Browsing by Author "Kucuk O."

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A Bayesian network model for prediction and analysis of possible forest fire causes
(2020-02-01) Sevinc V.; Kucuk O.; Goltas M.
Possible causes of a forest fire ignition could be human-caused (arson, smoking, hunting, picnic fire, shepherd fire, stubble burning) or natural-caused (lightning strikes, power lines). Temperature, relative humidity, tree species, distance from road, wind speed, distance from agricultural land, amount of burnt area, month and distance from settlement are the risk factors that may affect the occurrence of forest fires. This study introduces the use of Bayesian network model to predict the possible forest fire causes, as well as to perform an analysis of the multilateral interactive relations among them. The study was conducted in Mugla Regional Directorate of Forestry area located in the southwest of Turkey. The fire data, which were recorded between 2008 and 2018 in the area, were provided by General Directorate of Forestry. In this study, after applying some different structural learning algorithms, a Bayesian network, which is built on the nodes relative humidity, temperature, wind speed, month, distance from settlement, amount of burnt area, distance from agricultural land, distance from road and tree species, was estimated. The model showed that month is the first and temperature is the second most effective factor on the forest fire ignitions. The Bayesian network model approach adopted in this study could also be used with data obtained from different areas having different sizes.
An integrated approach for mapping fire suppression difficulty in three different ecosystems of Eastern Europe
(2017-01-02) Mitsopoulos I.; Mallinis G.; Zibtsev S.; Yavuz M.; Saglam B.; Kucuk O.; Bogomolov V.; Borsuk A.; Zaimes G.
Increased fire activity, related both to human activities and to climate change, necessitates effective fire prevention and suppression strategies. The main purpose of this paper is to model and map fire suppression difficulty using common approaches in three different ecosystems in Eastern Europe by employing very high-resolution satellite imagery and landscape fire behaviour modelling. The integrated approach could allow fire managers to organize prevention and management of firefighting activities more efficiently by implementing both simple and easy-to-use risk and operational fire suppression difficulty indices. The development of cross-border common methodological approaches could foster cooperation between national authorities that would also maximize the efficiency of firefighting procedures.
Canopy fuel characteristics and fuel load in young black pine trees
(2007-01-01) Kucuk O.; Saglam B.; Bilgili E.
Crown structure and fuel loading are important factors affecting crown fire occurrence and behavior. This paper reports on the canopy fuel characteristics and regression models to determine Canopy Fuel Loading (CFL) of young black pine (Pinus nigra Arnold) trees. Equations were based on the data from 11 destructively sampled black pine plantation trees. This data was used to develop best equations fit with ordinary least squares procedures that estimate available and total canopy fuel load for young black pine plantation trees. Model fits for available and total canopy fuel load were generally good. Results indicated that available and total canopy fuel load could be easily predicted using diameter at breast height (D), variable. The resulting equations were able to account for 94% of the observed variation in the total canopy fuel load. Average tree canopy fuel load was 8.9 kg. On average 41% of canopy fuel load was allocated to the needle, 13% to the fine branch, 20% to the medium branch, 18% to thick branch and 8% to the very thick branch. Vertical distribution of canopy fuels was variable. Most foliage was found on the main branches of the medium portion of the canopy. The lower and upper portions of the crown had relatively less foliage. The results of the study allowed also for the comparisons of linear and nonlinear equations of biomass estimation commonly used in literature. © 2007 Taylor and Francis Group, LLC.
Compatible above-ground biomass equations and carbon stock estimation for small diameter Turkish pine (Pinus brutia Ten.)
(2018-05-01) Sakici O.E.; Kucuk O.; Ashraf M.I.
Small trees and saplings are important for forest management, carbon stock estimation, ecological modeling, and fire management planning. Turkish pine (Pinus brutia Ten.) is a common coniferous species and comprises 25.1% of total forest area of Turkey. Turkish pine is also important due to its flammable fuel characteristics. In this study, compatible above-ground biomass equations were developed to predict needle, branch, stem wood, and above-ground total biomass, and carbon stock assessment was also described for Turkish pine which is smaller than 8 cm diameter at breast height or shorter than breast height. Compatible biomass equations are useful for biomass prediction of small diameter individuals of Turkish pine. These equations will also be helpful in determining fire behavior characteristics and calculating their carbon stock. Overall, present study will be useful for developing ecological models, forest management plans, silvicultural plans, and fire management plans.
Crown fuel characteristics and fuel load estimates in young calabrian pine (Pinus brutia ten.) stands in Northwestern Turkey
(2008-12-01) Kucuk O.; Bilgili E.
Crown structure and fuel loading are important fuel characteristics affecting crown fire occurrence and behavior. This paper reports on the crown fuel characteristics and regression models to determine crown fuel load of young Calabrian pine (Pinus brutia Ten.) trees. Crown bulk density (CBD), crown base height (CBH) and basal area (BA) were 0.212 kg m-3, 4.5 m and 24.18 m2 ha-1, respectively. Average crown fuel load (CFL) was 1.51 kg m-2. The proportion of needle and available fuel (needle+fine branches) were 19.1 and 48.2 percent, respectively. Also, regression equations were developed for predicting needle, branch and total biomass of Calabrian pine trees. Equations were based on the data from 35 destructively sampled Calabrian pine trees. The relationships between needle and branch biomass and tree properties were determined by linear regression, considering tree properties as the independent and needle, branch and total biomass as the dependent variables. Diameter at breast height (DBH), crown length (CL) and crown width (CW) were the most significant independent variables for crown fuel biomass. The resulting equations were able to account for 58-80% of the observed variation in total biomass. The results of this study will not only contribute to the prediction of fire behavior, but it will surely be of invaluable use in other forestry disciplines.
Determination of pumper truck intervention ratios in zones with high fire potential by using geographical information system
(2014-01-01) Aricak B.; Kucuk O.; Enez K.
Fighting forest fires not only depends on the forest type, topography, and weather conditions, but is also closely related to the technical properties of fire-fighting equipment. Firefighting is an important part of fire management planning. However, because of the complex nature of forests, creating thematic layers to generate potential fire risk maps is difficult. The use of remote sensing data has become an efficient method for the discrete classification of potential fire risks. The study was located in the Central District of the Kastamonu Regional Forest Directorate, covering an area of 24,320 ha, 15,685 ha of which is forested. On the basis of stand age, crown closure, and tree species, the sizes and distributions of potential fire risk zones within the study area were determined using high-resolution GeoEye satellite imagery and geographical information system data. The status of pumper truck intervention in zones with high fire risk and the sufficiency of existing forest roads within an existing forest network were discussed based on combustible matter characteristics. Pumper truck intervention was 83% for high-risk zones, 79% for medium-risk zones, and 78% for low-risk zones. A pumper truck intervention area map along existing roads was also created. © 2014 The Authors.
Determining a fire potential map based on stand age, stand closure and tree species, using satellite imagery (Kastamonu Central Forest directorate sample)
(2014-01-01) Aricak B.; Kucuk O.; Enez K.
Becoming successful in fighting forest fires is not only a matter of taking the required measures into consideration and efficiently and economically using the resources, but also employing the cutting edge science and technology in every aspect of the process. Determining the potential fire prone regions within forest stands, plays an important role in the success rate of forest fire prevention and firefighting. Various techniques are used in the determination of fire potential; especially high resolution satellite imagery can provide very sensitive and detailed information regarding the conditions of regional topography and fuel material (fuel) accumulation. Fuel material models have long been effectively used in fire management, fire behavioral estimates and determination of fire danger risks. Additionally, fuel material maps, prepared based on fuel material features, can help in the determination of fire potential. Fire potential maps include fuel material types and their distribution in the field. In this particular study, an October, 2011 dated »GeoEye« image, encompassing 24 320 ha of Kastamonu Central Forest Directorate area, 15 685 ha of which is forested, was used. The image was classified based on fuel material features, such as tree species, mixture, crown closure, age classes, etc. Acreages and distributions of the potential fire prone areas were determined, and where these areas were concentrated, possible fire suppressing precautionary methods were discussed. As long as the satellite image acquisition is periodically supplied, fire potential map can be updated depending on fuel material features.
Development of design geometry of aluminum fittings for healthy and safety sanitary installations
(2017-01-01) Kucuk O.; Ozturk B.
With the development of the aluminum alloy fittings instead of nodular cast iron fittings, corrosion resistance, lightweight, machinability and improvements of the product quality have been important subjects at industry. Various products are wanted to be developed at this industry for the aluminum fittings which are not manufactured in Turkey. In this study, three different 1/2″ Tees were manufactured according to TS 11 standardisations. Design of the aluminum fittings in different countries and nodular cast iron fittings which are produced by Konak Rakor Company were compared with the new design which has outer rings in order to increase strength of the product. On account for maintaining the accuracy of the layout variables, wall thickness of the models were kept fixed in all test subjects. Mechanical properties of different aluminum alloys were compared to nodular cast iron under the 10 Bar pressure with FEM analysis. As a result of the analysis it was observed that the safety factor is 5.75 and the weight is 136 g for the 1/2″ nodular cast iron Tee. Highest FS (factor of safety) value which is 15 between aluminum materials were obtained from the M3/Al and the weight of the design was calculated as 58 g.
Diurnal surface fuel moisture prediction model for Calabrian pine stands in Turkey
(2019-06-01) Bilgili E.; Coskuner K.A.; Usta Y.; Saglam B.; Kucuk O.; Berber T.; Goltas M.
This study presents a dynamic model for the prediction of diurnal changes in the moisture content of dead surface fuels in normally stocked Calabrian pine stands under varying weather conditions. The model was developed based on several empirical relationships between moisture contents of dead surface fuels and weather variables, and calibrated using field data collected from three Calabrian stands from three different regions of Turkey (Mugla, southwest; Antalya, south; Trabzon, north-east). The model was tested and validated with independent measurements of fuel moisture from two sets of field observations made during dry and rainy periods. Model predictions showed a mean absolute error (MAE) of 1.19% for litter and 0.90% for duff at Mugla, and 3.62% for litter and 14.38% for duff at Antalya. When two rainy periods were excluded from the analysis at Antalya site, the MAE decreased from 14.38% to 4.29% and R2 increased from 0.25 to 0.83 for duff fuels. Graphical inspection and statistical validation of the model indicated that the diurnal litter and duff moisture dynamics could be predicted reasonably. The model can easily be adapted for other similar fuel types in the Mediterranean region.
Estimating above-ground fuel biomass in young calabrian pine (Pinus brutia Ten.)
(2009-04-16) Bilgili E.; Kucuk O.
Crown fuel biomass is of great importance in the field of forest-fire science. In this study, regression equations were developed for predicting needle, branch, and total biomass of young calabrian pine (Pinus brutia Ten.) trees and saplings. Equations were based on the data from 71 destructively sampled trees and saplings. The relationships between needle and branch biomass and tree properties were determined by linear regression, considering tree properties as the independent variable and needle, branch, and total biomass as the dependent variables. Tree and sapling properties included tree height (H), crown length (CL), crown width (CW), diameter at breast height (DBH), and root collar diameter (RCD). Results indicated that needle, branch, and total biomass could be accurately predicted using the regression equations obtained. The resulting equations were able to account for 60-94% of the observed variation in the total biomass. © 2009 American Chemical Society.
Estimation of carbon emissions from experimental fires in young anatolian black pine (Pinus nigra Arnold) plantations
(2010-05-18) Kucuk O.; Bilgili E.
This paper presents and discusses the direct carbon emissions from experimental fires in young Anatolian black pine (Pinus nigra Arnold) plantation stands. The estimates were based on eighteen experimental fires carried out under different weather and fuel conditions. Total fuel loading in plots ranged from 2.14 to 3.09 kg m-2, fuel consumption from 1.36 to 2.09 kg m-2, consumption ratio from 54 to 87%, respectively. The amount of total carbon emission ranged from 0.298 to 0.918 kg m-2. Factors affecting the amount of carbon emissions were fuel loading, burned area and consumption ratio. The results will be useful to understand me role of forest fires in C emissions, and help meet the requirements of the international agreements and regulations, such as Kyoto Protocol as well as Land Use and Land Use Change in Forestry Program (LULUCF). © by PSP.
Evaluating the frequency, dominance, resemblance analysis and diversity index of bird species in Ilgaz Mountain National Park
(2017-01-01) Kucuk O.; Evcin O.; Aslan F.
In this study, bird species inhabiting within Il-gaz Mountain National Park (IMNP) were identified. At 3 different habitat features, the frequency, similarity and dominance analyses of bird species were carried out, and their diversity indexes were determined. We identified 10 Order, 27 families and 54 bird species. According to each family, 35 Passer-iformes, 2 Ciconiiformes, 4 Falconiformes, 1 Galli-formes, 3 Columbiformes, 1 Cuculiformes, 1 Caprimulgiformes, 2 Strigiformes, 2 Coraciiformes and 1 Piciformes were observed. Through this study, 18 new bird species was recorded into avifauna of IMNP. When the most dominant order was Passer-iformes, the least dominant orders were Galliformes, Cuculiformes and Piciformes in IMNP. Sparrow (Passer domesticus) was the most observed bird in the first observation station, while they were White wagtail (Motacilla alba) and Chaffinch (Fringilla coelebs) in the second and third observation stations, respectively. The results will enlighten future studies regarding the fauna of the region, biodiversity, protection of bird species populations and future management plans.
Fire behavior prediction with artificial intelligence in thinned black pine (Pinus nigra Arnold) stand
(2023-02-01) Kucuk O.; Sevinc V.
Modeling forest fire behavior is very important for the effective control of forest fires and the setting up of necessary precautions before fires start. However, studies of forest fire behavior are complex studies that depend on many variables and usually involve large data sets. For this reason, the predictive power and speed of classical forecasting models are lower than of artificial intelligence models in cases involving big data and many variables. Moreover, classical forecasting models must satisfy certain statistical assumptions, unlike artificial intelligence methods. Thus, in this study, predictions were made of surface fire behavior, especially the rate of fire spread and the fire intensity, at the location at which fires started using two artificial intelligence methods, an artificial neural network and a decision tree. The accuracy of the developed models was fitted and tested. Finally, the classical regression model for predicting surface fire behavior was compared with the two artificial intelligence methods. The accuracy measures of the artificial intelligence models were found to be better than those of the classical model.
Fuel modelling and potential fire behavior in Turkey
(2015-01-01) Kucuk O.; Bilgili E.; Fernandes P.M.
Description of fuel characteristics is an essential input to fire behavior models that can provide decision-support for fire management. Fuel models describe fuel characteristics for fire modeling systems based on Rothermel's fire spread model. In this study, fire behavior data collected in field experiments in different fuel complexes in Turkey is used in the process of fuel model development. Nine fuel models were built for low and tall maquis, Anatolian black pine (P. nigra J.F. Arnold subsp. nigra var. caramanica (Loudon) Rehder), litter, and slash variable in age and load. BehavePlus simulations of fire rate of spread, flame length and fireline intensity for typical summer weather conditions highlight the quite different fire potential between the studied fuel types. The difficulty in dealing with fuel complexes dominated by live fuels was evident from the simulations. On the contrary, the model correctly predicted the observed temporal decrease of fire behavior in slash. This study shows the crucial importance of experimental fire data to parameterize fuel models.
Habitat suitability model with maximum entropy approach for European roe deer (Capreolus capreolus) in the Black Sea Region
(2019-11-01) Evcin O.; Kucuk O.; Akturk E.
Evaluating the relationships between wildlife species and their habitats helps to predict effects of habitat change for present and future management of wild animal populations. Building ecological models are good ways to understand and manage wildlife populations and to predict various environmental scenarios. Recently, management of ungulates is becoming more important in Europe due to a high demand of hunting and their role in biodiversity. European roe deer (Capreolus capreolus) is the smallest species of cervids and has a widespread distribution in Turkey. In this study, two habitat suitability models of roe deers, living in the Black Sea Region in Turkey, were created by using a maximum entropy (MaxEnt) approach. Two wildlife development areas, which have widely different habitat types, were selected as study sites. As a result of this study, area under the curve (AUC) values were found to be above 0.80. According to the modeling results, in two different habitat types, ecological variables are quite similar in general. This study is the first study on modeling European roe deers in Turkey.
Predicting canopy fuel characteristics in Pinus brutia Ten., Pinus nigra Arnold and Pinus pinaster Ait. Forests from stand variables in North-Western Turkey
(2021-02-01) Kucuk O.; Goltas M.; Demirel T.; Mitsopoulos I.; Bilgili E.
Canopy fuel characteristics play an important role in crown fire behaviour in conifer forests. In this study, the canopy fuel characteristics of Calabrian pine, Anatolian Black pine and Maritime pine stands in Turkey are estimated using forest stand parameters. Sets of equations are fitted to the measured data revealing correlations between canopy fuel characteristics and stand parameters by performing a stepwise multiple regression analysis. At the stand level, the resulting models explain a high percentage of the observed variability. The developed equations can be used by forest and fire managers to estimate canopy fuel characteristics, predict crown-fire behaviour and design fuel treatment projects in Turkey.
Rates of surface fire spread in a young calabrian pine (Pinus brutia Ten.) plantation
(2012-01-01) Kucuk O.; Bilgili E.; Bulut S.; Fernandes P.M.
Fire behaviour data and models are essential in modern fire management. Thirty five experimental line-ignited fires were carried out in a young calabrian pine (Pinus brutia Ten.) stand with the objective of modelling the rate of surface fire spread. Relationships between rate of fire spread, and fuel, weather and topographical conditions were established by correlation and regression analyses. Dead fine fuel loading ranged from 0.19 to 0.68 kg m-2. Rate of fire spread varied from 0.3 to 3.75 m min-1 and flame length ranged from 5 cm to 55 cm. Rate of fire spread equations were generated that described the relationships of spread rate with fuel and weather conditions, using linear regression models. Wind speed had a dominant effect on rate of surface fire spread and explained 72% (P < 0.01) of the observed variation.
Visibility analysis of fire lookout towers in the Boyabat State Forest Enterprise in Turkey
(2017-07-01) Kucuk O.; Topaloglu O.; Altunel A.O.; Cetin M.
For a successful fire suppression, it is essential to detect and intervene forest fires as early as possible. Fire lookout towers are crucial assets in detecting forest fires, in addition to other technological advancements. In this study, we performed a visibility analysis on a network of fire lookout towers currently operating in a relatively fire-prone region in Turkey’s Western Black Sea region. Some of these towers had not been functioning properly; it was proposed that these be taken out of the grid and replaced with new ones. The percentage of visible areas under the current network of fire lookout towers was 73%; it could rise to 81% with the addition of newly proposed towers. This study was the first research to conduct a visibility analysis of current and newly proposed fire lookout towers in the Western Black Sea region and focus on its forest fire problem.