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.

The 2019/20 eastern Australian mega forest fires - a global forest perspective

2020 ◽  
Author(s):  
Matthias Boer ◽  
Víctor Resco De Dios ◽  
Ross Bradstock
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Austral Summer ◽  
Fire Regimes ◽  
Burned Area ◽  
Fire Event ◽  
Data Set ◽  
Broadleaf Forest ◽  
Eastern Australia ◽  
Fire Activity

<p>The 2019/20 forest fires in eastern Australia burned over 5.8 million hectares of mainly temperate broadleaf forest between September 2019 and January 2020. This burned area figure is expected to rise over the remainder of the austral summer, but is already an order of magnitude larger than the mean annual burned area for Australian forest fires over the last 20 years, which is ~0.59 Mha per year. Here we show that this forest fire event is of a record-breaking scale, both nationally and globally, and was pre-conditioned by wide-spread prolonged drought and extreme heat.</p><p>We analysed global remotely sensed burned area data for 2000-2019 to estimate annual burned area fractions of all continental forest biomes. The annual burned area fraction, which is related to the length of fire intervals and other aspects of fire regimes, allows us to compare levels of fire activity across different forest biomes and continents.</p><p>Though very large fires occur in some forest biomes, such as the boreal forests of North-America and Asia, over the 20 years covered by our data set, annual burned area fractions have been very small (<0.03) for nearly all continental forest biomes including Australia’s temperate broadleaf forest biome. These findings provide a global historical reference for the interpretation of the scale of the 2019/20 eastern Australian mega forest fires.</p><p>With fire activity in all forest biomes strongly constrained by the moisture content of the fuels, explanations for the unconstrained burning of millions of hectares of temperate broadleaf forest in a single season must be sought in the extreme drought that has affected eastern Australia for the last two years. We use gridded daily soil moisture predictions for the continent to show how widespread and prolonged dryness set the stage for the unprecedented forest fire event of 2019/20.</p>

scholarly journals REMOTE SENSING & GIS INTEGRATION FOR MONITORING THE AREAS AFFECTED BY FOREST FIRES: A CASE STUDY IN IZMIR, TURKEY

2018 ◽  
Vol XLII-3/W4 ◽  
pp. 165-170 ◽  
Author(s):  
E. Çolak ◽  
A. F. Sunar
Keyword(s):  
Remote Sensing ◽  
Forest Fire ◽  
Forest Fires ◽  
Landsat 8 ◽  
Area Index ◽  
Burned Areas ◽  
Digital Elevation ◽  
Elevation Model ◽  
Normalized Burn Ratio ◽  
Sentinel 2

<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>

scholarly journals Multitemporal Mapping of Post-Fire Land Cover Using Multiplatform PRISMA Hyperspectral and Sentinel-UAV Multispectral Data: Insights from Case Studies in Portugal and Italy

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 3982
Author(s):  
Giacomo Lazzeri ◽  
William Frodella ◽  
Guglielmo Rossi ◽  
Sandro Moretti
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Fire Severity ◽  
Experimental Methodology ◽  
Vegetation Recovery ◽  
Burned Area ◽  
Remotely Sensed Data ◽  
The Impact ◽  
Sentinel 2

Wildfires have affected global forests and the Mediterranean area with increasing recurrency and intensity in the last years, with climate change resulting in reduced precipitations and higher temperatures. To assess the impact of wildfires on the environment, burned area mapping has become progressively more relevant. Initially carried out via field sketches, the advent of satellite remote sensing opened new possibilities, reducing the cost uncertainty and safety of the previous techniques. In the present study an experimental methodology was adopted to test the potential of advanced remote sensing techniques such as multispectral Sentinel-2, PRISMA hyperspectral satellite, and UAV (unmanned aerial vehicle) remotely-sensed data for the multitemporal mapping of burned areas by soil–vegetation recovery analysis in two test sites in Portugal and Italy. In case study one, innovative multiplatform data classification was performed with the correlation between Sentinel-2 RBR (relativized burn ratio) fire severity classes and the scene hyperspectral signature, performed with a pixel-by-pixel comparison leading to a converging classification. In the adopted methodology, RBR burned area analysis and vegetation recovery was tested for accordance with biophysical vegetation parameters (LAI, fCover, and fAPAR). In case study two, a UAV-sensed NDVI index was adopted for high-resolution mapping data collection. At a large scale, the Sentinel-2 RBR index proved to be efficient for burned area analysis, from both fire severity and vegetation recovery phenomena perspectives. Despite the elapsed time between the event and the acquisition, PRISMA hyperspectral converging classification based on Sentinel-2 was able to detect and discriminate different spectral signatures corresponding to different fire severity classes. At a slope scale, the UAV platform proved to be an effective tool for mapping and characterizing the burned area, giving clear advantage with respect to filed GPS mapping. Results highlighted that UAV platforms, if equipped with a hyperspectral sensor and used in a synergistic approach with PRISMA, would create a useful tool for satellite acquired data scene classification, allowing for the acquisition of a ground truth.

scholarly journals SPECTRAL ANALYSIS OF THE HIMAWARI-8 DATA FOR HOTSPOT DETECTION FROM LAND/FOREST FIRES IN SUMATRA

2018 ◽  
Vol 15 (1) ◽  
pp. 15
Author(s):  
Hana Listi Fitriana ◽  
Sayidah Sulma ◽  
NFN Suwarsono ◽  
Any Zubaidah ◽  
Indah Prasasti
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Accuracy Assessment ◽  
Training Sample ◽  
Acquisition Time ◽  
Landsat 8 ◽  
Main Process ◽  
Hotspot Detection ◽  
Sample Collection ◽  
Fire Event

Himawari-8 is the last generation of the low spatial resolution satellite imagery that has capability to detect the thermal variation on the earth of every 10 minute. This must be very potential to be used for detecting land/forest fire. This paper has explored the spectral prospective of the Himawari-8 for detecting land/forest fire hotspot. The main objective for this study is to identify the potential use of Himawari-8 for detecting of land forest fire hotspot. The study area was performed in Ogan Komering Ilir, South of Sumatra, which on 2015 occur great forest/land fire event. The main process included in this study are image projection, training sample collection and spectral statistical analysis measured by calculate statistic, they are average values, standard deviation values from reflectance visible band value and brightness temperature value, beside that validation of data obtained from medium resolution data of Landsat 8 with the similar acquisition time. The study found that the Himawari-8 has good capacity to identify land/forest fire hotspot as expressed for high accuracy assessment using band 3 and band 7.

scholarly journals Comparison of Methods for the Assessment of Fire Danger in the Czech Republic

2019 ◽  
Vol 67 (5) ◽  
pp. 1285-1295 ◽  
Author(s):  
František Jurečka ◽  
Martin Možný ◽  
Jan Balek ◽  
Zdeněk Žalud ◽  
Miroslav Trnka
Keyword(s):  
Czech Republic ◽  
Forest Fire ◽  
Forest Fires ◽  
Fire Danger ◽  
Special Focus ◽  
Fire Weather ◽  
Fire Event ◽  
Fire Weather Index ◽  
The Czech Republic ◽  
Fire Danger Indices

The performance of fire indices based on weather variables was analyzed with a special focus on the Czech Republic. Three fire weather danger indices that are the basis of fire danger rating systems used in different parts of the world were assessed: the Canadian Fire Weather Index (FWI), Australian Forest Fire Danger Index (FFDI) and Finnish Forest Fire Index (FFI). The performance of the three fire danger indices was investigated at different scales and compared with actual fire events. First, the fire danger indices were analyzed for different land use types during the period 1956–2015. In addition, in the analysis, the three fire danger indices were compared with wildfire events during the period 2001–2015. The fire danger indices were also analyzed for the specific locality of the Bzenec area where a large forest fire event occurred in May 2012. The study also focused on the relationship between fire danger indices and forest fires during 2018 across the area of the Jihomoravský region. Comparison of the index values with real fires showed that the index values corresponded well with the occurrence of forest fires. The analysis of the year 2018 showed that the highest index values were reached on days with the greater fire occurrence. On days with 5 or 7 reported fires per day, the fire danger indices reached values between 3 and 4.

Integration of AWiFS and MODIS active fire data for burn mapping at regional level using the Burned Area Synergic Algorithm (BASA)

2009 ◽  
Vol 18 (4) ◽  
pp. 404 ◽  
Author(s):  
Federico González-Alonso ◽  
Silvia Merino-de-Miguel
Keyword(s):  
Forest Fires ◽  
Burned Area ◽  
Wide Field ◽  
Imaging Spectrometer ◽  
Area Index ◽  
North West ◽  
Active Fire ◽  
Moderate Resolution ◽  
Field Sensor ◽  
Speed Accuracy

The present paper presents an algorithm that synergistically combines data from four different parts of the spectrum (near-, shortwave, middle- and thermal infrared) to produce a reliable burned-area map. It is based on the use of a modified version of the BAIM (MODIS – Moderate Resolution Imaging Spectrometer – Burned Area Index) together with active fire information. The following study focusses in particular on an image from the AWiFS (Advanced Wide Field Sensor) sensor dated 21 August 2006 and MODIS active fires detected during the first 20 days of August as well as ancillary maps and information. The methodology was tested in Galicia (north-west Spain) where hundreds of forest fires occurred during the first 20 days of August 2006. Burned area data collected from the present work was compared with official fire statistics from both the Spanish Ministry of the Environment and the Galician Forestry Service. The speed, accuracy and cost-effectiveness of this method suggest that it would be of great interest for use at both regional and national levels.

scholarly journals Mathematical Modeling of Heat Transfer in an Element of Combustible Plant Material When Exposed to Radiation from a Forest Fire

Safety ◽  
2019 ◽  
Vol 5 (3) ◽  
pp. 56 ◽  
Author(s):  
Nikolay Baranovskiy ◽  
Alena Demikhova
Keyword(s):  
Heat Transfer ◽  
Forest Fire ◽  
Forest Fires ◽  
Plant Material ◽  
Mathematical Physics ◽  
Burned Area ◽  
Herbaceous Plant ◽  
One Dimensional ◽  
Impact Prediction ◽  
The Impact

The last few decades have been characterized by an increase in the frequency and burned area of forest fires in many countries of the world. Needles, foliage, branches, and herbaceous plants are involved in burning during forest fires. Most forest fires are surface ones. The purpose of this study was to develop a mathematical model of heat transfer in an element of combustible plant material, namely, in the stem of a herbaceous plant, when exposed to radiation from a surface forest fire. Mathematically, the process of heat transfer in an element of combustible plant material was described by a system of non-stationary partial differential equations with corresponding initial and boundary conditions. The finite difference method was used to solve this system of equations in combination with a locally one-dimensional method for solving multidimensional tasks of mathematical physics. Temperature distributions were obtained as a result of modeling in a structurally inhomogeneous stem of a herbaceous plant for various scenarios of the impact of a forest fire. The results can be used to develop new systems for forest fire forecasting and their environmental impact prediction.

scholarly journals Event-Based Integrated Assessment of Environmental Variables and Wildfire Severity through Sentinel-2 Data

Forests ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 1021 ◽  
Author(s):  
Juan Picos ◽  
Laura Alonso ◽  
Guillermo Bastos ◽  
Julia Armesto
Keyword(s):  
Land Cover ◽  
Forest Fires ◽  
Fire Suppression ◽  
Fire Severity ◽  
Environmental Parameters ◽  
Weather Conditions ◽  
Integrated Approach ◽  
Policy Makers ◽  
Event Based ◽  
Sentinel 2

To optimize suppression, restoration, and prevention plans against wildfire, postfire assessment is a key input. Since little research has been carried out on applying Sentinel-2 imagery through an integrated approach to evaluate how environmental parameters affect fire severity, this work aims to fill this gap. A set of large forest fires that occurred in northwest Spain during extreme weather conditions were adopted as a case study. Sentinel-2 information was used to build the fire severity map and to evaluate the relation between it and a set of its driving factors: land cover, aspect, slope, proximity to the nearest stream, and fire recurrence. The cover types most affected by fire were scrubland, rocky areas, and Eucalyptus. The presence of streams was identified as a major cause of the reduced severity of fires in broadleaves. The occurrence of fires in the past is linked to the severity of fires, depending on the land cover. This research aims to help fire researchers, authority managers, and policy makers distinguish the conditions under which the damage by fire is minimized and optimize the resources allocated to restoration and future fire suppression.

The spatio-temporal characteristics of forest fires in China: observations from hybrid remote sensing data

2020 ◽  
Author(s):  
Lei Fang ◽  
Zeyu Qiao ◽  
Jian Yang
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
High Frequency ◽  
Fire Management ◽  
Hot Spot ◽  
Landsat Imagery ◽  
Low Frequency ◽  
Burned Area ◽  
Prevention Policy ◽  
The Past

&lt;p&gt;Forest fire is a natural disaster threatening global human well-beings as well as a crucial disturbance agent driving forest landscape changes. The remotely sensed burned area (BA) products can provide spatially and temporally continuous monitoring of global fires, but the accuracies remain to be improved. We firstly developed a hybrid burned area mapping approach, which integrated the advantages of a 250 m global BA product (CCI_Fire) and a 30 m global forest change (GFC) product, to generate an improved 250 m BA product (so-called CCI_GFC product). Based on 248 fire patches derived from Landsat imagery, the results showed that the CCI_GFC product improved the CCI_Fire product substantially, which are significantly better than MCD64A1 product. According to the CCI_GFC, we found the total BA in the past 17 years was about 12.1 million ha in China, which approximately covered 6.1% of the total forested areas with a significantly decreased trend through Mann-Kendall test (Tau= -0.47, P&lt;0.05) . We conducted a grid analysis (0.05&amp;#176;&amp;#215;0.05&amp;#176;) to determine the hot spots of forest fire from 2001 to 2017. We also quantified fire characteristics on frequency, spatial distribution, and seasonality in terms of Burned Forest Rate (BFR), hot spot areas, and fire seasons, respectively. We found that low frequency burns with a 0&lt;BFR&amp;#8804;20% in 17 years covered 64% of total grids; the medium-low frequency burns (20%&lt;BFR&amp;#8804;40%), the medium frequency burns (40%&lt;BFR&amp;#8804;60%), the medium-high frequency burns (60%&lt; BFR&amp;#8804;80%) accounted for 15%, 7%, 4% respectively; the high frequency burns (80%&lt;BFR&amp;#8804;100%) and extremely high burns (100%&lt;BFR&amp;#8804;120%) together occupy 10% of total grids which mainly distributed in Xiao Hinggan mountains, south China, and southwest China. The seasonality of forest fires differed substantially among eco-regions. The fire seasons of two temperate forest eco-regions are spring and autumn. The two peak fire months are May and October, in which about 22% and 37% of the total burned area were founded respectively. As a comparison, fire seasons in tropical and subtropical eco-regions are spring and winter (i.e., November to March of the next year), which accounted 88% of the total burned area. Our study clearly illustrated the characteristics of forest fire patterns in the past 17 years, which highlighted the remarkable achievements due to a nationwide implementation of fire prevention policy. At the same time, we emphasized that it is critically important to regard the long-term forest fire dynamics to design scientific and reasonable strategies or methods for fire management and controlling, which will be of sound significance to optimize the allocation of financial resources on fire management, and to achieve sustainable management of forests.&lt;/p&gt;

scholarly journals Forest Fire Area Detection by Using Landsat-8 and Sentinel-2 Satellite Images: A Case Study in Mugla, Turkey

2020 ◽  
Author(s):  
Bahadir Kurnaz ◽  
Caglar Bayik ◽  
Saygin Abdikan
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Satellite Images ◽  
Near Infrared ◽  
Kappa Statistics ◽  
Landsat 8 ◽  
Important Place ◽  
Burn Scar ◽  
Object Based ◽  
Sentinel 2

Abstract Background: Forests have an extremely important place in the ecosystem in terms of ensuring social and environmental balance. The biggest danger for forests that have this importance is forest fires due to various reasons. It is extremely important to estimate the formation and behavior characteristics of fires in terms of combating forest fires. Using the satellite images obtained with the developing technology for this purpose provides great convenience in the detection of the fire areas and the severity of the fire affected. In this study, forest fire that occurred in the Zeytinköy region of Muğla province was investigated using remotely sensed images. According to the reference data provided by the General Directorate of Forestry (GDF), 425 hectares of area was destroyed by fire. In this study, it is aimed to extract burn scar by applying seven vegetation indexes on Sentinel-2 and Landsat-8 satellite images. Additionally, forest fire areas have been determined with the object-based classification technique. Results: As a result of the study, when the obtained results are compared with the values obtained from GDF, it is determined that object based analysis of Sentinel-2 provided the highest accuracy with 98.36% overall accuracy and 0.976 kappa statistics. Comparing the results of spectral indices of Sentinel-2 and Landsat-8, Sentinel-2 resulted better results in all indices. Among the indices RdNBR and dNDVI obtained better results than other indices with Sentinel-2 and Landsat-8, respectively. Conclusions: In general, it has been determined that Sentinel-2 data is more suitable than Landsat-8 satellite images for determining Turkish red pine forest fired areas. Red and near infrared based images can be used for rapid mapping of fired areas. The results also indicated that the indices provided by multi-temporal Sentinel-2 data can assist forest management for rapid monitoring of fire scars and also for evolution of reforestation after fire.

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