Mapping of vegetation cover using Sentinel-2 to estimate forest fire danger

2019 ◽  
Author(s):  
Elena P. Yankovich ◽  
Ksenia S. Yankovich ◽  
Nikolay V. Baranovskiy ◽  
Alexander Bazarov ◽  
Roman Sychev ◽  
...  
Keyword(s):  
Forest Fire ◽  
Vegetation Cover ◽  
Fire Danger ◽  
Forest Fire Danger ◽  
Sentinel 2

Classification of Territory on Forest Fire Danger Level Using GIS and Remote Sensing

2020 ◽  
pp. 258-267 ◽  
Author(s):  
Elena Petrovna Yankovich ◽  
Ksenia S. Yankovich
Keyword(s):  
Remote Sensing ◽  
Forest Fire ◽  
Forest Fires ◽  
Vegetation Cover ◽  
Remote Sensing Data ◽  
Fire Danger ◽  
Gis And Remote Sensing ◽  
Forest Fuels ◽  
Forest Fire Danger

The vegetation cover is the most important factor in forest fires, because it reflects the presence of forest fuels. The study of the variability of the vegetation cover, as well as observation of its condition, allows estimating the level of fire danger of the forest quarter. The work presents a geo-information system containing a set of tools to determine the level of fire danger of the forest quarter. The system is able to predict (determine the probability) and classify forest quarters according to the level of fire danger. The assessment of forest fire danger of Tomsk forestry of Tomsk region has been carried out. Fire probability maps of forest quarters were created based on remote sensing data and ArcGIS software.

scholarly journals Classification of Vegetation to Estimate Forest Fire Danger Using Landsat 8 Images: Case Study

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Ksenia S. Yankovich ◽  
Elena P. Yankovich ◽  
Nikolay V. Baranovskiy
Keyword(s):  
Lake Baikal ◽  
Forest Fire ◽  
Vegetation Cover ◽  
Spectral Characteristics ◽  
Forest Vegetation ◽  
Fire Danger ◽  
Landsat 8 ◽  
Agricultural Crop ◽  
Forest Fire Danger

The vegetation cover of the Earth plays an important role in the life of mankind, whether it is natural forest or agricultural crop. The study of the variability of the vegetation cover, as well as observation of its condition, allows timely actions to make a forecast and monitor and estimate the forest fire condition. The objectives of the research were (i) to process the satellite image of the Gilbirinskiy forestry located in the basin of Lake Baikal; (ii) to select homogeneous areas of forest vegetation on the basis of their spectral characteristics; (iii) to estimate the level of forest fire danger of the area by vegetation types. The paper presents an approach for estimation of forest fire danger depending on vegetation type and radiant heat flux influence using geographic information systems (GIS) and remote sensing data. The Environment for Visualizing Images (ENVI) and the Geographic Resources Analysis Support System (GRASS) software were used to process satellite images. The area’s forest fire danger estimation and visual presentation of the results were carried out in ArcGIS Desktop software. Information on the vegetation was obtained using the analysis of the Landsat 8 Operational Land Imager (OLI) images for a typical forestry of the Lake Baikal natural area. The maps (schemes) of the Gilbirinskiy forestry were also used in the present article. The unsupervised k-means classification was used. Principal component analysis (PCA) was applied to increase the accuracy of decoding. The classification of forest areas according to the level of fire danger caused by the typical ignition source was carried out using the developed method. The final information product was the map displaying vector polygonal feature class, containing the type of vegetation and the level of fire danger for each forest quarter in the attribute table. The fire danger estimation method developed by the authors was applied to each separate quarter and showed realistic results. The method used may be applicable for other areas with prevailing forest vegetation.

scholarly journals Forest fire danger rating in complex topography – results from a case study in the Bavarian Alps in autumn 2011

2013 ◽  
Vol 13 (9) ◽  
pp. 2157-2167 ◽  
Author(s):  
C. Schunk ◽  
C. Wastl ◽  
M. Leuchner ◽  
C. Schuster ◽  
A. Menzel
Keyword(s):  
Forest Fire ◽  
Temperature Inversion ◽  
Fire Danger ◽  
Complex Topography ◽  
Pressure System ◽  
Drought Period ◽  
Bavarian Alps ◽  
Forest Fire Danger ◽  
Fire Danger Indices

Abstract. Forest fire danger rating based on sparse meteorological stations is known to be potentially misleading when assigned to larger areas of complex topography. This case study examines several fire danger indices based on data from two meteorological stations at different elevations during a major drought period. This drought was caused by a persistent high pressure system, inducing a pronounced temperature inversion and its associated thermal belt with much warmer, dryer conditions in intermediate elevations. Thus, a massive drying of fuels, leading to higher fire danger levels, and multiple fire occurrences at mid-slope positions were contrasted by moderate fire danger especially in the valleys. The ability of fire danger indices to resolve this situation was studied based on a comparison with the actual fire danger as determined from expert observations, fire occurrences and fuel moisture measurements. The results revealed that, during temperature inversion, differences in daily cycles of meteorological parameters influence fire danger and that these are not resolved by standard meteorological stations and fire danger indices (calculated on a once-a-day basis). Additional stations in higher locations or high-resolution meteorological models combined with fire danger indices accepting at least hourly input data may allow reasonable fire danger calculations under these circumstances.

scholarly journals Temporal variations and change in forest fire danger in Europe for 1960–2012

2014 ◽  
Vol 14 (6) ◽  
pp. 1477-1490 ◽  
Author(s):  
A. Venäläinen ◽  
N. Korhonen ◽  
O. Hyvärinen ◽  
N. Koutsias ◽  
F. Xystrakis ◽  
...  
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
National Level ◽  
Temporal Variations ◽  
Fire Danger ◽  
Fire Season ◽  
Fire Weather ◽  
Fire Weather Index ◽  
Current Season ◽  
Forest Fire Danger

Abstract. Understanding how fire weather danger indices changed in the past and how such changes affected forest fire activity is important in a changing climate. We used the Canadian Fire Weather Index (FWI), calculated from two reanalysis data sets, ERA-40 and ERA Interim, to examine the temporal variation of forest fire danger in Europe in 1960–2012. Additionally, we used national forest fire statistics from Greece, Spain and Finland to examine the relationship between fire danger and fires. There is no obvious trend in fire danger for the time period covered by ERA-40 (1960–1999), whereas for the period 1980–2012 covered by ERA Interim, the mean FWI shows an increasing trend for southern and eastern Europe which is significant at the 99% confidence level. The cross correlations calculated at the national level in Greece, Spain and Finland between total area burned and mean FWI of the current season is of the order of 0.6, demonstrating the extent to which the current fire-season weather can explain forest fires. To summarize, fire risk is multifaceted, and while climate is a major determinant, other factors can contribute to it, either positively or negatively.

scholarly journals Long-term temporal changes in the occurrence of a high forest fire danger in Finland

2012 ◽  
Vol 12 (8) ◽  
pp. 2591-2601 ◽  
Author(s):  
H. M. Mäkelä ◽  
M. Laapas ◽  
A. Venäläinen
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Large Scale ◽  
Weather Conditions ◽  
Temporal Variations ◽  
Fire Danger ◽  
Specific Information ◽  
Climate Data ◽  
Forest Fire Danger

Abstract. Climate variation and change influence several ecosystem components including forest fires. To examine long-term temporal variations of forest fire danger, a fire danger day (FDD) model was developed. Using mean temperature and total precipitation of the Finnish wildfire season (June–August), the model describes the climatological preconditions of fire occurrence and gives the number of fire danger days during the same time period. The performance of the model varied between different regions in Finland being best in south and west. In the study period 1908–2011, the year-to-year variation of FDD was large and no significant increasing or decreasing tendencies could be found. Negative slopes of linear regression lines for FDD could be explained by the simultaneous, mostly not significant increases in precipitation. Years with the largest wildfires did not stand out from the FDD time series. This indicates that intra-seasonal variations of FDD enable occurrence of large-scale fires, despite the whole season's fire danger is on an average level. Based on available monthly climate data, it is possible to estimate the general fire conditions of a summer. However, more detailed input data about weather conditions, land use, prevailing forestry conventions and socio-economical factors would be needed to gain more specific information about a season's fire risk.

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