scholarly journals Mapping the Causes of Forest Fires in Portugal by Clustering Analysis

Geosciences ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 53 ◽  
Author(s):  
Ana C. Meira Castro ◽  
Adélia Nunes ◽  
António Sousa ◽  
Luciano Lourenço
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
False Alarms ◽  
Natural Phenomena ◽  
Mainland Portugal ◽  
Efficient Management ◽  
Preventive Actions ◽  
Or Fires ◽  
Behavior Profile

This paper presents a spatial characterization of the distribution at district level of the forest fire events that occurred in mainland Portugal between 1996 and 2015 and whose causes were investigated. We further examine the breakdown of the causes of these forest fires over this period. Results supported by relevant validated statistics show that of the total fire events recorded, 94.4% were identified as an effective occurrence, of which 22.2% had burned an area greater than 1 ha, and of these only 42.1% were investigated. False alarms or fires without a recorded burning area are more significant in the districts of Aveiro, Lisbon and Porto, the biggest municipalities. Of the fires whose causes were investigated, the largest number of recorded events were in NE regions (49.0%), followed by NW regions (41.7%), and finally in the rest of the country (9.3%). Taking into account the ratio between the investigated fires and the total number of fires and the behavior profile produced for cluster analysis, a different panorama is brought to light, with the center and south regions showing greater effort to investigate the fires. A thorough analysis of the causes and motivations of the ignition of these forest fire occurrences showed that human activity, either deliberate (20.4%) or negligent (29.9%), outweigh natural phenomena (0.6%). Reactivations (14.6%) and Unknown (34.5%) causes decreased as time passed, whereas negligent and deliberate causes increased. However, these results could change if the percentage of unknown information in relation to the origin of the forest fires is considerable. The outcome of this research will support an efficient management related to fire mitigation and suppression including establishing preventive actions to reduce the occurrence of forest fires and emphasize the need to improve the procedure for recording forest fire events in Portugal, especially in relation to identifying their cause.

scholarly journals LOS INCENDIOS FORESTALES EN EL PERÚ: GRAVE PROBLEMA POR RESOLVER

FLORESTA ◽  
2004 ◽  
Vol 34 (2) ◽  
Author(s):  
Maria Isabel Manta Nolasco ◽  
H. León
Keyword(s):  
Decision Making ◽  
Environmental Policy ◽  
Natural Resources ◽  
Forest Fire ◽  
Forest Fires ◽  
Point Of View ◽  
Burned Area ◽  
Toma De Decisiones ◽  
The Impact

El estudio de los incendios forestales en el Perú fue realizado sobre el área nacional, que abarca una superficie de 1´285,215 km2, para el periodo comprendido entre el año 1973 y el año 2000. El objetivo de la investigación fue caracterizar el problema de los incendios forestales peruanos a través de la descripción del ambiente donde se desarrollan los incendios forestales, del impacto de los incendios forestales sobre la población y los recursos naturales, de las estadísticas del área afectada y del número de incendios forestales y de la organización actual para el manejo de los incendios forestales. El análisis del problema permitió diagnosticar un conjunto de factores biofísicos, dificultades y deficiencias en la política ambiental actual, desde el punto de vista de su uso como elementos de toma de decisiones que contribuyan a reducir la gravedad de los incendios forestales en el país. FOREST FIRES IN PERU: A BIG PROBLEM FOR SOLVING Abstract The study of the forest fires in Peru was carried out over the national territory, that amounts in total an area of 1´285,215 km2, for the period 1973- 2000. The goal of the research was the characterization of the forest fire issue in Peru. To do that a set of different criteria were used, namely: the description of the forest fires environment features, the assessment of the impact of fires on the population and natural resources, the forest fires statistics concerning the total number of fires and total burned area and the current organization for forest fires management. The analysis of this problem made possible to diagnose a set of byophisic factors, difficulties and drawbacks in the current environmental policy, from the point of view of their use as decision-making elements that contribute to reduce the current importance of the forest fires problem in the country.

Unmanned Aerial Vehicle (UAV) based Forest Fire Detection and monitoring for reducing false alarms in forest-fires

2020 ◽  
Vol 149 ◽  
pp. 1-16 ◽  
Author(s):  
S. Sudhakar ◽  
V. Vijayakumar ◽  
C. Sathiya Kumar ◽  
V. Priya ◽  
Logesh Ravi ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Forest Fire ◽  
Forest Fires ◽  
Fire Detection ◽  
False Alarms ◽  
Aerial Vehicle ◽  
Forest Fire Detection

scholarly journals Detection and Monitoring of Forest Fires Using Himawari-8 Geostationary Satellite Data in South Korea

2019 ◽  
Vol 11 (3) ◽  
pp. 271 ◽  
Author(s):  
Eunna Jang ◽  
Yoojin Kang ◽  
Jungho Im ◽  
Dong-Won Lee ◽  
Jongmin Yoon ◽  
...  
Keyword(s):  
Machine Learning ◽  
South Korea ◽  
Forest Fire ◽  
Satellite Data ◽  
Forest Fires ◽  
Fire Detection ◽  
Geostationary Satellite ◽  
False Alarms ◽  
Post Processing ◽  
Forest Fire Detection

Geostationary satellite remote sensing systems are a useful tool for forest fire detection and monitoring because of their high temporal resolution over large areas. In this study, we propose a combined 3-step forest fire detection algorithm (i.e., thresholding, machine learning-based modeling, and post processing) using Himawari-8 geostationary satellite data over South Korea. This threshold-based algorithm filtered the forest fire candidate pixels using adaptive threshold values considering the diurnal cycle and seasonality of forest fires while allowing a high rate of false alarms. The random forest (RF) machine learning model then effectively removed the false alarms from the results of the threshold-based algorithm (overall accuracy ~99.16%, probability of detection (POD) ~93.08%, probability of false detection (POFD) ~0.07%, and 96% reduction of the false alarmed pixels for validation), and the remaining false alarms were removed through post-processing using the forest map. The proposed algorithm was compared to the two existing methods. The proposed algorithm (POD ~ 93%) successfully detected most forest fires, while the others missed many small-scale forest fires (POD ~ 50–60%). More than half of the detected forest fires were detected within 10 min, which is a promising result when the operational real-time monitoring of forest fires using more advanced geostationary satellite sensor data (i.e., with higher spatial and temporal resolutions) is used for rapid response and management of forest fires.

scholarly journals A Collaborative Region Detection and Grading Framework for Forest Fire Smoke Using Weakly Supervised Fine Segmentation and Lightweight Faster-RCNN

Forests ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 768
Author(s):  
Jin Pan ◽  
Xiaoming Ou ◽  
Liang Xu
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Learning Strategy ◽  
Early Stage ◽  
Fire Detection ◽  
Surveillance Systems ◽  
Region Detection ◽  
Decision Network ◽  
Fire Smoke ◽  
Weakly Supervised

Forest fires are serious disasters that affect countries all over the world. With the progress of image processing, numerous image-based surveillance systems for fires have been installed in forests. The rapid and accurate detection and grading of fire smoke can provide useful information, which helps humans to quickly control and reduce forest losses. Currently, convolutional neural networks (CNN) have yielded excellent performance in image recognition. Previous studies mostly paid attention to CNN-based image classification for fire detection. However, the research of CNN-based region detection and grading of fire is extremely scarce due to a challenging task which locates and segments fire regions using image-level annotations instead of inaccessible pixel-level labels. This paper presents a novel collaborative region detection and grading framework for fire smoke using a weakly supervised fine segmentation and a lightweight Faster R-CNN. The multi-task framework can simultaneously implement the early-stage alarm, region detection, classification, and grading of fire smoke. To provide an accurate segmentation on image-level, we propose the weakly supervised fine segmentation method, which consists of a segmentation network and a decision network. We aggregate image-level information, instead of expensive pixel-level labels, from all training images into the segmentation network, which simultaneously locates and segments fire smoke regions. To train the segmentation network using only image-level annotations, we propose a two-stage weakly supervised learning strategy, in which a novel weakly supervised loss is proposed to roughly detect the region of fire smoke, and a new region-refining segmentation algorithm is further used to accurately identify this region. The decision network incorporating a residual spatial attention module is utilized to predict the category of forest fire smoke. To reduce the complexity of the Faster R-CNN, we first introduced a knowledge distillation technique to compress the structure of this model. To grade forest fire smoke, we used a 3-input/1-output fuzzy system to evaluate the severity level. We evaluated the proposed approach using a developed fire smoke dataset, which included five different scenes varying by the fire smoke level. The proposed method exhibited competitive performance compared to state-of-the-art methods.

scholarly journals Short-Term Effects of Fire Severity on Vegetation Based on Sentinel-2 Satellite Data

2021 ◽  
Vol 13 (1) ◽  
pp. 432
Author(s):  
Aru Han ◽  
Song Qing ◽  
Yongbin Bao ◽  
Li Na ◽  
Yuhai Bao ◽  
...  
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Vegetation Change ◽  
Fire Severity ◽  
Dynamic Change ◽  
Burned Area ◽  
Fire Event ◽  
Vegetation Dynamic ◽  
Area Index ◽  
Sentinel 2

An important component in improving the quality of forests is to study the interference intensity of forest fires, in order to describe the intensity of the forest fire and the vegetation recovery, and to improve the monitoring ability of the dynamic change of the forest. Using a forest fire event in Bilahe, Inner Monglia in 2017 as a case study, this study extracted the burned area based on the BAIS2 index of Sentinel-2 data for 2016–2018. The leaf area index (LAI) and fractional vegetation cover (FVC), which are more suitable for monitoring vegetation dynamic changes of a burned area, were calculated by comparing the biophysical and spectral indices. The results showed that patterns of change of LAI and FVC of various land cover types were similar post-fire. The LAI and FVC of forest and grassland were high during the pre-fire and post-fire years. During the fire year, from the fire month (May) through the next 4 months (September), the order of areas of different fire severity in terms of values of LAI and FVC was: low > moderate > high severity. During the post fire year, LAI and FVC increased rapidly in areas of different fire severity, and the ranking of areas of different fire severity in terms of values LAI and FVC was consistent with the trend observed during the pre-fire year. The results of this study can improve the understanding of the mechanisms involved in post-fire vegetation change. By using quantitative inversion, the health trajectory of the ecosystem can be rapidly determined, and therefore this method can play an irreplaceable role in the realization of sustainable development in the study area. Therefore, it is of great scientific significance to quantitatively retrieve vegetation variables by remote sensing.

scholarly journals Empirical Research on Climate Warming Risks for Forest Fires: A Case Study of Grade I Forest Fire Danger Zone, Sichuan Province, China

2021 ◽  
Vol 13 (14) ◽  
pp. 7773
Author(s):  
San Wang ◽  
Hongli Li ◽  
Shukui Niu
Keyword(s):  
Wind Speed ◽  
Forest Fire ◽  
Climate Warming ◽  
Forest Fires ◽  
Meteorological Factors ◽  
Sichuan Province ◽  
Danger Zone ◽  
Climatic Regions ◽  
Area Burned ◽  
Forest Fire Danger

The Sichuan province is a key area for forest and grassland fire prevention in China. Forest resources contribute significantly not only to the biological gene pool in the mid latitudes but also in reducing the concentration of greenhouse gases and slowing down global warming. To study and forecast forest fire change trends in a grade I forest fire danger zone in the Sichuan province under climate change, the dynamic impacts of meteorological factors on forest fires in different climatic regions were explored and a model between them was established by using an integral regression in this study. The results showed that the dominant factor behind the area burned was wind speed in three climatic regions, particularly in Ganzi and A’ba with plateau climates. In Ganzi and A’ba, precipitation was mainly responsible for controlling the number of forest fires while it was mainly affected by temperature in Panzhihua and Liangshan with semi-humid subtropical mountain climates. Moreover, the synergistic effect of temperature, precipitation and wind speed was responsible in basin mid-subtropical humid climates with Chengdu as the center and the influence of temperature was slightly higher. The differential forest fire response to meteorological factors was observed in different climatic regions but there was some regularity. The influence of monthly precipitation in the autumn on the area burned in each climatic region was more significant than in other seasons, which verified the hypothesis of a precipitation lag effect. Climate warming and the combined impact of warming effects may lead to more frequent and severe fires.

Associations Between Ambient Particulate Air Pollution and Cognitive Function in Indonesian Children Living in Forest Fire–Prone Provinces

2021 ◽  
pp. 101053952110317
Author(s):  
Bin Jalaludin ◽  
Frances L. Garden ◽  
Agata Chrzanowska ◽  
Budi Haryanto ◽  
Christine T. Cowie ◽  
...  
Keyword(s):  
Air Pollution ◽  
Cognitive Function ◽  
Forest Fire ◽  
Forest Fires ◽  
Regression Models ◽  
Individual Factors ◽  
Aerodynamic Diameter ◽  
Particulate Air Pollution ◽  
Multivariable Models ◽  
Particulate Matter 2.5

Smoke from forest fires can reach hazardous levels for extended periods of time. We aimed to determine if there is an association between particulate matter ≤2.5 µm in aerodynamic diameter (PM2.5) and living in a forest fire–prone province and cognitive function. We used data from the Indonesian Family and Life Survey. Cognitive function was assessed by the Ravens Colored Progressive Matrices (RCPM). We used regression models to estimate associations between PM2.5 and living in a forest fire–prone province and cognitive function. In multivariable models, we found very small positive relationships between PM2.5 levels and RCPM scores (PM2.5 level at year of survey: β = 0.1%; 95% confidence interval [CI] = 0.01% to 0.19%). There were no differences in RCPM scores for children living in forest fire–prone provinces compared with children living in non-forest fire–prone provinces (mean difference = −1.16%, 95% CI = −2.53% to 0.21%). RCPM scores were lower for children who had lived in a forest fire–prone province all their lives compared with children who lived in a non-forest fire–prone province all their life (β = −1.50%; 95% CI = −2.94% to −0.07%). Living in a forest fire–prone province for a prolonged period of time negatively affected cognitive scores after adjusting for individual factors.

scholarly journals Characteristics of Korean Forest Fires and Forest Fire Policies in the Joseon Dynasty Period (1392–1910) Derived From Historical Records

Forests ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 29
Author(s):  
Donghyun Kim
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
East Coast ◽  
Historical Record ◽  
Capital City ◽  
Fire Damage ◽  
Historical Records ◽  
Royal Authority ◽  
Joseon Dynasty ◽  
Fire Stations

This study examined the records of forest fire outbreaks and characteristics over the 518 years of the Joseon Dynasty period (1392–1910) through the analysis of major historical records of Korea. The historical books used in this study were 14 major national historical books, and include the Annals of the Joseon Dynasty (朝鮮王朝實錄), the Diaries of the Royal Secretariat (承政院日記), and the literature was examined, centering on official records of the royal palace in the Joseon Dynasty period. The contents of forest fires recorded in the historical record literature include the overviews of outbreak, forest fire types, and forest fire damage. According to the results of analysis of historical records, the largest forest fire damage was in the forest fire that occurred on the east coast in 1672, in which 65 persons died and in the forest fire that occurred in the same area in 1804, in which 61 persons died and 2600 private houses were destroyed by fire. The causes of fire outbreak were shown to be unknown causes in 42 cases, accidental fires in 10 cases, arson in 3 cases, thunder strike in 3 cases, hunting activities in 2 cases, child playing with fire in 1 case, cultivating activities in 1 case, and house fire in 1 case. Forest fire outbreaks were analyzed by region and by season and according to the results, 56% (39 cases) of the forest fires broke out on the east coast and 73% (46 cases) broke out in the spring. Forest fire policies include those for general forests, those for reserved forests, those for prohibited forests, those for capital city forests, those for royal family’s graves, royal ancestral shrine, and placenta chamber, those for hunting grounds such as martial art teaching fields, and relief policies for people in areas damaged by forest fires, forest fire policies for national defense facilities such as beacon fire stations, and burning and burning control policies for pest control. In conclusion, due to the seriousness of forest fires in the Joseon Dynasty period, the royal authority and local administrative agencies made various forest fire prevention policies, policies for stabilization of the people’s livelihood damaged due to forest fires, and methods to manage major facilities in forests.

Comparison of the mineralogical effects of an experimental forest fire on a goethite/ferrihydrite soil with a topsoil that contains hematite, maghemite and goethite

Clay Minerals ◽  
2009 ◽  
Vol 44 (2) ◽  
pp. 239-247 ◽  
Author(s):  
P. Nørnberg ◽  
A. L. Vendelboe ◽  
H. P. Gunnlaugsson ◽  
J. P. Merrison ◽  
K. Finster ◽  
...  
Keyword(s):  
Organic Matter ◽  
High Temperature ◽  
Forest Fire ◽  
Forest Fires ◽  
Organic Matter Content ◽  
Matter Content ◽  
Humid Climate ◽  
Fe Mineralogy ◽  
Reducing Environment

AbstractA long-standing unresolved puzzle related to the Danish temperate humid climate is the presence of extended areas with large Fe contents, where goethite and ferrihydrite are present in the topsoil along with hematite and maghemite. Hematite and, particularly, maghemite would normally be interpreted as the result of high temperature as found after forest fires. However, a body of evidence argues against these sites having been exposed to fire. In an attempt to get closer to an explanation of this Fe mineralogy, an experimental forest fire was produced. The results showed a clear mineralogical zonation down to 10 cm depth. This was not observed at the natural sites, which contained a mixture of goethite/ferrihydrite, hematite and maghemite down to 20 cm depth. The experimental forest fire left charcoal and ashes at the topsoil, produced high pH and decreased organic matter content, all of which is in contrast to the natural sites. The conclusion from this work is that the mineralogy of these sites is not consistent with exposure to forest fire, but may instead result from long-term transformation in a reducing environment, possibly involving microbiology.

Incidence and recurrence of large forest fires in mainland Portugal

2016 ◽  
Vol 84 (2) ◽  
pp. 1035-1053 ◽  
Author(s):  
F. Ferreira-Leite ◽  
A. Bento-Gonçalves ◽  
A. Vieira ◽  
A. Nunes ◽  
L. Lourenço
Keyword(s):  
Forest Fires ◽  
Mainland Portugal
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