel Valero ◽  
...  

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.


2014 ◽  
Vol 11 (6) ◽  
pp. 1449-1459 ◽  
Author(s):  
I. N. Fletcher ◽  
L. E. O. C. Aragão ◽  
A. Lima ◽  
Y. Shimabukuro ◽  
P. Friedlingstein

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.


2007 ◽  
Vol 16 (2) ◽  
pp. 174 ◽  
Author(s):  
Kerry Anderson ◽  
Gerhard Reuter ◽  
Mike D. Flannigan

The focus of this investigation is to quantify the effects of perturbations in the meteorological data used in a fire-growth model. Observed variations of temperature, humidity, wind speed, and wind direction are applied as perturbations to hourly values within a simulated weather forecast to produce several forecasts. In turn, these are used by a deterministic eight-point fire-growth model to produce an ensemble of possible final fire perimeters. Two studies were conducted to assess the value of applying perturbations. In the first study, fire growth using detailed, one-minute data was compared to growth based on the more commonly used hourly data. Results showed that the detailed weather produced fire growth larger and wider than the hourly based data. By applying perturbations, variations in the flank and back-fire spread were captured by the random-perturbation model while the forward spread fell within the 20 to 30% probability prediction. A sensitivity analysis based on the observed variations showed that wind speed accounted for a 44% difference in area burned, while temperature accounted for only a 16% difference. In the second study, case studies were conducted on four observed forest fires in Wood Buffalo National Park. Results showed that daily fire-growth predictions using simulated weather forecasts over-predicted fire growth using actual hourly weather observations by 27%. Systematic-perturbation models best compensated for this with most fire growth falling within the predicted range of the models (52 out of 63 days).


Author(s):  
Koyu Satoh ◽  
Naian Liu ◽  
Qiong Liu ◽  
K. T. Yang

It is important to examine the behavior of forest fires and city fires to mitigate the property damages and victims by fires. There have been many previous studies on forest fires where the fire spreading patterns were investigated, utilizing artificial satellite pictures of forest fires, together with the use of corresponding weather data and GIS data. On the other hand, large area city fires are very scarce in the world, particularly in modern cities where high-rise concrete buildings are constructed with sufficient open spaces. Thus, the examples of city fires to be referred are few and detailed investigations of city fires are limited. However, there have still been existing old cities where traditional houses built with flammable material such as wood, maybe historically important, only separated with very small open spacing. Fires may freely spread in those cities, once a big earthquake happens there and then water supply for the fire brigade is damaged in the worst case along with the effect of strong wind. There are some fundamental differences between the forest fires and city fires, as the fuel may distribute either continuously or discretely. For instance, in forest fires, the dead fallen leaves, dry grasses and trees are distributed continuously on the ground, while the wooden houses in cities are discretely distributed with some separation of open spacing, such as roads and gardens. Therefore, the wooden houses neighboring the burning houses with some separation are heated by radiation and flames to elevate the temperatures, thus causing the ignition, and finally reaching a large city fire. The authors have studied the forest fire spread and are planning to start a laboratory experiment of city fire spreading. In the preliminary investigation, a numerical study is made to correlate with the laboratory experiment of city fire propagation, utilizing the three-dimensional CFD simulations. Based on the detailed experimental analysis, the authors are attempting to modify the three dimensional CFD code to predict the forest fires and city fires more precisely, taking into account the thermal heating and ignition processes. In this study, some fundamental information on the city fire propagation has been obtained, particularly to know the safe open spacing distances between the houses in the cities and also the wind speed.


Author(s):  
Hadj Miloua

Current study focuses to the application of an advanced physics-based (reaction–diffusion) fire behavior model to the fires spreading through surface vegetation such as grasslands and elevated vegetation such as trees present in forest stands. This model in three dimensions, called Wildland Fire Dynamics Simulator WFDS, is an extension, to vegetative fuels, of the structural FDS developed at NIST. For simplicity, the vegetation was assumed to be uniformly distributed in a tree crown represented by a well defined geometric shape. This work on will focus on predictions of thermal function such as the radiation heat transfer and and thermal function for diverse cases of spatial distribution of vegetation in forest stands. The influence of wind, climate characteristics and terrain topography will also be used to extend and validate the model. The results obtained provide a basis to carry out a risk analysis for fire spread in the studied vegetative fuels in the Mediterranean forest fires.


Phytotaxa ◽  
2017 ◽  
Vol 307 (1) ◽  
pp. 84 ◽  
Author(s):  
PHATTARAVEE PROMMANUT ◽  
MANIT KIDYOO ◽  
WINS BUDDHAWONG ◽  
SOMRAN SUDDEE

Dendrobium chiangdaoense, a new species belonging to Dendrobium section Stachyobium is described and illustrated. It is only known from the type locality in mixed deciduous forest at ca. 800 m elev. on limestone hills in Chiang Dao District, Chiang Mai Province, northern Thailand. It most closely resembles D. dixonianum, a more widespread northern Thailand species occurring in upper montane rain forest at 1,650–1,800 m elev.


2013 ◽  
Vol 10 (8) ◽  
pp. 14141-14167 ◽  
Author(s):  
I. N. Fletcher ◽  
L. E. O. C. Aragão ◽  
A. Lima ◽  
Y. Shimabukuro ◽  
P. Friedlingstein

Abstract. Current methods for modelling burnt area in Dynamic Global Vegetation Models 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. Using observed fractal distributions of fire scars in Brazilian Amazonia, we propose an alternative burnt area model for tropical forests, with fire counts as sole input and few parameters. Several parameterizations of two possible distributions are calibrated at multiple spatial resolutions using a satellite-derived burned area map, and compared. The tapered Pareto model most accurately simulates the total area burnt (only 3.5 km2 larger than the recorded 16 387 km2) and its spatial distribution. When tested pan-tropically using MODIS MCD14ML fire counts, the model accurately predicts temporal and spatial fire trends, but produces generally higher estimates than the GFED3.1 burnt area product, suggesting higher pan-tropical carbon emissions from fires than previously estimated.


Author(s):  
Kohyu Satoh ◽  
Liu Naian ◽  
Liu Qiong ◽  
K. T. Yang

In large-scale forest fires and city fires, merging fires and fire whirls have often been observed, which cause substantial casualties and property damages. It is important to know particularly where and under what conditions of weather such merging fires and fire whirls appear in cities or forests. However, there have been no adequate answers, since the detailed physical characteristics about them are not fully clarified yet, although previous studies have examined the phenomena of merging flames. Therefore, we have carried out preliminary studies and found that the merged tall fires can enhance the fire spread, and developed a method to analyze burn-out data of fire arrays. If sufficient knowledge can be obtained by relevant experiments and numerical computations, it may be possible to mitigate the damages due to merged fires and fire whirls. The objective of this study is to investigate the merging conditions of fires in square arrays in laboratory experiments and also by CFD numerical simulations, varying the size of square array, inter-fire distance and heat release rate, to judge ‘unmerged’ or ‘merged’ conditions in the fire array. It has been found that the fire merging is dependent on the inter-fire distance in the array and also on the total heat release rate of all fires surrounding the center region of the array. Also found that the experimental and simulated results on the merged and unmerged cases in the fire array, as affected by the total heat release rate and the inter-fire distance, which control the convective gas flow into the array, behave very similarly. Therefore, it can be concluded that the fire merging in array fires are highly based on the convection in the flow field due to fires and can be predicted by simple CFD simulations.


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