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Αξιοποίηση δορυφορικών δεδομένων & λογισμικών ανοικτού κώδικα για την προσομοίωση της χωρικής εξάπλωσης δασικής πυρκαγιάς - Utilizing satellite imagery and open-source software for wildfire spread prediction in Greece (In Greek with English abstract)

  • October 2021
  • Conference: 20ο Πανελλήνιο Δασολογικό Συνέδριο
  • At: Trikala, Thessaly
Authors:
Fotis Bouras at University of Patras
Fotis Bouras
Miltiadis Athanasiou at Hellenic Agricultural Organization - Demeter
Miltiadis Athanasiou
Andreas Langousis at University of Patras
Andreas Langousis
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Abstract and Figures

Η χωρική εξάπλωση δασικής πυρκαγιάς στην ημιορεινή Αρκαδία στις 11 Σεπτεμβρίου 2017, προσομοιώθηκε μέσω του συστήματος FARSITE 4. Για την περιγραφή της τοπογραφίας της περιοχής, μεταφορτώθηκε ψηφιακό μοντέλο εδάφους (Aster GDEM) και εισήχθη στο Quantum GIS. Για την χαρτογράφηση της καύσιμης ύλης, δορυφορικές εικόνες Landsat 8 OLI ταξινομήθηκαν με την μέθοδο της αντικειμενοστραφούς ανάλυσης και χρησιμοποιήθηκαν μετεωρολογικά δεδομένα από τον κοντινό μετεωρολογικό σταθμό της Μεγαλόπολης του Εθνικού Αστεροσκοπείου Αθηνών. Με βάση τα τελευταία, δοκιμάστηκαν μικρές παραλλαγές στις διευθύνσεις και τις τιμές της ταχύτητας του ανέμου, για την λεπτομερή περιγραφή των μετεωρολογικών συνθηκών που επικρατούσαν στην περιοχή κατά την εξάπλωση της δασικής πυρκαγιάς και δημιουργήθηκαν έξι διαφορετικά σενάρια,. Για κάθε σενάριο, εκτιμήθηκαν α) οι θέσεις της περιμέτρου της δασικής πυρκαγιάς σε δεδομένες χρονικές στιγμές, β) ο ρυθμός εξάπλωσης (ROS, m/min), γ) η έντασή της (Ι, kW/m), δ) ο στατιστικός δείκτης συσχέτισης Sorensen- Dice (SD) και ε) ο ποσοστιαίος δείκτης απόκλισης της εκτιμώμενης καμένης έκτασης από την πραγματική. Τα αποτελέσματα των προσομοιώσεων συζητήθηκαν και επισημάνθηκαν πιθανοί τρόποι αξιοποίησής τους κατά τη διαχείριση των δασικών πυρκαγιών. FARSITE (now included in FlamMap6) was used to simulate the spread and behavior of a wildfire that had been documented in Arcadia, Greece, in 2017. A Digital Elevation Model (Aster GDEM), available at no cost from a remote sensing instrument operating aboard NASA's Terra satellite [Japan's Ministry of Economy, Trade and Industry (METI) radiometer], was downloaded from https://asterweb.jpl.nasa.gov /gdem.asp and processed using Quantum GIS (http://www.qgis.org). Satellite images Landsat 8 OLI were classified by an object-oriented analysis method, supporting fuel mapping, and data from an adjacent meteorological station of National Observatory of Athens allowed a detailed description of the wind field. Fire spread simulations were run for six discrete wind field scenarios, and the obtained results are presented along with a thorough discussion of strengths, potential benefits as well as weaknesses of the applied method.
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ISBN: 978-618-84551-2-2
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andlag@upatras.gr
2Wildfire Management Consulting and Training, 8, 13673 , info@m-
athanasiou.gr
FARSITE 4.
AsterG QuantumGIS.
,
kW
Sorensen- Dice (
FARSITE.
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-
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c
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Albini
(1976), Anderson
Prabhakara
Farsite
FARSITE
Quantum GIS QGIS
GRASS
Aster GDEM
(Advanced
-
(https://asterweb.jpl.nasa.gov/gdem.asp).
QGiS
Earthexplorer (https://earthexplorer.usgs.gov/).
km
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(T) = 34 =
cm -hr
10-
hr ( cm)
-hr (
-
Table 1. Description of the six discrete scenarios used for the wildfire spread simulations. “m.s.M.” is for Megalopolis
meteorological station original recorded data.
1 2 3 4 5 6
“Acceleration”
(wind speed)
[Beaufort (km·h-1)] (m.s.M.)
4
(24) (m.s.M.) 4 (24) 5 (34)
(wind direction) (m.s.M.)
180°(14:00-16:30)
225°(16:30-22:00)
180°(14:00-16:30)
225°(16:30-22:00)
180°(14:00-16:30)
210°(16:30-21:00)
225°(21:00-22:00)
x = 340706, y
vector
h min
2
Sorensen-
=(1)
a b
c
= (2)
kW
SD
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. Sorensen – Dice (SD)
Table 2. Relative change and Sorensen – Dice (SD) coefficient for the six scenarios.
1
2
3
4
5
[km2(ha)]
2,83
(283)
1,83
(183)
1,20
(120)
1,02
(102)
1,50
(150)
1,27
(127)
1,87
(187)
-
35,38
-
57,49
-
63,86
-
47,12
-
55,07
33,92
0,19 0,16 0,13 0,21 0,28 0,53
Table 3. Wildfire behaviour prediction for the six scenarios. In the second column, estimated perimeter at 15:00 (white),
17:00 (yellow) and 20:00 (red).
(Scenario)
6,
The orange polygon at scenario 6,
represents the actual burned area
(m/min)
Rate of spread (m/min)
(kW/m)
Fireline Intensity (kW/m)
1
2
3
4
5
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-1.
,
1. H
[ , (source):
https://www.you tube.com /watch? v=RWWk209 pjMI& fbclid=
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WfT6dVZ hkZtqU ovOx0E]
Figure 1. The wildfire spreads through Mediterranean shrublands
2. ,
[
, (source):
https://www.you tube.com /watch? v=RWWk209
pjMI& fbclid= IwAR0_maSU UQg 5wp1e XVR
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ovOx0E]
Figure 2. Dozers were used for Fireline
construction
2
187 ha
SD.
SD
ROS
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ROS I
3.
(Papadopoulos and Pavlidou 2011).
Figure 3. Profile along the main axis of the head fire spread. A: eruption point, B & : significant change of head spread
direction, : end of profile
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FlamMap
Kalabokidis
Abstract
FARSITE (now included in FlamMap6) was used to simulate the spread and behavior of a wildfire that
had been documented in Arcadia, Greece, in 2017. A Digital Elevation Model (Aster GDEM), available
at no cost from a remote sensing instrument operating aboard NASA's Terra satellite [Japan's Ministry
of Economy, Trade and Industry (METI) radiometer], was downloaded from
https://asterweb.jpl.nasa.gov /gdem.asp and processed using Quantum GIS (http://www.qgis.org).
Satellite images Landsat 8 OLI were classified by an object-oriented analysis method, supporting fuel
mapping, and data from an adjacent meteorological station of National Observatory of Athens allowed
a detailed description of the wind field. Fire spread simulations were run for six discrete wind field
scenarios, and the obtained results are presented along with a thorough discussion of strengths, potential
benefits as well as weaknesses of the applied method.
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Evaluating the relationship between biomass, percent groundcover and remote sensing indices across six winter cover crop fields in Maryland, United States
Article
Full-text available
Winter cover crops are an essential part of managing nutrient and sediment losses from agricultural lands. Cover crops lessen sedimentation by reducing erosion, and the accumulation of nitrogen in aboveground biomass results in reduced nutrient runoff. Winter cover crops are planted in the fall and are usually terminated in early spring, making them susceptible to senescence, frost burn, and leaf yellowing due to wintertime conditions. This study sought to determine to what extent remote sensing indices are capable of accurately estimating the percent groundcover and biomass of winter cover crops, and to analyze under what critical ranges these relationships are strong and under which conditions they break down. Cover crop growth on six fields planted to barley, rye, ryegrass, triticale or wheat was measured over the 2012–2013 winter growing season. Data collection included spectral reflectance measurements, aboveground biomass, and percent groundcover. Ten vegetation indices were evaluated using surface reflectance data from a 16-band CROPSCAN sensor. Restricting analysis to sampling dates before the onset of prolonged freezing temperatures and leaf yellowing resulted in increased estimation accuracy. There was a strong relationship between the normalized difference vegetation index (NDVI) and percent groundcover (r2 = 0.93) suggesting that date restrictions effectively eliminate yellowing vegetation from analysis. The triangular vegetation index (TVI) was most accurate in estimating high ranges of biomass (r2 = 0.86), while NDVI did not experience a clustering of values in the low and medium biomass ranges but saturated in the higher range (>1500 kg/ha). The results of this study show that accounting for index saturation, senescence, and frost burn on leaves can greatly increase the accuracy of estimates of percent groundcover and biomass for winter cover crops.
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Fire Behavior Simulation in Mediterranean Forests Using the Minimum Travel Time Algorithm
Conference Paper
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  • Jul 2013
Recent large wildfires in Greece exemplify the need for pre-fire burn probability assessment and possible landscape fire flow estimation to enhance fire planning and resource allocation. The Minimum Travel Time (MTT) algorithm, incorporated as FlamMap’s version five module, provide valuable fire behavior functions, while enabling multi-core utilization for the calculations. The primary goal of this study was the MTT implementation for two study areas in Mediterranean forest types of Greece, i.e. Lesvos Island (in North Aegean Sea) and Messenia (in Southwestern Peloponnesus) by calculating burn probabilities, fire size and flame length probability from thousands of simulated fire events (located either randomly or based on historical ignitions). A second goal aimed on estimating fire hazard and vulnerability for several values-at-risk of the study areas. To achieve these goals the necessary geospatial datasets were created by field inventories, remote sensing techniques, geo-statistics and Geographic Information Systems (GIS). Weather and fuel moisture inputs were retrieved from nearby weather stations. Maps showing the most fire-prone and high-risk parts of each area were created, along with fire hazard scatter plots for values-at-risk. Interpretation of the results may suggest possible fire fighting strategies, places that need vegetation management, areas that require more patrols and surveillance and areas with increased fire intensity.
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Wildland surface fire spread modelling, 1990–2007. 3: Simulation and mathematical analogue models
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  • Jul 2009
In recent years, advances in computational power and spatial data analysis (GIS, remote sensing, etc) have led to an increase in attempts to model the spread and behvaiour of wildland fires across the landscape. This series of review papers endeavours to critically and comprehensively review all types of surface fire spread models developed since 1990. This paper reviews models of a simulation or mathematical analogue nature. Most simulation models are implementations of existing empirical or quasi-empirical models and their primary function is to convert these generally one dimensional models to two dimensions and then propagate a fire perimeter across a modelled landscape. Mathematical analogue models are those that are based on some mathematical conceit (rather than a physical representation of fire spread) that coincidentally simulates the spread of fire. Other papers in the series review models of an physical or quasi-physical nature and empirical or quasi-empirical nature. Many models are extensions or refinements of models developed before 1990. Where this is the case, these models are also discussed but much less comprehensively. Comment: 20 pages + 9 pages references + 1 page figures. Submitted to the International Journal of Wildland Fire
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Wildland surface fire spread modelling, 1990–2007. 2: Empirical and quasi-empirical models
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  • Jul 2009
In recent years, advances in computational power and spatial data analysis (GIS, remote sensing, etc) have led to an increase in attempts to model the spread and behaviour of wildland fires across the landscape. This series of review papers endeavours to critically and comprehensively review all types of surface fire spread models developed since 1990. This paper reviews models of an empirical or quasi-empirical nature. These models are based solely on the statistical analysis of experimentally obtained data with or without some physical framework for the basis of the relations. Other papers in the series review models of a physical or quasi-physical nature, and mathematical analogues and simulation models. The main relations of empirical models are that of wind speed and fuel moisture content with rate of forward spread. Comparisons are made of the different functional relationships selected by various authors for these variables. Comment: 22 pages + 7 pages references + 2 pages tables + 2 pages figures. Submitted to International Journal of Wildland Fire
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Wildland surface fire spread modelling, 1990–2007. 1: Physical and quasi-physical models
Article
  • Jul 2009
In recent years, advances in computational power and spatial data analysis (GIS, remote sensing, etc) have led to an increase in attempts to model the spread and behaviour of wildland fires across the landscape. This series of review papers endeavours to critically and comprehensively review all types of surface fire spread models developed since 1990. This paper reviews models of a physical or quasi-physical nature. These models are based on the fundamental chemistry and/or physics of combustion and fire spread. Other papers in the series review models of an empirical or quasi-empirical nature, and mathematical analogues and simulation models. Many models are extensions or refinements of models developed before 1990. Where this is the case, these models are also discussed but much less comprehensively. Comment: 31 pages + 8 pages references + 2 figures + 5 tables. Submitted to International Journal of Wildland Fire
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FARSITE: Fire Area Simulator—model development and evaluation
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This paper reports on the,structure of a fire growth simulation model, FARSITE, and its performance under simplified test conditions. FARSITE incorporates existing models of surface fire, crown fire, point-source fire acceleration, spotting, and fuel moisture. This documentation of how the simulation was constructed, and how the individual fire behavior models perform, will be useful to researchers and managers who use FARSITE or are interested in fire growth simulation. The models were integrated using a vector propagation technique for fire perimeter expansion that controls for both space and time resolution of fire growth over the landscape. The model produces vector fire perimeters (polygons) at specified time intervals. The vertices of these polygons contain information on the fire's spread rate and intensity, which are interpolated to produce raster maps of fire behavior. Because fire behavior at each vertex is assumed independent of the others, the simulation outputs illustrate the strict spatial consequences to fire behavior of incorporating the models into a two-dimensional simulation. Simplified test conditions show that surface fire growth and intensity conform to idealized patterns. Similarities also exist between simulated crown fires and observed patterns of extreme wind-driven fires. Complex patterns of fi re growth and behavior result from the spatial and temporal dependencies in the model. The limitations and assumptions of this approach are discussed.
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Predicting Behavior and Size of Crown Fires in the Northern Rocky Mountains
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