scholarly journals Effects of prescribed forest burning on carabid beetles (Coleoptera: Carabidae): a case study in south-eastern Norway

2006 ◽  
Vol 17 (3) ◽  
Author(s):  
Konstantin Gongalsky ◽  
Fred Midtgaard ◽  
Hans Overgaard
Keyword(s):  
Forest Fires ◽  
Prescribed Burning ◽  
Abundant Species ◽  
Carabid Beetles ◽  
Burned Area ◽  
Burned Areas ◽  
Clear Cut ◽  
Se Norway ◽  
Eastern Norway

The influence of prescribed burning on ground beetles was studied in a single 12 ha stand that was partially clear-cut, selectively-cut and retained (= standing forest), and was compared to an unburned stand in 2002 in SE Norway. Thirty-two species were collected using Barber pitfall traps. Carabids were more numerous and more diverse in the burned area, compared to the unburned forest. Overall abundance was highest in the selectively-cut treatment, followed by the clear-cut and standing forest. Species diversity tended to increase in the sequence unburned forest – burned standing forest – burned selectively-cut – burned clearcut. Species composition differed little between the burned treatments. Pterostichus adstrictus, a species associated with open habitats and which frequently colonizes burned areas, was the most abundant species collected. It was most common in the burned area, particularly in the selectively-cut treatment. Our results suggest that burning of a single stand may support some carabid species, even endangered ones, although larger forest fires are probablymore effective for conservation purposes.

scholarly journals Exploitation of Sentinel-2 Time Series to Map Burned Areas at the National Level: A Case Study on the 2017 Italy Wildfires

2019 ◽  
Vol 11 (6) ◽  
pp. 622 ◽  
Author(s):  
Federico Filipponi
Keyword(s):  
Time Series ◽  
Spatial Resolution ◽  
Satellite Data ◽  
High Spatial Resolution ◽  
National Level ◽  
Burned Area ◽  
Commission Error ◽  
Burned Areas ◽  
Sentinel 2

Satellite data play a major role in supporting knowledge about fire severity by delivering rapid information to map fire-damaged areas in a precise and prompt way. The high availability of free medium-high spatial resolution optical satellite data, offered by the Copernicus Programme, has enabled the development of more detailed post-fire mapping. This research study deals with the exploitation of Sentinel-2 time series to map burned areas, taking advantages from the high revisit frequency and improved spatial and spectral resolution of the MSI optical sensor. A novel procedure is here presented to produce medium-high spatial resolution burned area mapping using dense Sentinel-2 time series with no a priori knowledge about wildfire occurrence or burned areas spatial distribution. The proposed methodology is founded on a threshold-based classification based on empirical observations that discovers wildfire fingerprints on vegetation cover by means of an abrupt change detection procedure. Effectiveness of the procedure in mapping medium-high spatial resolution burned areas at the national level was demonstrated for a case study on the 2017 Italy wildfires. Thematic maps generated under the Copernicus Emergency Management Service were used as reference products to assess the accuracy of the results. Multitemporal series of three different spectral indices, describing wildfire disturbance, were used to identify burned areas and compared to identify their performances in terms of spectral separability. Result showed a total burned area for the Italian country in the year 2017 of around 1400 km2, with the proposed methodology generating a commission error of around 25% and an omission error of around 40%. Results demonstrate how the proposed procedure allows for the medium-high resolution mapping of burned areas, offering a benchmark for the development of new operational downstreaming services at the national level based on Copernicus data for the systematic monitoring of wildfires.

Monitoring Forest Fire using Geo-Spatial Information Techniques and Spatial Statistics: One Case Study of Forest fire in Margalla Hills, Islamabad, Pakistan

2020 ◽  
Author(s):  
Aqil Tariq ◽  
Hong Shu ◽  
Saima Siddiqui
Keyword(s):  
Spatial Patterns ◽  
Forest Fire ◽  
Forest Fires ◽  
Human Activities ◽  
Fire Risk ◽  
Maximum Temperature ◽  
Forest Density ◽  
Burned Areas ◽  
Severity Rating

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.

scholarly journals Spatial scales influence long-term response of herbivores to prescribed burning in a savanna ecosystem

2017 ◽  
Vol 26 (4) ◽  
pp. 287 ◽  
Author(s):  
Duncan M. Kimuyu ◽  
Ryan L. Sensenig ◽  
Robert M. Chira ◽  
John M. Githaiga ◽  
Truman P. Young
Keyword(s):  
Prescribed Burning ◽  
Spatial Scales ◽  
Fire Effects ◽  
Spatial Extent ◽  
Burned Area ◽  
Burned Areas ◽  
Spatial And Temporal Heterogeneity ◽  
Intermediate Size ◽  
Term Response

Both wild and prescribed fire in savanna ecosystems influence habitat use by herbivores by creating or maintaining spatial and temporal heterogeneity in forage quality and vegetation cover. Yet little is known about how spatial scales influence long-term persistence of fire effects. We examined changes over a 6-year period in herbivore preference for experimentally burned patches that varied in spatial extent and grain. Avoidance for the burns by elephants and preference for the burns by impala and Grant’s gazelle decreased significantly. For the rest of the species (zebra, eland, oryx, hartebeest, warthog and hare), there were no significant changes in preference for the burns. Changes in preference for the burned areas depended on the spatial extent and grain of the burn, with intermediate-size (9-ha) burns and large (8-ha) patchy burns being more preferred 6–7 years after fire. Grain, but not the spatial extent of the burned area, influenced changes in grass height. Fire resulted in a delayed reduced tree density irrespective of the spatial scale of the burn. Results of this study indicate that, depending on the scale of fire prescription, the impacts of fire on herbivores may last longer than previous studies suggest.

scholarly journals Burned Area Mapping over the Southern Cape Forestry Region, South Africa Using Sentinel Data within GEE Cloud Platform

2021 ◽  
Vol 10 (8) ◽  
pp. 511
Author(s):  
Sifiso Xulu ◽  
Nkanyiso Mbatha ◽  
Kabir Peerbhay
Keyword(s):  
South Africa ◽  
Forest Fires ◽  
Google Earth ◽  
Burned Area ◽  
Western Cape ◽  
Planted Forests ◽  
Poor Countries ◽  
Burned Areas ◽  
Forestry Industry ◽  
High Level

Planted forests in South Africa have been affected by an increasing number of economically damaging fires over the past four decades. They constitute a major threat to the forestry industry and account for over 80% of the country’s commercial timber losses. Forest fires are more frequent and severe during the drier drought conditions that are typical in South Africa. For proper forest management, accurate detection and mapping of burned areas are required, yet the exercise is difficult to perform in the field because of time and expense. Now that ready-to-use satellite data are freely accessible in the cloud-based Google Earth Engine (GEE), in this study, we exploit the Sentinel-2-derived differenced normalized burned ratio (dNBR) to characterize burn severity areas, and also track carbon monoxide (CO) plumes using Sentinel-5 following a wildfire that broke over the southeastern coast of the Western Cape province in late October 2018. The results showed that 37.4% of the area was severely burned, and much of it occurred in forested land in the studied area. This was followed by 24.7% of the area that was burned at a moderate-high level. About 15.9% had moderate-low burned severity, whereas 21.9% was slightly burned. Random forests classifier was adopted to separate burned class from unburned and achieved an overall accuracy of over 97%. The most important variables in the classification included texture, NBR, and the NIR bands. The CO signal sharply increased during fire outbreaks and marked the intensity of black carbon over the affected area. Our study contributes to the understanding of forest fire in the dynamics over the Southern Cape forestry landscape. Furthermore, it also demonstrates the usefulness of Sentinel-5 for monitoring CO. Taken together, the Sentinel satellites and GEE offer an effective tool for mapping fires, even in data-poor countries.

scholarly journals AN UNSUPERVISED METHOD BASED ON FIRE INDEX ENHANCEMENT AND GRNN FOR AUTOMATED BURNED AREA MAPPING FROM SINGLE-PERIOD REMOTE SENSING IMAGERY

2021 ◽  
Vol V-3-2021 ◽  
pp. 37-42
Author(s):  
Q. Zhang ◽  
Y. Xiao
Keyword(s):  
Remote Sensing ◽  
Forest Fires ◽  
Current Situation ◽  
General Regression Neural Network ◽  
Burned Area ◽  
Area Index ◽  
Remote Sensing Imagery ◽  
Burned Areas ◽  
Unsupervised Method ◽  
Burned Area Mapping

Abstract. In the current situation of frequent forest fires, the study of forest burned area mapping is important. However, there is still room for improvement in the accuracy of existing forest burning area mapping methods. Therefore, in this paper, an unsupervised method based on fire index enhancement and GRNN (General Regression Neural Network) is proposed for automated forest burned area mapping from single-date post-fire remote sensing imagery. The proposed method first uses adaptive spatial context information to enhance the generated fire index to improve its ability to indicate the burned areas. Then the uncertainty analysis is performed on the enhanced fire index to extract reliable burned samples and non-burned samples for subsequent classifier training. Finally, the improved GRNN model considering the spatial correlation of pixels is used as a classifier to binarize the enhanced fire index to generate the final burned area map. Based on two commonly used fire indexes, NBR (Normalized Burn Ratio) and BAI (Burned Area Index), this paper conducts burned area mapping experiments on a post-fire image of a forest area in Inner Mongolia, China to test the effectiveness of the proposed method, and two commonly used threshold methods (Otsu and Kmeans clustering) are also used to conduct burned area mapping based on threshold segmentation of fire index for comparison experiments. The experimental results prove the effectiveness and superiority of the proposed method. The proposed method is unsupervised and automated, so it has high application value and potential under the current situation of frequent forest fires.

A view of recent forest fire in Australia by satellite derived indices

2021 ◽  
Author(s):  
Kim-Anh Nguyen ◽  
Yuei-An Liou ◽  
Le-Thu Ho
Keyword(s):  
Air Quality ◽  
Optical Sensors ◽  
Forest Fires ◽  
Remote Sensing Data ◽  
Heat Index ◽  
Burned Area ◽  
Landsat 8 ◽  
Burned Areas ◽  
High Severity ◽  
Sentinel 2

<p>Bushfire is one of the dangerous natural manmade hazards. It can cause great damges to the air quality, human health, environment and bio-diversity. In addition, forest fires may be a potential and signigicant source of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans. In early 2020, Australia experienced serious bushfires with over an area of estimated 18.6 million hectares burned, over 5,900 buidlings (including 2, 779 homes) destroyed, and at least 34 people (including three fire fighters) and billion animals and some endangered species killed. Subsequently, air quality was degraded to hazardous levels. It was estimated that about 360 million tonnes of CO<sub>2</sub> was emitted as of 2 Jan. 2020 by NASA. Remote sensing data has been instrumental for the environmental monitoring in particular the bushfire. Many methods and algorithms have been proposed to detect the burned areas in the forest. However, it is challenging or even infeasible to routinely apply them by non-experts due to a chain of sophisticated schemes during their implementation. Here, we present a simple and effective method for mapping a burned area. The performances of different optical sensors and indices are conducted. Sentinel-2 MSI and Landsat 8 data are ultilized for the comparison of burned forest by analyzing different indices (including NDVI, NDBR and newly development index Nomarlized Difference Laten Heat Index (NDLI)). The forest damages are estimated over the Katoombar, Austrialia and the burning severity map is generated and classified into eight levels (none, high regrowth, lowregrowth, unburned, low severity, moderate low severity, moderate high severity, and high severity). The comparision in results from Sentinel-2 MSI data and Landsat image is performed and presented.</p>

scholarly journals Intercomparison of Burned Area Products and Its Implication for Carbon Emission Estimations in the Amazon

2020 ◽  
Vol 12 (23) ◽  
pp. 3864
Author(s):  
Ana Carolina M. Pessôa ◽  
Liana O. Anderson ◽  
Nathália S. Carvalho ◽  
Wesley A. Campanharo ◽  
Celso H. L. Silva Junior ◽  
...  
Keyword(s):  
Land Cover ◽  
Forest Fires ◽  
Carbon Emission ◽  
Regional Scale ◽  
National Level ◽  
Burned Area ◽  
Land Cover Changes ◽  
Burned Areas ◽  
Great Divergence ◽  
Global Emissions

Carbon (C) emissions from forest fires in the Amazon during extreme droughts may correspond to more than half of the global emissions resulting from land cover changes. Despite their relevant contribution, forest fire-related C emissions are not directly accounted for within national-level inventories or carbon budgets. A fundamental condition for quantifying these emissions is to have a reliable estimation of the extent and location of land cover types affected by fires. Here, we evaluated the relative performance of four burned area products (TREES, MCD64A1 c6, GABAM, and Fire_cci v5.0), contrasting their estimates of total burned area, and their influence on the fire-related C emissions in the Amazon biome for the year 2015. In addition, we distinguished the burned areas occurring in forests from non-forest areas. The four products presented great divergence in the total burned area and, consequently, total related C emissions. Globally, the TREES product detected the largest amount of burned area (35,559 km2), and consequently it presented the largest estimate of committed carbon emission (45 Tg), followed by MCD64A1, with only 3% less burned area detected, GABAM (28,193 km2) and Fire_cci (14,924 km2). The use of Fire_cci may result in an underestimation of 29.54 ± 3.36 Tg of C emissions in relation to the TREES product. The same pattern was found for non-forest areas. Considering only forest burned areas, GABAM was the product that detected the largest area (8994 km2), followed by TREES (7985 km2), MCD64A1 (7181 km2) and Fire_cci (1745 km2). Regionally, Fire_cci detected 98% less burned area in Acre state in southwest Amazonia than TREES, and approximately 160 times less burned area in forests than GABAM. Thus, we show that global products used interchangeably on a regional scale could significantly underestimate the impacts caused by fire and, consequently, their related carbon emissions.

scholarly journals A Synergetic Approach to Burned Area Mapping Using Maximum Entropy Modeling Trained with Hyperspectral Data and VIIRS Hotspots

2020 ◽  
Vol 12 (5) ◽  
pp. 858 ◽  
Author(s):  
Alfonso Fernández-Manso ◽  
Carmen Quintano
Keyword(s):  
Maximum Entropy ◽  
Forest Fires ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Infrared Imaging ◽  
Hyperspectral Data ◽  
Burned Area ◽  
Burned Areas ◽  
Mediterranean Countries ◽  
Burned Area Mapping

Southern European countries, particularly Spain, are greatly affected by forest fires each year. Quantification of burned area is essential to assess wildfire consequences (both ecological and socioeconomic) and to support decision making in land management. Our study proposed a new synergetic approach based on hotspots and reflectance data to map burned areas from remote sensing data in Mediterranean countries. It was based on a widely used species distribution modeling algorithm, in particular the Maximum Entropy (MaxEnt) one-class classifier. Additionally, MaxEnt identifies variables with the highest contribution to the final model. MaxEnt was trained with hyperspectral indexes (from Earth-Observing One (EO-1) Hyperion data) and hotspot information (from Visible Infrared Imaging Radiometer Suite Near Real-Time 375 m active fire product). Official fire perimeter measurements by Global Positioning System acted as a ground reference. A highly accurate burned area estimation (overall accuracy = 0.99%) was obtained, and the indexes which most contributed to identifying burned areas included Simple Ratio (SR), Red Edge Normalized Difference Vegetation Index (NDVI750), Normalized Difference Water Index (NDWI), Plant Senescence Reflectance Index (PSRI), and Normalized Burn Ratio (NBR). We concluded that the presented methodology enables accurate burned area mapping in Mediterranean ecosystems and may easily be automated and generalized to other ecosystems and satellite sensors.

scholarly journals USE OF MULTISPECTRAL IMAGING IN THE EVALUATION OF BURNINGS AND FOREST FIRES IN KRAHÔLANDIA INDIGENOUS LAND (2003-2014)

FLORESTA ◽  
2015 ◽  
Vol 45 (4) ◽  
pp. 853
Author(s):  
Lawrence Nóbrega de Oliveira ◽  
Gustavo Maximiano Junqueira Lazzarini ◽  
Antonio Carlos Batista ◽  
Kaio Cesar Cardoso de Lima Fonseca Alves ◽  
Marcos Giongo
Keyword(s):  
Remote Sensing ◽  
Forest Fires ◽  
Multispectral Imaging ◽  
Remote Sensing Data ◽  
Indigenous Communities ◽  
Burned Area ◽  
Land Area ◽  
Burned Areas ◽  
Gis Tools ◽  
Indigenous Land

AbstractHuman actions change the natural occurrences of wildfire. The indigenous communities, during their time of occupation of the Cerrado, probably utilized fire to manipulate the landscape and its resources. In this study, we mapped and analyzed the spatial distribution of burned areas of the Kraholândia Indigenous Land, from 2003 to 2014, using Remote Sensing resources and GIS tools. During the assessed period, the total burned area extended across 1,516,873 ha, representing 4.94 times the sum of Kraholândia Indigenous Land area (306,871 ha). The average annual burned area was 126,406 ha (41.19%), with the year of the largest burned area recorded at 185,297 ha (60.4%) and the year of the smallest burned area was 71,764 ha (23.4%). There were 29,764 ha (9.7%) that had never been burned during the 12 years, and 1,693 ha (0.6%) that had been burned every year of the period. Moreover, the areas that recorded the highest frequency of fire occurrence and burnings were surprisingly not those that produced the largest burned areas over the period. The remote sensing data, allied with methodology employed, succeeded in identifying the frequency of burnings and wildfire in the Krahôlandia Indigenous Land.ResumoUtilização de imagens multispectrais na avaliação das ocorrências de queimadas e incêndios florestais na Terra Indígena Krahôlandia (2003-2014). As ações humanas alteram as ocorrências naturais dos incêndios e queimadas. Os povos indígenas, quando da ocupação do Cerrado, provavelmente usavam o fogo para manipular a paisagem e os seus recursos em várias épocas do ano. Este trabalho teve por objetivo analisar e mapear a distribuição espacial de áreas queimadas na Terra Indígena Krahôlandia, no período de 2003 a 2014, utilizando ferramentas de sensoriamento remoto e SIG. Nos 12 anos avaliados, a área queimada total foi de 1.516.872,51 ha, que representa 4,94 vezes a área total da TI Krahôlandia (306.871,02 ha). A média anual de área queimada foi de 126.406,04 ha (41,19%) com o ano da maior área queimada com 185,297 ha (60,4%) e o ano da área menor com 71,764 ha (23,4%). Houve 29.764 ha (9,7%) que nunca tinham sido queimadas durante os 12 anos, e 1.693 ha (0,6%) que tinham sido queimados todos os doze anos. Além disso, as áreas que registraram a maior frequência de ocorrência de incêndios e queimadas não foram surpreendentemente aquelas que produziram as maiores áreas queimadas ao longo do período. Os dados de sensoriamento remoto aliados com metodologia empregada conseguiu identificar a frequência de ocorrência de queimadas e incêndios florestais na terra indígena Krahôlandia.Palavras-chave: Cerrado; recorrência de fogo.

scholarly journals Mapping Forest Fire Risk at a Local Scale—A Case Study in Andalusia (Spain)

Environments ◽  
2019 ◽  
Vol 6 (3) ◽  
pp. 30 ◽  
Author(s):  
Ismael Vallejo-Villalta ◽  
Estefanía Rodríguez-Navas ◽  
Joaquín Márquez-Pérez
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Fire Risk ◽  
Moisture Stress ◽  
Forest Environment ◽  
Protection Measures ◽  
Burned Areas ◽  
Fuel Models ◽  
Forest Fire Risk

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.

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