Hydrological resilience to forest fire in the subarctic Canadian Shield

Author(s):  
Christopher Spence ◽  
Newell Hedstrom ◽  
Suzanne Tank ◽  
William Quinton ◽  
David Olefeldt ◽  
...  

<p>Forest fires are becoming more frequent and larger in the subarctic Canadian Shield, so understanding the effect of fire on catchment scale water budgets is becoming increasingly important.  The objective of this study was to determine the water budget impact of a forest fire that partially burned a ~450 km<sup>2</sup> subarctic Canadian Shield basin.  Water budget components were measured in a pair of catchments; one burnt and another unburnt. Burnt and unburnt areas had comparable net radiation, but ground thaw was deeper in burned areas.  Snowpacks were deeper in burns. Differences in streamflow between the catchments were within measurement uncertainty.  Enhanced winter streamflow from the burned watershed was evident by icing growth at the streamflow gauge location, which was not observed in the unburned catchment.  A new framework to assess hydrological resilience to forest fire across the region revealed that watersheds with higher bedrock and open water fractions are more resilient to hydrological change after fire in the subarctic shield, and resilience decreases with increasingly wet conditions.  </p>

2020 ◽  
Author(s):  
Aqil Tariq ◽  
Hong Shu ◽  
Saima Siddiqui

Abstract Background Understanding the spatial patterns of forest fires is of key importance for fire risk management with ecological implications. Fire occurrence, which may result from the presence of an ignition source and the conditions necessary for a fire to spread, is an essential component of fire risk assessment. Methods The aim of this research was to develop a methodology for analyzing spatial patterns of forest fire danger with a case study of tropical forest fire at Margalla Hills, Islamabad, Pakistan. A geospatial technique was applied to explore influencing factors including climate, vegetation, topography, human activities, and 299 fire locations. We investigated the spatial extent of burned areas using Landsat data and determined how these factors influenced the severity rating of fires in these forests. The importance of these factors on forest fires was analyzed and assessed using logistic and stepwise regression methods. Results The findings showed that as the number of total days since the start of fire has increased, the burned areas increased at a rate of 25.848 ha / day (R 2 = 0.98). The average quarterly mean wind speed, forest density, distance to roads and average quarterly maximum temperature were highly correlated to the daily severity rating of forest fires. Only the average quarterly maximum temperature and forest density affected the size of the burnt areas. Fire maps indicate that 22% of forests are at the high and very high level (> 0.65), 25% at the low level (0.45-0.65), and 53% at the very low level (0.25 – 0.45). Conclusion Through spatial analysis, it is found that most forest fires happened in less populated areas and at a long distance from roads, but some climatic and human activities could have influenced fire growth. Furthermore, it is demonstrated that geospatial information technique is useful for exploring forest fire and their spatial distribution.


Environments ◽  
2019 ◽  
Vol 6 (3) ◽  
pp. 30 ◽  
Author(s):  
Ismael Vallejo-Villalta ◽  
Estefanía Rodríguez-Navas ◽  
Joaquín Márquez-Pérez

Forest fires are a critical environmental problem facing current societies, with serious repercussions at ecological, economic and personal safety levels. Detailed maps enabling identification of areas liable to be affected is an indispensable first step allowing different prevention and protection measures vis-à-vis this kind of phenomenon. These maps could be especially valuable for use in land management and emergency planning at a municipality scale. A methodology is shown for producing local maps of mid- and short-term forest fire risk, integrating both natural and human factors. Among natural factors, variables normally used in hazard models are considered as fuel models, slopes or vegetation moisture stress. From the human perspective, more novel aspects have been evaluated, meant either to assess human-induced hazard (closeness to forestland of causative elements or the ability of people to penetrate the forest environment), or to assess vulnerability, considering the population’s location in urban centres and scattered settlements. The methodology is applied in a municipality of Andalusia (Spain) and obtained results were compared to burned areas maps.


2006 ◽  
Vol 15 (3) ◽  
pp. 389 ◽  
Author(s):  
Byungdoo Lee ◽  
Pil Sun Park ◽  
Joosang Chung

Information on the temporal and spatial patterns of forest fires can contribute to efficient forest fire management. To evaluate the readjustment of forest fire precautionary periods and to provide information for forest fire prevention and suppression strategies, the temporal and spatial characteristics of forest fire occurrences and spread in Korea were analysed using statistics from 1970 to 2003. Monthly forest fire occurrences and burned area were examined using time-series analysis, and F-tests were conducted among forest fire occurrences, burned area, and fire area growth rate to understand monthly forest fire characteristics. To understand the spatial characteristics of forest fires, cities and counties with similar forest fire characteristics were grouped based on cluster analysis of forest fire occurrences and spread characteristics. A seasonal exponential smoothing model was selected for forest fire occurrences and burned area. The number of mean annual forest fire occurrences was 429, and mean annual burned area was 2908 ha year–1 in Korea. The seasonal differences in forest fire characteristics were clearly distinguished, with 61% of total forest fire occurrences and 90% of total burned area being in March and April. Forest fire precautionary periods are suggested based on forest fire occurrence patterns. A total of 226 cities and counties throughout the country were classified into three groups. Group 1, which had frequent forest fire occurrences with smaller burned areas and slower fire growth area rates, was distributed in the western part of Korea and metropolitan regions. Group 3, which had a relatively small number of forest fire occurrences but larger burned areas and fast growth rates, was located in the central inland region and the eastern part of the Taeback Mountain Range. Group 2 had characteristics intermediate between those of group 1 and group 3.


2013 ◽  
Vol 59 (No. 7) ◽  
pp. 279-287 ◽  
Author(s):  
M.R. Ullah ◽  
X.D. Liu ◽  
M. Al-Amin

This paper describes the forest fire dynamics in the city of Sanming in Fujian province, China, from 2000 to 2009 with a view to understand the number of fires and burned areas in different counties. It also includes the spatial-temporal distribution of fires and application of the Canadian Forest Fire Danger Rating System (CFFDRS). Daily forest fire data was provided by the Department of Wildfire Prevention of Sanming Forestry Bureau. FWI calculator v.7.0.2.76 was used in this study for analysing the weather parameter data. The results showed that a total of 818 fires and burned areas of 8721.16 ha were found during the study period of 10 years. However, the highest and lowest forest fires were found in Youxi county and Sanming district, respectively. Most of the fires with large burned areas occurred at 2 p.m. Moreover, occurrences of fires were found the highest and lowest in March and June, respectively. Based on FWI calculation, the highest danger rating value was found in March, 2009. This study proposes that it would be possible to manage regular forest fire occurrences through the application of CFFDRS. Finally, to plan the fire prevention and management in southern China and other tropical countries, this system has a great opportunity for further implementations.  


2020 ◽  
Vol 4 (4) ◽  
pp. 813-826
Author(s):  
Mohamed Elhag ◽  
Nese Yimaz ◽  
Jarbou Bahrawi ◽  
Silvena Boteva

AbstractForest fires are a common feature in the Mediterranean forests through the years, as a wide tract of forest fortune is lost because of the incendiary fires in the forests. The enormous damages caused by forest fires enhanced the efforts of scientists towards the attenuation of the negative effects of forest fire and consequently the minimization of biodiversity losses by searching more for the adequate distribution of attempts on forest fire prevention and, suppression. The multi-temporal Principal Components Analysis is applied to a pair of images of consecutive years obtained from Landsat-8 satellite to unconventional map and assess the spatial extent of the burned areas on the island of Thasos, Greece. First, the PCA was applied on the before fire image, and then a multi-temporal image is created from the 3rd, 4th, and 5th band of before and after images including Normalized Difference Vegetation Index to enhance the results. The results from the different steps of this analysis robustly mapped the burned areas by 82.28 ha confirmed by almost 85%. Are compared with data provided by the local forest service in order to assess their accuracy. The multi-temporal PCA outputs including NDVI (PC 4, PC %, and PC 6) give better accuracy due to its ability to distinguish the burned areas of older years and to the Normalized Difference Vegetation Index that gives better variance to the image.


Author(s):  
E. Çolak ◽  
A. F. Sunar

<p><strong>Abstract.</strong> A forest fire is stated as an ecological disaster whether it is man-made or caused naturally. İzmir is one of the regions where forest fires are most intensified in Turkey. The study area located at Aegean region of Turkey suffered two forest fires in 2017; Menderes and Bayındır areas. This study presents the integration of remote sensing (Sentinel 2 and Landsat 8 satellite images) and GIS data to map and evaluate the forest burned areas due to both forest fires. For this purpose, different indexes such as Burn Area Index (BAI), Mid Infrared Burn Index (MIRBI), Normalized Burn Ratio (NBR) and Normalized Burn Ratio Thermal (NBRT) Burn Index are applied besides different classification algorithms. The results showed that different vegetation types/zones are being affected. Sentinel 2 and Landsat 8 data are integrated to the GIS established with fieldwork data to analyse and also validate the results. Digital Elevation Model (DEM) data produced from ASTER satellite is also overlaid to the outcomes to emphasize the destructed forest areas. The efficiency of using two different satellites are outlined by comparing the accuracy of forest fire maps produced.</p>


2020 ◽  
Author(s):  
Jeonghwan KIM ◽  
Joo-Hoon Lim ◽  
Moonhyun Shin ◽  
Seung Hyun Han ◽  
Wonseok Kang

Abstract Background : Forest fire is a natural phenomenon that is very important to afforestation in the secondary succession process. Approximately 349.7 M ha yr -1 of forest had been lost due to forest fire in the world. In Republic of Korea, the forest fires occur at a rate of approximately 400 events yr -1 , and burned areas are mainly located on the eastern coast. In the eastern coastal region, pine forest is widely distributed, and pine forest is changed to oak forest through stump sprout regeneration following forest fires. However, there is a lack of research on oak competition during regeneration in burned areas. Therefore, this research was conducted to evaluate the effects of species composition and the survival ratio of Quercus serrata , Quercus variabilis , and Quercus mongolica in burned areas. The investigation plots were set to investigate tree growth, survival, and composition in Goseong-gun, Republic of Korea. Results : The mean tree heights of Q. serrata and Q. variabilis were approximately 9.8 m and 9.1 m, respectively, which were higher than the approximately 5.8 m heights of Q. mongolica stands 18 years after a forest fire, and the trend for tree diameter at breast height was the same for all three species. In the early stage of regeneration, the survival probability of the Q. serrata sprouts rapidly decreased at a rate 1.7-2.0 times higher than that of other oak species in the Q. serrata -dominant stands. The median survival time of Q. variabilis sprouts in the Q. variabilis -dominant stands was approximately 10.1 years, which was similar to Q. serrata -dominant stands. However, the dominant stand of Q. mongolica was different from that of other dominant stands due to different topography and soil environments located in the ridge and the upper part of the mountain. Conclusion : Dominant species decision seems to be determined by the survival and occurrence of sprouts during the early stage in postfire regenerated oak forests. Therefore, it would be more desirable to coppice sprout for dominant species productivity and rapid dominance after a forest fire.


Author(s):  
Fantina Tedim ◽  
Maria Lúcia de Paula Herrmann

Recent data suggest that both Portugal and Brazil have seen an increase in the number of forest fires in protected areas. In Portugal, between 1992 and 2003 the annual average area burned in protected areas was 10,418 ha and in the period 2001-2005 was 16,025 ha. Nevertheless, in Brazil, the state of Santa Catarina stands out as the state recording a decrease in the number of fires. Based on these facts, the main objectives of the present research are to analyse the incidence, severity and causes of forest fires in protected areas in both countries and to assess the impacts of prevention and combat policies as well as the strategies and models implemented in the recovery of burned areas.


Forests ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 768
Author(s):  
Jin Pan ◽  
Xiaoming Ou ◽  
Liang Xu

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.


2021 ◽  
Vol 13 (1) ◽  
pp. 432
Author(s):  
Aru Han ◽  
Song Qing ◽  
Yongbin Bao ◽  
Li Na ◽  
Yuhai Bao ◽  
...  

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.


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