Orman Yangınları Sonrası Ekosistem Tabanlı Planlamaya Doğru: Yanma Derinliğinin Sınıflandırılması

Coşkun Okan Güney; Ahmet Mert; Serkan Gülsoy

doi:10.35341/afet.1197031

Derleme

Toward Ecosystem-Based Planning After Forest Fires: Classification of Fire/Burn Severity

Yıl 2023, Cilt: 6 Sayı: 1, 206 - 225, 31.03.2023

Coşkun Okan Güney , Ahmet Mert , Serkan Gülsoy

https://doi.org/10.35341/afet.1197031

Öz

Forest fires are part of natural processes that affect ecosystems all around the world. Fire affects biophysical processes at different spatio-temporal scales, from micro-scale impacts to broad landscape patterns and processes. In order to implement post-fire decision-making processes, managers should be able to adequately characterize burned areas. This is possible by determining fire severity, which is considered as the degree of fire-induced ecological change in both vegetation and soil and is one of the most important components of the fire regime. Fire severity can be classified based on visual observation of the degree of fuels consumed and the amount of char on plant and soil surfaces that remained unconsumed after the fire. Fire severity is generally classified as unburned, low, moderate, and high. Assessing post-fire damage of large areas can take a lot of effort, money, and time. Therefore, after large fires, remote sensing methods are often used to determine the extent of fire damage to the ecosystems. Fire severity classifications are usually expressed in terms of spectral indices derived from optical remote sensing data or by using maps derived from active remote sensing methods such as SAR and LiDAR. Fire severity classification maps allow to determine the impact of forest fires on soil, water, ecosystem flora and fauna, and the atmosphere. They can therefore promote a more sustainable ecosystem-based planning of burned/unburned areas. In this review, information about the concept of fire severity and fire severity classification is given. For future studies on this topic, the literature was reviewed and summarized and its advantages and disadvantages were discussed.

Anahtar Kelimeler

Forest Fire, Fire Ecology, Fire Regime, Fire/Burn Severity, Remote Sensing

Kaynakça

Agee, J. K., 1993, Fire ecology of Pacific Northwest forests, California, ABD, Island press.
Akkuzu E, Kucuk Ö, Ünal S, Evcin Ö, Ugış A. (2014). Effects of Forest Fires on Mammal Species: A Brief Review. International Forest Fire Conference in Black Sea Region, Kastamonu.
Albini, F. A., 1976, Estimating wildfire behavior and effects, Intermountain Forest and Range Experiment Station, Utah, ABD, 92.
Albini, F. A. Reinhardt, E. D., 1995, Modeling ignition and burning rate of large woody natural fuels, International Journal of Wildland Fire, 5 (2): 81-91. https://doi.org/10.1071/WF9950081 Ariza, A., Rey, J. S. de Miguel, S. M., 2019, Comparison of maximum likelihood estimators and regression models for burn severity mapping in Mediterranean forests using Landsat TM and ETM+ data, Revista Cartogr ráfica (98): 145-177. https://doi.org/10.35424/rcarto.i98.145
Arnett, J. T. T. R., Coops, N. C., Daniels, L. D. Falls, R. W., 2015, Detecting forest damage after a low-severity fire using remote sensing at multiple scales, International Journal of Applied Earth Observation and Geoinformation, 35: 239-246. https://doi.org/10.1016/j.jag.2014.09.013 Baysal, İ., Bilgili, E. Bașkent, E. Z., 2016, Orman Yangınları ve Orman Amenajman Planları, Kastamonu Üniversitesi Orman Fakültesi Dergisi, 16 (1): 169-180. https://doi.org/10.17475/kujff.48428
Bendell, J. F., 1974, Effects of fire on birds and mammals, In: Fire and ecosystems, Eds: Kozlowski, T. T., Minnesota, ABD: Academic Press, New York, p.
Bird, R. B., Bird, D. W., Codding, B. F., Parker, C. H. Jones, J. H., 2008, The ‘‘fire stick farming’’ hypothesis: Australian Aboriginal foraging strategies, biodiversity, and anthropogenic fire mosaics, PNAS, 105 (39): 1- 6. https://doi.org/10.1073/pnas.08047571
Bond, T. C., Streets, D. G., Yarber, K. F., Nelson, S. M., Woo, J. H. Klimont, Z., 2004, A technology‐based global inventory of black and organic carbon emissions from combustion, Journal of Geophysical Research: Atmospheres, 109 (D14). https://doi.org/10.1029/2003JD003697
Bond, W. J. Keeley, J. E., 2005, Fire as a global ‘herbivore’: the ecology and evolution of flammable ecosystems, Trends in ecology & evolution, 20 (7): 387-394. https://doi.org/10.1016/j.tree.2005.04.025
Bowman, D. M., Balch, J. K., Artaxo, P., Bond, W. J., Carlson, J. M., Cochrane, M. A., D’Antonio, C. M., DeFries, R. S., Doyle, J. C. Harrison, S. P., 2009, Fire in the Earth system, Science, 324 (5926): 481-484. https://doi.org/10.1126/science.1163886
Brewer, C. K., J. Chris Winne, Roland L. Redmond, David W. Opitz Mangrich, M. V., 2005, Classifying and mapping wildfire severity: A comparison of methods, Photogrammetric Engineering & Remote Sensing, 71: 1311-1320. https://doi.org/10.14358/PERS.71.11.1311
Butler, B., Cohen, J., Latham, D., Schuette, R., Sopko, P., Shannon, K., Jimenez, D. Bradshaw, L., 2004, Measurements of radiant emissive power and temperatures in crown fires, Canadian Journal of Forest Research, 34 (8): 1577-1587. https://doi.org/10.1139/X04-060
Byram, G., 1959, Combustion of forest fuels. In ‘Forest fire: control and use’.(Ed. KP Davis) pp. 61–89, McGraw-Hill: New York.
Cansler, C. A. McKenzie, D., 2012, How robust are burn severity indices when applied in a new region? Evaluation of alternate field-based and remote-rensing methods, Remote Sensing, 4 (2): 456-483. https://doi.org/10.3390/rs4020456
Cardil, A., Mola-Yudego, B., Blazquez-Casado, A. Gonzalez-Olabarria, J. R., 2019, Fire and burn severity assessment: Calibration of Relative Differenced Normalized Burn Ratio (RdNBR) with field data, Journal of Environmental Management, 235: 342-349. https://doi.org/10.1016/j.jenvman.2019.01.077
Chen, X., Vogelmann, J. E., Rollins, M., Ohlen, D., Key, C. H., Yang, L., Huang, C. Shi, H., 2011, Detecting post- fire burn severity and vegetation recovery using multitemporal remote sensing spectral indices and field- collected composite burn index data in a ponderosa pine forest, International Journal of Remote Sensing, 32 (23): 7905-7927. https://doi.org/10.1080/01431161.2010.524678
Chuvieco, E., Riaño, D., Danson, F. M. Martin, P., 2006, Use of a radiative transfer model to simulate the postfire spectral response to burn severity, Journal of Geophysical Research: Biogeosciences, 111 (G4). https://doi.org/10.1029/2005JG00014
Chuvieco, E., Mouillot, F., van der Werf, G. R., San Miguel, J., Tanasse, M., Koutsias, N., García, M., Yebra, M., Padilla, M. Gitas, I., 2019, Historical background and current developments for mapping burned area from satellite Earth observation, Remote sensing of Environment, 225: 45-64. https://doi.org/10.1016/j.rse.2019.02.013
Cochrane, M. A. Ryan, K. C., 2009, Fire and fire ecology: Concepts and principles, In: Tropical Fire Ecology, Eds: Springer, p. 25-62. https://doi.org/10.1007/978-3-540-77381-8_2
Conard, S. G., Sukhinin, A. I., Stocks, B. J., Cahoon, D. R., Davidenko, E. P. Ivanova, G. A., 2002, Determining effects of area burned and fire severity on carbon cycling and emissions in Siberia, Climatic change, 55 (1- 2): 197-211. https://doi.org/10.1023/A:1020207710195
Cruz, M., Butler, B., Alexander, M., Forthofer, J. Wakimoto, R., 2006, Predicting the ignition of crown fuels above a spreading surface fire. Part I: Model idealization, International Journal of Wildland Fire, 15. https://doi.org/10.1071/WF04061
De Santis, A. Chuvieco, E., 2009, GeoCBI: a modified version of the Composite Burn Index for the initial assessment of the short-term burn severity from remotely sensed data, Remote sensing of Environment, 113 (3): 554-562. https://doi.org/10.1016/j.rse.2008.10.011
DeBano, L. F., Ffolliott, P. F. Baker, M. B., 1996, Fire severity effects on water resources, US Department of Agriculture, Forest Service, 77-84.
Dickinson, M. B. Johnson, E. A., 2001, Fire effects on trees, In: Forest fires, Eds: Elsevier, p. 477-525. https://doi.org/10.1016/B978-012386660-8/50016-7
Dickinson, M. B. Johnson, E. A., 2004, Temperature-dependent rate models of vascular cambium cell mortality, Canadian Journal of Forest Research, 34 (3): 546-559. https://doi.org/10.1139/X03-223
Epting, J., Verbyla, D. Sorbel, B., 2005, Evaluation of remotely sensed indices for assessing burn severity in interior Alaska using Landsat TM and ETM+, Remote sensing of Environment, 96 (3-4): 328-339. https://doi.org/10.1016/j.rse.2005.03.002
Fernández-Álvarez, M., Armesto, J. Picos, J., 2019, LiDAR-based wildfire prevention in WUI: The automatic detection, measurement and evaluation of forest fuels, Forests, 10 (2): 148. https://doi.org/10.3390/f10020148
Fernández-García, V., Santamarta, M., Fernández-Manso, A., Quintano, C., Marcos, E. Calvo, L., 2018, Burn severity metrics in fire-prone pine ecosystems along a climatic gradient using Landsat imagery, Remote sensing of Environment, 206: 205-217. https://doi.org/10.1016/j.rse.2017.12.029
Fernandez, C. Vega, J. A., 2018, Evaluation of the rusle and disturbed wepp erosion models for predicting soil loss in the first year after wildfire in NW Spain, Environmental Research, 165: 279-285. https://doi.org/10.1016/j.envres.2018.04.008
Frandsen, W. H. Ryan, K. C., 1986, Soil moisture reduces belowground heat flux and soil temperatures under a burning fuel pile, Canadian Journal of Forest Research, 16 (2): 244-248. https://doi.org/10.1139/x86-043
French, N. H., Kasischke, E. S., Hall, R. J., Murphy, K. A., Verbyla, D. L., Hoy, E. E. Allen, J. L., 2008, Using Landsat data to assess fire and burn severity in the North American boreal forest region: an overview and summary of results, International Journal of Wildland Fire, 17 (4): 443-462. https://doi.org/10.1071/WF08007
García-Llamas, P., Suárez-Seoane, S., Fernández-Guisuraga, J. M., Fernández-García, V., Fernández-Manso, A., Quintano, C., Taboada, A., Marcos, E. Calvo, L., 2019, Evaluation and comparison of Landsat 8, Sentinel-2 and Deimos-1 remote sensing indices for assessing burn severity in Mediterranean fire-prone ecosystems, International Journal of Applied Earth Observation and Geoinformation, 80: 137-144. https://doi.org/10.1016/j.jag.2019.04.006
Güney, C. O., 2022, Uydu görüntülerinden türetilen spektral indeksler kullanilarak orman ekosistemlerinde yanma derinliğinin tahmin edilmesi, Doktora, Isparta Uygulamalı Bilimler Üniversitesi, Lisansüstü Eğitim Enstitüsü, Isparta.
Güney, C. O., Sarı, A., Cekim, H. O., Küçüksille, E. U., Sentürk, Ö., Gülsoy, S. Özkan, K., 2022, An advanced approach for leaf flammability index estimation, International Journal of Wildland Fire, 31 (3): 277-290. https://doi.org/10.1071/WF21022
Hall, R. J., Freeburn, J. T., De Groot, W. J., Pritchard, J. M., Lynham, T. J. Landry, R., 2008, Remote sensing of burn severity: experience from western Canada boreal fires, International Journal of Wildland Fire, 17 (4): 476-489. https://doi.org/10.1071/WF08013 Heikkilä, T. V., Grönqvist, R. Jurvélius, M., 2010, Wildland fire management: handbook for trainers, Roma, İtaly, FAO.
Hoscilo, A., Tansey, K. J. Page, S. E., 2013, Post-fire vegetation response as a proxy to quantify the magnitude of burn severity in tropical peatland, International Journal of Remote Sensing, 34 (2): 412-433. https://doi.org/10.1080/01431161.2012.709328
Hudak, A. T., Morgan, P., Bobbitt, M. J., Smith, A. M. S., Lewis, S. A., Lentile, L. B., Robichaud, P. R., Clark, J. T.
McKinley, R. A., 2007, The relationship of multispectral satellite imagery to immediate fire effects, Fire ecology, 3 (1): 64-90. https://doi.org/10.4996/fireecology.0301064 Johnson, E. A. Miyanishi, K., 2001, Forest Fires: Behavior and Ecological Effects, Canada, Academic Press. https://doi.org/10.1016/B978-0-123-86660-8.X5000-4
Keeley, J. E. Zedler, P. H., 1998, Evolution of life histories in Pinus, In: Ecology and biogeography of Pinus, Eds: Richardson, D. M., Cambridge, United Kingdom: Cambridge University Press, p. 219-250.
Keeley, J. E. Fotheringham, C. J., 2000, Role of fire in regeneration from seed, Seeds: the ecology of regeneration in plant communities, 2: 311-330. Keeley, J. E., 2009, Fire intensity, fire severity and burn severity: a brief review and suggested usage, International Journal of Wildland Fire, 18 (1): 116-126. https://doi.org/10.1071/WF07049
Key, C. H. Benson, N. C., 1999, Measuring and remote sensing of burn severity. Proceedings Joint Fire Science Conference and Workshop. Idaho, USA, University of Idaho and International Association of Wildland Fire Moscow, ID. 2: 284.
Key, C. H., 2006, Ecological and sampling constraints on defining landscape fire severity, Fire ecology, 2 (2): 34-59. https://doi.org/10.4996/fireecology.0202034
Key, C. H. Benson, N. C., 2006, Landscape assessment (LA), In: In: Lutes, Duncan C.; Keane, Robert E.; Caratti, John F.; Key, Carl H.; Benson, Nathan C.; Sutherland, Steve; Gangi, Larry J. 2006. FIREMON: Fire effects monitoring and inventory system. Gen. Tech. Rep. RMRS-GTR-164-CD. Fort Collins, CO: US Department of Agriculture, Forest Service, Rocky Mountain Research Station. p. LA-1-55, Eds, p. https://doi.org/10.2737/RMRS-GTR-164
Küçük, Ö., 2009, Yangın Ekolojisi, I.Orman Yangınları ile Mücadele Sempozyumu, 07-10 Ocak 2009, Antalya. Lasaponara, R. Tucci, B., 2019, Identification of burned areas and severity using SAR Sentinel-1. IEEE Geoscience and Remote Sensing Letters. 16: 917-921.
Lentile, L. B., Holden, Z. A., Smith, A. M., Falkowski, M. J., Hudak, A. T., Morgan, P., Lewis, S. A., Gessler, P. E. Benson, N. C., 2006, Remote sensing techniques to assess active fire characteristics and post-fire effects, International Journal of Wildland Fire, 15 (3): 319-345. https://doi.org/10.1071/WF05097
Lentile, L. B., Morgan, P., Hudak, A. T., Bobbitt, M. J., Lewis, S. A., Smith, A. M. S. Robichaud, P. R., 2007, Post- fire burn severity and vegetation response following eight large wildfires across the Western United States, Fire ecology, 3 (1): 91-108. https://doi.org/10.4996/fireecology.0301091
Liu, Z. Wimberly, M. C., 2015, Climatic and landscape influences on fire regimes from 1984 to 2010 in the western United States, PLoS One, 10 (10): e0140839. https://doi.org/10.1371/journal.pone.0140839
Mallinis, G., Mitsopoulos, I. Chrysafi, I., 2018, Evaluating and comparing Sentinel 2A and Landsat-8 Operational Land Imager (OLI) spectral indices for estimating fire severity in a Mediterranean pine ecosystem of Greece, GIScience & Remote Sensing, 55 (1): 1-18. https://doi.org/10.1080/15481603.2017.1354803 Mauri, E. Pons, P., 2019, Handbook of good practices in post-wildfire management, 2nd ed., Anifog Project I+D+i CGL2014-54094-R, Spain, Universitat de Girona.
Michaletz, S. T. Johnson, E. A., 2006, A heat transfer model of crown scorch in forest fires, Canadian Journal of Forest Research, 36 (11): 2839-2851. https://doi.org/10.1139/X06-158
Michaletz, S. T. Johnson, E. A., 2007, How forest fires kill trees: a review of the fundamental biophysical processes, Scandinavian Journal of Forest Research, 22 (6): 500-515. https://doi.org/10.1080/02827580701803544
Miller, J. D. Thode, A. E., 2007, Quantifying burn severity in a heterogeneous landscape with a relative version of the delta Normalized Burn Ratio (dNBR), Remote sensing of Environment, 109 (1): 66-80. https://doi.org/10.1016/j.rse.2006.12.006
Miller, J. D. Quayle, B., 2015, Calibration and validation of immediate post-fire satellite-derived data to three severity metrics, Fire ecology, 11 (2). https://doi.org/10.4996/fireecology.1102012
Miranda, A., Amorim, J. H., Valente, J., Monteiro, A., Ferreira, J. Borrego, C., 2014, Forest fires effects on the atmosphere: 20 years of research in Portugal, In: Advances in forest fire research, Eds: viegas, D. X.: Imprensa da Universidade de Coimbra, p. 283-297. https://doi.org/10.14195/978-989-26-0884-6_30
Montealegre, A. L., Lamelas, M. T., Tanase, M. A. de la Riva, J., 2014, Forest fire severity assessment using ALS data in a Mediterranean environment, Remote Sensing, 6 (5): 4240-4265. https://doi.org/10.3390/rs6054240
Morgan, P., Hardy, C. C., Swetnam, T. W., Rollins, M. G. ve Long, D. G., 2001, Mapping fire regimes across time and space: understanding coarse and fine-scale fire patterns, International Journal of Wildland Fire, 10 (4), 329-342.
Morgan, P., Keane, R. E., Dillon, G. K., Jain, T. B., Hudak, A. T., Karau, E. C., Sikkink, P. G., Holden, Z. A. Strand, E. K., 2014, Challenges of assessing fire and burn severity using field measures, remote sensing and modelling, International Journal of Wildland Fire, 23 (8): 1045-1060. https://doi.org/10.1071/WF13058
Neary, D. G., Ryan, K. C. DeBano, L. F., 2005, Wildland Fire in Ecosystems: Effects of Fire on Soils and Water, Gen. Tech. Rep. RMRS-GTR-42-vol. 4. Ogden, UT: US Department of Agriculture, Forest Service, Rocky Mountain Research Station. https://doi.org/10.2737/RMRS-GTR-42-V4
Packham, D. R. Pompe, A., 1971, Radiation temperatures of forest fires, Australian Forest Research, 5 (3): 1-8.
Parker, B. M., Lewis, T. Srivastava, S. K., 2015, Estimation and evaluation of multi-decadal fire severity patterns using Landsat sensors, Remote sensing of Environment, 170: 340-349. https://doi.org/10.1016/j.rse.2015.09.014
Parks, S. A., Dillon, G. K. Miller, C., 2014, A new metric for quantifying burn severity: the relativized burn ratio, Remote Sensing, 6 (3): 1827-1844. https://doi.org/10.3390/rs6031827
Pausas, J. G. Keeley, J. E., 2009, A burning story: the role of fire in the history of life, BioScience, 59 (7): 593- 601. https://doi.org/10.1525/bio.2009.59.7.10
Pleniou, M. Koutsias, N., 2013, Sensitivity of spectral reflectance values to different burn and vegetation ratios: A multi-scale approach applied in a fire affected area, ISPRS Journal of Photogrammetry and Remote Sensing, 79: 199-210. https://doi.org/10.1016/j.isprsjprs.2013.02.016
Roberts, S. L., van Wagtendonk, J. W., Miles, A. K., Kelt, D. A. Lutz, J. A., 2008, Modeling the effects of fire severity and spatial complexity on small mammals in Yosemite National Park, California, Fire ecology, 4 (2): 83-104. https://doi.org/10.4996/fireecology.0402083
Ryan, K. C. Noste, N. V., 1985, Evaluating prescribed fires, in: JE Lotan et al.(tech. coor), Proceedings – Symposium and Workshop on Wilderness Fire, USDA Forest Service Intermountain Forest and Range Experiement Station, General Technical Report INT-182.Utah State University, 230-238.
Ryan, K. C. Frandsen, W. H., 1991, Basal injury from smoldering fires in mature Pinus ponderosa Laws, International Journal of Wildland Fire, 1 (2): 107-118. https://doi.org/10.1071/WF9910107
Ryan, K. C., 2002, Dynamic interactions between forest structure and fire behavior in boreal ecosystems,Silva Fennica, 36 (1): 13-39. https://doi.org/10.14214/sf.548
Ryan, K. C., Jones, A. T., Koerner, C. L. Lee, K. M., 2012, Wildland Fire in Ecosystems: Effects of Fire on Cultural Resources and Archaeology, Gen. Tech. Rep. RMRS-GTR-42-vol. 3. Fort Collins, CO: US Department of Agriculture, Forest Service, Rocky Mountain Research Station. 224 p. https://doi.org/10.2737/RMRS-GTR- 42
Sandberg, D. V., 2009, Wildland fire in ecosystems: effects of fire on air, Gen. Tech. Rep. RMRS-GTR-42-vol. 5. Ogden, UT: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. https://doi.org/10.2737/RMRS-GTR-42-V5
Satio, K., 2001, Flames, In: In: Forest Fires Behavior and Ecological Effects, Eds: Johnson, E. A. M., K., eds. San Diego: Academic Press, p. 11-54.
Saulino, L., Rita, A., Migliozzi, A., Maffei, C., Allevato, E., Garonna, A. P. Saracino, A., 2020, Detecting burn severity across Mediterranean forest types by coupling medium-spatial resolution satellite imagery and field data, Remote Sensing, 12 (4). https://doi.org/10.3390/rs12040741 Simard, S. J., 1991, Fire severity, changing scales, and how things hang together, International Journal of Wildland Fire, 1 (1): 23-34. https://doi.org/10.1071/WF9910023
Skowronski, N. S., Gallagher, M. R. Warner, T. A., 2020, Decomposing the interactions between fire severity and canopy fuel structure using multi-temporal, active, and passive remote sensing approaches, Fire, 3 (1). https://doi.org/10.3390/fire3010007
Smith, J. K., 1997, Fire Ecology of The Forest Habitat Types of Northern Idaho, General Technical Report INT-GTR-363, vol.363, US Department of Agriculture, Forest Service, Intermountain Research Station. https://doi.org/10.2737/INT-GTR-363
Smith, J. K., Lyon, L. J., Huff, M., Hooper, R., Telfer, E. Schreiner, D., 2000, Wildland Fire in Ecosystems. Effects of Fire on Fauna, General Technical Report, RMRS-GTR-42. Rocky Mountain Research Station, USDA Forest Service.
Soverel, N. O., Perrakis, D. D. B. Coops, N. C., 2010, Estimating burn severity from Landsat dNBR and RdNBR indices across western Canada, Remote sensing of Environment, 114 (9): 1896-1909. https://doi.org/10.1016/j.rse.2010.03.013
Stocks, B. J., Lynham, T., Lawson, B., Alexander, M., Wagner, C. V., McAlpine, R. Dube, D., 1989, Canadian forest fire danger rating system: an overview, The Forestry Chronicle, 65 (4): 258-265.
Szpakowski, D. Jensen, J., 2019, A review of the applications of remote sensing in fire ecology, Remote Sensing, 11 (22). https://doi.org/10.3390/rs11222638
Tanase, M., Kennedy, R. Aponte, C., 2015a, Radar Burn Ratio for fire severity estimation at canopy level: An example for temperate forests, Remote sensing of Environment, 170: 14-31.
Tanase, M. A., Kennedy, R. Aponte, C., 2015b, Fire severity estimation from space: a comparison of active and passive sensors and their synergy for different forest types, International Journal of Wildland Fire, 24 (8). https://doi.org/10.1071/wf15059 Turner, M. G., Baker, W. L., Peterson, C. J. Peet, R. K., 1998, Factors influencing succession: Lessons from large, infrequent natural disturbances, Ecosystems, 1 (6): 511-523. https://doi.org/10.1007/s100219900047
Valor, T., González-Olabarria, J. R., Piqué, M. Casals, P., 2017, The effects of burning season and severity on the mortality over time of Pinus nigra spp. salzmannii (Dunal) Franco and P. sylvestris L, Forest Ecology and Management, 406: 172-183. https://doi.org/10.1016/j.foreco.2017.08.027
Veraverbeke, S., Lhermitte, S., Verstraeten, W. W. Goossens, R., 2011, Evaluation of pre/post-fire differenced spectral indices for assessing burn severity in a Mediterranean environment with Landsat Thematic Mapper, International Journal of Remote Sensing, 32 (12): 3521-3537. https://doi.org/10.1080/01431161003752430
Veraverbeke, S. Hook, S. J., 2013, Evaluating spectral indices and spectral mixture analysis for assessing fire severity, combustion completeness and carbon emissions, International Journal of Wildland Fire, 22 (5). https://doi.org/10.1071/wf12168
Verbyla, D. L., Kasischke, E. S. Hoy, E. E., 2008, Seasonal and topographic effects on estimating fire severity from Landsat TM/ETM+ data, International Journal of Wildland Fire, 17 (4): 527-534. https://doi.org/10.1071/WF08038
Vieira, D. C. S., Fernández, C., Vega, J. A. Keizer, J. J., 2015, Does soil burn severity affect the post-fire runoff and interrill erosion response? A review based on meta-analysis of field rainfall simulation data, Journal of Hydrology, 523: 452-464. https://doi.org/10.1016/j.jhydrol.2015.01.071
Wang, C. Glenn, N. F., 2009, Estimation of fire severity using pre- and post-fire LiDAR data in sagebrush steppe rangelands, International Journal of Wildland Fire, 18 (7). https://doi.org/10.1071/wf08173
Wells, C. G., Campbell, R. E., DeBano, L. F., Lewis, C. E., Fredriksen, R. L., Franklin, E. C., Froelich, R. C. Dunn, P. H., 1979, Effects of Fire On Soil: A State-of-Knowledge Review, Denver, Colorado, US Department of Agriculture, Forest Service.
Whelan, R. J., 1995, The ecology of fire, Cambridge university press, p.
White, J. D., Ryan, K. C., Key, C. C. Running, S. W., 1996, Remote sensing of forest fire severity and vegetation recovery, International Journal of Wildland Fire, 6 (3): 125-136. https://doi.org/10.1071/WF9960125
White, P. S. Pickett, S. T. A., 1985, Natural Disturbance and Patch Dynamics: An Introduction, In: Pickett, S.T.A., White, Peter S., The Ecology of Natural Disturbance and Patch Dynamics, Eds: Academic Press, p. 313. https://doi.org/10.1016/C2009-0-02952-3
Willard, E. E., Wakimoto, R. H. Ryan, K. C., 1995, Vegetation Recovery in Sedge Meadow Communities Within the Red Bench Fire, Glacier National Park, Fire in wetlands: a management perspective. Proceedings of the Tall Timbers Fire Ecology Conference, No. 19., Tall Timbers Research Station, Tallahassee, FL., 102-110.
URL 1, 2022, Wildfire Rank-Province of British Columbia, https://www2.gov.bc.ca/gov/content/safety/wildfire-status/wildfire-response/about-wildfire/wildfire- rank: Son Erişim Tarihi: 26.10.2022.

Orman Yangınları Sonrası Ekosistem Tabanlı Planlamaya Doğru: Yanma Derinliğinin Sınıflandırılması

Yıl 2023, Cilt: 6 Sayı: 1, 206 - 225, 31.03.2023

Coşkun Okan Güney , Ahmet Mert , Serkan Gülsoy

https://doi.org/10.35341/afet.1197031

Öz

Orman yangınları dünya üzerindeki ekosistemleri etkileyen doğal bir sürecin parçasıdır. Yangın, mikro ölçekli fenomenden geniş peyzaj desenleri ve süreçlerine kadar birden fazla zamansal ve mekânsal ölçekte biyofiziksel süreçleri etkiler. Yöneticiler yangın sonrası karar verme süreçlerini gerçekleştirebilmek için yanan alanların karakterizasyonunu iyi yapabilmelidir. Bu ise hem bitki örtüsü hem de toprakta yangının neden olduğu ekolojik değişimin derecesi olarak kabul edilen ve yangın rejiminin en önemli bileşenlerinden olan yanma derinliğinin tespiti ile mümkündür. Yanma derinliği, yanıcı madde tüketimi derecesinin görsel olarak gözlemlenmesi, yangından sonra tüketilmemiş bitki ve toprak yüzeylerindeki kömürleşme miktarı temelinde sınıflandırılabilir. Bu sınıflandırmalar genellikle yanmamış, az yanmış, orta derecede yanmış ve çok yanmış alanlara ayrılarak yapılır. Bazen yangınlar çok büyük alanlarda meydana gelir ve bu alanlarda zarar tespitleri yapmak çok fazla emek, para ve zaman gerektirebilir. Bu yüzden büyük yangınlar sonrası yangının ekosisteme verdiği zararın derecesi belirlenirken uzaktan algılama yöntemleri sıklıkla kullanılır. Yanma derinliği sınıflandırmaları genellikle optik uzaktan algılama verilerinden türetilen spektral indeksler ile ya da SAR ve LiDAR gibi aktif uzaktan algılama yöntemlerinden elde edilen haritalar ile ifade edilir. Yanma derinliğini sınıflandıran haritalar, orman yangınların toprak, su, ekosistem florası ve faunası, atmosfer üzerindeki etkilerini tanımlayabilir ve yangınlar sonucu ortaya çıkan farklı derecelerde yanmış/ yanmamış alanların sürdürebilir ekolojik bir yaklaşım ile planlanmasında kullanılabilir. Bu çalışmada yanma derinliği kavramı ve yanma derinliği sınıflandırmalarının aşamaları hakkında bilgiler verilmiş, bu konu hakkında bundan sonra yapılacak çalışmalar için literatür özetlenerek konunun iyi ve eksik yönleri tartışılmıştır.

Anahtar Kelimeler

Orman Yangını, Yangın Ekolojisi, Yangın Rejimi, Yanma Derinliği, Uzaktan Algılama

Kaynakça

Agee, J. K., 1993, Fire ecology of Pacific Northwest forests, California, ABD, Island press.
Akkuzu E, Kucuk Ö, Ünal S, Evcin Ö, Ugış A. (2014). Effects of Forest Fires on Mammal Species: A Brief Review. International Forest Fire Conference in Black Sea Region, Kastamonu.
Albini, F. A., 1976, Estimating wildfire behavior and effects, Intermountain Forest and Range Experiment Station, Utah, ABD, 92.
Albini, F. A. Reinhardt, E. D., 1995, Modeling ignition and burning rate of large woody natural fuels, International Journal of Wildland Fire, 5 (2): 81-91. https://doi.org/10.1071/WF9950081 Ariza, A., Rey, J. S. de Miguel, S. M., 2019, Comparison of maximum likelihood estimators and regression models for burn severity mapping in Mediterranean forests using Landsat TM and ETM+ data, Revista Cartogr ráfica (98): 145-177. https://doi.org/10.35424/rcarto.i98.145
Arnett, J. T. T. R., Coops, N. C., Daniels, L. D. Falls, R. W., 2015, Detecting forest damage after a low-severity fire using remote sensing at multiple scales, International Journal of Applied Earth Observation and Geoinformation, 35: 239-246. https://doi.org/10.1016/j.jag.2014.09.013 Baysal, İ., Bilgili, E. Bașkent, E. Z., 2016, Orman Yangınları ve Orman Amenajman Planları, Kastamonu Üniversitesi Orman Fakültesi Dergisi, 16 (1): 169-180. https://doi.org/10.17475/kujff.48428
Bendell, J. F., 1974, Effects of fire on birds and mammals, In: Fire and ecosystems, Eds: Kozlowski, T. T., Minnesota, ABD: Academic Press, New York, p.
Bird, R. B., Bird, D. W., Codding, B. F., Parker, C. H. Jones, J. H., 2008, The ‘‘fire stick farming’’ hypothesis: Australian Aboriginal foraging strategies, biodiversity, and anthropogenic fire mosaics, PNAS, 105 (39): 1- 6. https://doi.org/10.1073/pnas.08047571
Bond, T. C., Streets, D. G., Yarber, K. F., Nelson, S. M., Woo, J. H. Klimont, Z., 2004, A technology‐based global inventory of black and organic carbon emissions from combustion, Journal of Geophysical Research: Atmospheres, 109 (D14). https://doi.org/10.1029/2003JD003697
Bond, W. J. Keeley, J. E., 2005, Fire as a global ‘herbivore’: the ecology and evolution of flammable ecosystems, Trends in ecology & evolution, 20 (7): 387-394. https://doi.org/10.1016/j.tree.2005.04.025
Bowman, D. M., Balch, J. K., Artaxo, P., Bond, W. J., Carlson, J. M., Cochrane, M. A., D’Antonio, C. M., DeFries, R. S., Doyle, J. C. Harrison, S. P., 2009, Fire in the Earth system, Science, 324 (5926): 481-484. https://doi.org/10.1126/science.1163886
Brewer, C. K., J. Chris Winne, Roland L. Redmond, David W. Opitz Mangrich, M. V., 2005, Classifying and mapping wildfire severity: A comparison of methods, Photogrammetric Engineering & Remote Sensing, 71: 1311-1320. https://doi.org/10.14358/PERS.71.11.1311
Butler, B., Cohen, J., Latham, D., Schuette, R., Sopko, P., Shannon, K., Jimenez, D. Bradshaw, L., 2004, Measurements of radiant emissive power and temperatures in crown fires, Canadian Journal of Forest Research, 34 (8): 1577-1587. https://doi.org/10.1139/X04-060
Byram, G., 1959, Combustion of forest fuels. In ‘Forest fire: control and use’.(Ed. KP Davis) pp. 61–89, McGraw-Hill: New York.
Cansler, C. A. McKenzie, D., 2012, How robust are burn severity indices when applied in a new region? Evaluation of alternate field-based and remote-rensing methods, Remote Sensing, 4 (2): 456-483. https://doi.org/10.3390/rs4020456
Cardil, A., Mola-Yudego, B., Blazquez-Casado, A. Gonzalez-Olabarria, J. R., 2019, Fire and burn severity assessment: Calibration of Relative Differenced Normalized Burn Ratio (RdNBR) with field data, Journal of Environmental Management, 235: 342-349. https://doi.org/10.1016/j.jenvman.2019.01.077
Chen, X., Vogelmann, J. E., Rollins, M., Ohlen, D., Key, C. H., Yang, L., Huang, C. Shi, H., 2011, Detecting post- fire burn severity and vegetation recovery using multitemporal remote sensing spectral indices and field- collected composite burn index data in a ponderosa pine forest, International Journal of Remote Sensing, 32 (23): 7905-7927. https://doi.org/10.1080/01431161.2010.524678
Chuvieco, E., Riaño, D., Danson, F. M. Martin, P., 2006, Use of a radiative transfer model to simulate the postfire spectral response to burn severity, Journal of Geophysical Research: Biogeosciences, 111 (G4). https://doi.org/10.1029/2005JG00014
Chuvieco, E., Mouillot, F., van der Werf, G. R., San Miguel, J., Tanasse, M., Koutsias, N., García, M., Yebra, M., Padilla, M. Gitas, I., 2019, Historical background and current developments for mapping burned area from satellite Earth observation, Remote sensing of Environment, 225: 45-64. https://doi.org/10.1016/j.rse.2019.02.013
Cochrane, M. A. Ryan, K. C., 2009, Fire and fire ecology: Concepts and principles, In: Tropical Fire Ecology, Eds: Springer, p. 25-62. https://doi.org/10.1007/978-3-540-77381-8_2
Conard, S. G., Sukhinin, A. I., Stocks, B. J., Cahoon, D. R., Davidenko, E. P. Ivanova, G. A., 2002, Determining effects of area burned and fire severity on carbon cycling and emissions in Siberia, Climatic change, 55 (1- 2): 197-211. https://doi.org/10.1023/A:1020207710195
Cruz, M., Butler, B., Alexander, M., Forthofer, J. Wakimoto, R., 2006, Predicting the ignition of crown fuels above a spreading surface fire. Part I: Model idealization, International Journal of Wildland Fire, 15. https://doi.org/10.1071/WF04061
De Santis, A. Chuvieco, E., 2009, GeoCBI: a modified version of the Composite Burn Index for the initial assessment of the short-term burn severity from remotely sensed data, Remote sensing of Environment, 113 (3): 554-562. https://doi.org/10.1016/j.rse.2008.10.011
DeBano, L. F., Ffolliott, P. F. Baker, M. B., 1996, Fire severity effects on water resources, US Department of Agriculture, Forest Service, 77-84.
Dickinson, M. B. Johnson, E. A., 2001, Fire effects on trees, In: Forest fires, Eds: Elsevier, p. 477-525. https://doi.org/10.1016/B978-012386660-8/50016-7
Dickinson, M. B. Johnson, E. A., 2004, Temperature-dependent rate models of vascular cambium cell mortality, Canadian Journal of Forest Research, 34 (3): 546-559. https://doi.org/10.1139/X03-223
Epting, J., Verbyla, D. Sorbel, B., 2005, Evaluation of remotely sensed indices for assessing burn severity in interior Alaska using Landsat TM and ETM+, Remote sensing of Environment, 96 (3-4): 328-339. https://doi.org/10.1016/j.rse.2005.03.002
Fernández-Álvarez, M., Armesto, J. Picos, J., 2019, LiDAR-based wildfire prevention in WUI: The automatic detection, measurement and evaluation of forest fuels, Forests, 10 (2): 148. https://doi.org/10.3390/f10020148
Fernández-García, V., Santamarta, M., Fernández-Manso, A., Quintano, C., Marcos, E. Calvo, L., 2018, Burn severity metrics in fire-prone pine ecosystems along a climatic gradient using Landsat imagery, Remote sensing of Environment, 206: 205-217. https://doi.org/10.1016/j.rse.2017.12.029
Fernandez, C. Vega, J. A., 2018, Evaluation of the rusle and disturbed wepp erosion models for predicting soil loss in the first year after wildfire in NW Spain, Environmental Research, 165: 279-285. https://doi.org/10.1016/j.envres.2018.04.008
Frandsen, W. H. Ryan, K. C., 1986, Soil moisture reduces belowground heat flux and soil temperatures under a burning fuel pile, Canadian Journal of Forest Research, 16 (2): 244-248. https://doi.org/10.1139/x86-043
French, N. H., Kasischke, E. S., Hall, R. J., Murphy, K. A., Verbyla, D. L., Hoy, E. E. Allen, J. L., 2008, Using Landsat data to assess fire and burn severity in the North American boreal forest region: an overview and summary of results, International Journal of Wildland Fire, 17 (4): 443-462. https://doi.org/10.1071/WF08007
García-Llamas, P., Suárez-Seoane, S., Fernández-Guisuraga, J. M., Fernández-García, V., Fernández-Manso, A., Quintano, C., Taboada, A., Marcos, E. Calvo, L., 2019, Evaluation and comparison of Landsat 8, Sentinel-2 and Deimos-1 remote sensing indices for assessing burn severity in Mediterranean fire-prone ecosystems, International Journal of Applied Earth Observation and Geoinformation, 80: 137-144. https://doi.org/10.1016/j.jag.2019.04.006
Güney, C. O., 2022, Uydu görüntülerinden türetilen spektral indeksler kullanilarak orman ekosistemlerinde yanma derinliğinin tahmin edilmesi, Doktora, Isparta Uygulamalı Bilimler Üniversitesi, Lisansüstü Eğitim Enstitüsü, Isparta.
Güney, C. O., Sarı, A., Cekim, H. O., Küçüksille, E. U., Sentürk, Ö., Gülsoy, S. Özkan, K., 2022, An advanced approach for leaf flammability index estimation, International Journal of Wildland Fire, 31 (3): 277-290. https://doi.org/10.1071/WF21022
Hall, R. J., Freeburn, J. T., De Groot, W. J., Pritchard, J. M., Lynham, T. J. Landry, R., 2008, Remote sensing of burn severity: experience from western Canada boreal fires, International Journal of Wildland Fire, 17 (4): 476-489. https://doi.org/10.1071/WF08013 Heikkilä, T. V., Grönqvist, R. Jurvélius, M., 2010, Wildland fire management: handbook for trainers, Roma, İtaly, FAO.
Hoscilo, A., Tansey, K. J. Page, S. E., 2013, Post-fire vegetation response as a proxy to quantify the magnitude of burn severity in tropical peatland, International Journal of Remote Sensing, 34 (2): 412-433. https://doi.org/10.1080/01431161.2012.709328
Hudak, A. T., Morgan, P., Bobbitt, M. J., Smith, A. M. S., Lewis, S. A., Lentile, L. B., Robichaud, P. R., Clark, J. T.
McKinley, R. A., 2007, The relationship of multispectral satellite imagery to immediate fire effects, Fire ecology, 3 (1): 64-90. https://doi.org/10.4996/fireecology.0301064 Johnson, E. A. Miyanishi, K., 2001, Forest Fires: Behavior and Ecological Effects, Canada, Academic Press. https://doi.org/10.1016/B978-0-123-86660-8.X5000-4
Keeley, J. E. Zedler, P. H., 1998, Evolution of life histories in Pinus, In: Ecology and biogeography of Pinus, Eds: Richardson, D. M., Cambridge, United Kingdom: Cambridge University Press, p. 219-250.
Keeley, J. E. Fotheringham, C. J., 2000, Role of fire in regeneration from seed, Seeds: the ecology of regeneration in plant communities, 2: 311-330. Keeley, J. E., 2009, Fire intensity, fire severity and burn severity: a brief review and suggested usage, International Journal of Wildland Fire, 18 (1): 116-126. https://doi.org/10.1071/WF07049
Key, C. H. Benson, N. C., 1999, Measuring and remote sensing of burn severity. Proceedings Joint Fire Science Conference and Workshop. Idaho, USA, University of Idaho and International Association of Wildland Fire Moscow, ID. 2: 284.
Key, C. H., 2006, Ecological and sampling constraints on defining landscape fire severity, Fire ecology, 2 (2): 34-59. https://doi.org/10.4996/fireecology.0202034
Key, C. H. Benson, N. C., 2006, Landscape assessment (LA), In: In: Lutes, Duncan C.; Keane, Robert E.; Caratti, John F.; Key, Carl H.; Benson, Nathan C.; Sutherland, Steve; Gangi, Larry J. 2006. FIREMON: Fire effects monitoring and inventory system. Gen. Tech. Rep. RMRS-GTR-164-CD. Fort Collins, CO: US Department of Agriculture, Forest Service, Rocky Mountain Research Station. p. LA-1-55, Eds, p. https://doi.org/10.2737/RMRS-GTR-164
Küçük, Ö., 2009, Yangın Ekolojisi, I.Orman Yangınları ile Mücadele Sempozyumu, 07-10 Ocak 2009, Antalya. Lasaponara, R. Tucci, B., 2019, Identification of burned areas and severity using SAR Sentinel-1. IEEE Geoscience and Remote Sensing Letters. 16: 917-921.
Lentile, L. B., Holden, Z. A., Smith, A. M., Falkowski, M. J., Hudak, A. T., Morgan, P., Lewis, S. A., Gessler, P. E. Benson, N. C., 2006, Remote sensing techniques to assess active fire characteristics and post-fire effects, International Journal of Wildland Fire, 15 (3): 319-345. https://doi.org/10.1071/WF05097
Lentile, L. B., Morgan, P., Hudak, A. T., Bobbitt, M. J., Lewis, S. A., Smith, A. M. S. Robichaud, P. R., 2007, Post- fire burn severity and vegetation response following eight large wildfires across the Western United States, Fire ecology, 3 (1): 91-108. https://doi.org/10.4996/fireecology.0301091
Liu, Z. Wimberly, M. C., 2015, Climatic and landscape influences on fire regimes from 1984 to 2010 in the western United States, PLoS One, 10 (10): e0140839. https://doi.org/10.1371/journal.pone.0140839
Mallinis, G., Mitsopoulos, I. Chrysafi, I., 2018, Evaluating and comparing Sentinel 2A and Landsat-8 Operational Land Imager (OLI) spectral indices for estimating fire severity in a Mediterranean pine ecosystem of Greece, GIScience & Remote Sensing, 55 (1): 1-18. https://doi.org/10.1080/15481603.2017.1354803 Mauri, E. Pons, P., 2019, Handbook of good practices in post-wildfire management, 2nd ed., Anifog Project I+D+i CGL2014-54094-R, Spain, Universitat de Girona.
Michaletz, S. T. Johnson, E. A., 2006, A heat transfer model of crown scorch in forest fires, Canadian Journal of Forest Research, 36 (11): 2839-2851. https://doi.org/10.1139/X06-158
Michaletz, S. T. Johnson, E. A., 2007, How forest fires kill trees: a review of the fundamental biophysical processes, Scandinavian Journal of Forest Research, 22 (6): 500-515. https://doi.org/10.1080/02827580701803544
Miller, J. D. Thode, A. E., 2007, Quantifying burn severity in a heterogeneous landscape with a relative version of the delta Normalized Burn Ratio (dNBR), Remote sensing of Environment, 109 (1): 66-80. https://doi.org/10.1016/j.rse.2006.12.006
Miller, J. D. Quayle, B., 2015, Calibration and validation of immediate post-fire satellite-derived data to three severity metrics, Fire ecology, 11 (2). https://doi.org/10.4996/fireecology.1102012
Miranda, A., Amorim, J. H., Valente, J., Monteiro, A., Ferreira, J. Borrego, C., 2014, Forest fires effects on the atmosphere: 20 years of research in Portugal, In: Advances in forest fire research, Eds: viegas, D. X.: Imprensa da Universidade de Coimbra, p. 283-297. https://doi.org/10.14195/978-989-26-0884-6_30
Montealegre, A. L., Lamelas, M. T., Tanase, M. A. de la Riva, J., 2014, Forest fire severity assessment using ALS data in a Mediterranean environment, Remote Sensing, 6 (5): 4240-4265. https://doi.org/10.3390/rs6054240
Morgan, P., Hardy, C. C., Swetnam, T. W., Rollins, M. G. ve Long, D. G., 2001, Mapping fire regimes across time and space: understanding coarse and fine-scale fire patterns, International Journal of Wildland Fire, 10 (4), 329-342.
Morgan, P., Keane, R. E., Dillon, G. K., Jain, T. B., Hudak, A. T., Karau, E. C., Sikkink, P. G., Holden, Z. A. Strand, E. K., 2014, Challenges of assessing fire and burn severity using field measures, remote sensing and modelling, International Journal of Wildland Fire, 23 (8): 1045-1060. https://doi.org/10.1071/WF13058
Neary, D. G., Ryan, K. C. DeBano, L. F., 2005, Wildland Fire in Ecosystems: Effects of Fire on Soils and Water, Gen. Tech. Rep. RMRS-GTR-42-vol. 4. Ogden, UT: US Department of Agriculture, Forest Service, Rocky Mountain Research Station. https://doi.org/10.2737/RMRS-GTR-42-V4
Packham, D. R. Pompe, A., 1971, Radiation temperatures of forest fires, Australian Forest Research, 5 (3): 1-8.
Parker, B. M., Lewis, T. Srivastava, S. K., 2015, Estimation and evaluation of multi-decadal fire severity patterns using Landsat sensors, Remote sensing of Environment, 170: 340-349. https://doi.org/10.1016/j.rse.2015.09.014
Parks, S. A., Dillon, G. K. Miller, C., 2014, A new metric for quantifying burn severity: the relativized burn ratio, Remote Sensing, 6 (3): 1827-1844. https://doi.org/10.3390/rs6031827
Pausas, J. G. Keeley, J. E., 2009, A burning story: the role of fire in the history of life, BioScience, 59 (7): 593- 601. https://doi.org/10.1525/bio.2009.59.7.10
Pleniou, M. Koutsias, N., 2013, Sensitivity of spectral reflectance values to different burn and vegetation ratios: A multi-scale approach applied in a fire affected area, ISPRS Journal of Photogrammetry and Remote Sensing, 79: 199-210. https://doi.org/10.1016/j.isprsjprs.2013.02.016
Roberts, S. L., van Wagtendonk, J. W., Miles, A. K., Kelt, D. A. Lutz, J. A., 2008, Modeling the effects of fire severity and spatial complexity on small mammals in Yosemite National Park, California, Fire ecology, 4 (2): 83-104. https://doi.org/10.4996/fireecology.0402083
Ryan, K. C. Noste, N. V., 1985, Evaluating prescribed fires, in: JE Lotan et al.(tech. coor), Proceedings – Symposium and Workshop on Wilderness Fire, USDA Forest Service Intermountain Forest and Range Experiement Station, General Technical Report INT-182.Utah State University, 230-238.
Ryan, K. C. Frandsen, W. H., 1991, Basal injury from smoldering fires in mature Pinus ponderosa Laws, International Journal of Wildland Fire, 1 (2): 107-118. https://doi.org/10.1071/WF9910107
Ryan, K. C., 2002, Dynamic interactions between forest structure and fire behavior in boreal ecosystems,Silva Fennica, 36 (1): 13-39. https://doi.org/10.14214/sf.548
Ryan, K. C., Jones, A. T., Koerner, C. L. Lee, K. M., 2012, Wildland Fire in Ecosystems: Effects of Fire on Cultural Resources and Archaeology, Gen. Tech. Rep. RMRS-GTR-42-vol. 3. Fort Collins, CO: US Department of Agriculture, Forest Service, Rocky Mountain Research Station. 224 p. https://doi.org/10.2737/RMRS-GTR- 42
Sandberg, D. V., 2009, Wildland fire in ecosystems: effects of fire on air, Gen. Tech. Rep. RMRS-GTR-42-vol. 5. Ogden, UT: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. https://doi.org/10.2737/RMRS-GTR-42-V5
Satio, K., 2001, Flames, In: In: Forest Fires Behavior and Ecological Effects, Eds: Johnson, E. A. M., K., eds. San Diego: Academic Press, p. 11-54.
Saulino, L., Rita, A., Migliozzi, A., Maffei, C., Allevato, E., Garonna, A. P. Saracino, A., 2020, Detecting burn severity across Mediterranean forest types by coupling medium-spatial resolution satellite imagery and field data, Remote Sensing, 12 (4). https://doi.org/10.3390/rs12040741 Simard, S. J., 1991, Fire severity, changing scales, and how things hang together, International Journal of Wildland Fire, 1 (1): 23-34. https://doi.org/10.1071/WF9910023
Skowronski, N. S., Gallagher, M. R. Warner, T. A., 2020, Decomposing the interactions between fire severity and canopy fuel structure using multi-temporal, active, and passive remote sensing approaches, Fire, 3 (1). https://doi.org/10.3390/fire3010007
Smith, J. K., 1997, Fire Ecology of The Forest Habitat Types of Northern Idaho, General Technical Report INT-GTR-363, vol.363, US Department of Agriculture, Forest Service, Intermountain Research Station. https://doi.org/10.2737/INT-GTR-363
Smith, J. K., Lyon, L. J., Huff, M., Hooper, R., Telfer, E. Schreiner, D., 2000, Wildland Fire in Ecosystems. Effects of Fire on Fauna, General Technical Report, RMRS-GTR-42. Rocky Mountain Research Station, USDA Forest Service.
Soverel, N. O., Perrakis, D. D. B. Coops, N. C., 2010, Estimating burn severity from Landsat dNBR and RdNBR indices across western Canada, Remote sensing of Environment, 114 (9): 1896-1909. https://doi.org/10.1016/j.rse.2010.03.013
Stocks, B. J., Lynham, T., Lawson, B., Alexander, M., Wagner, C. V., McAlpine, R. Dube, D., 1989, Canadian forest fire danger rating system: an overview, The Forestry Chronicle, 65 (4): 258-265.
Szpakowski, D. Jensen, J., 2019, A review of the applications of remote sensing in fire ecology, Remote Sensing, 11 (22). https://doi.org/10.3390/rs11222638
Tanase, M., Kennedy, R. Aponte, C., 2015a, Radar Burn Ratio for fire severity estimation at canopy level: An example for temperate forests, Remote sensing of Environment, 170: 14-31.
Tanase, M. A., Kennedy, R. Aponte, C., 2015b, Fire severity estimation from space: a comparison of active and passive sensors and their synergy for different forest types, International Journal of Wildland Fire, 24 (8). https://doi.org/10.1071/wf15059 Turner, M. G., Baker, W. L., Peterson, C. J. Peet, R. K., 1998, Factors influencing succession: Lessons from large, infrequent natural disturbances, Ecosystems, 1 (6): 511-523. https://doi.org/10.1007/s100219900047
Valor, T., González-Olabarria, J. R., Piqué, M. Casals, P., 2017, The effects of burning season and severity on the mortality over time of Pinus nigra spp. salzmannii (Dunal) Franco and P. sylvestris L, Forest Ecology and Management, 406: 172-183. https://doi.org/10.1016/j.foreco.2017.08.027
Veraverbeke, S., Lhermitte, S., Verstraeten, W. W. Goossens, R., 2011, Evaluation of pre/post-fire differenced spectral indices for assessing burn severity in a Mediterranean environment with Landsat Thematic Mapper, International Journal of Remote Sensing, 32 (12): 3521-3537. https://doi.org/10.1080/01431161003752430
Veraverbeke, S. Hook, S. J., 2013, Evaluating spectral indices and spectral mixture analysis for assessing fire severity, combustion completeness and carbon emissions, International Journal of Wildland Fire, 22 (5). https://doi.org/10.1071/wf12168
Verbyla, D. L., Kasischke, E. S. Hoy, E. E., 2008, Seasonal and topographic effects on estimating fire severity from Landsat TM/ETM+ data, International Journal of Wildland Fire, 17 (4): 527-534. https://doi.org/10.1071/WF08038
Vieira, D. C. S., Fernández, C., Vega, J. A. Keizer, J. J., 2015, Does soil burn severity affect the post-fire runoff and interrill erosion response? A review based on meta-analysis of field rainfall simulation data, Journal of Hydrology, 523: 452-464. https://doi.org/10.1016/j.jhydrol.2015.01.071
Wang, C. Glenn, N. F., 2009, Estimation of fire severity using pre- and post-fire LiDAR data in sagebrush steppe rangelands, International Journal of Wildland Fire, 18 (7). https://doi.org/10.1071/wf08173
Wells, C. G., Campbell, R. E., DeBano, L. F., Lewis, C. E., Fredriksen, R. L., Franklin, E. C., Froelich, R. C. Dunn, P. H., 1979, Effects of Fire On Soil: A State-of-Knowledge Review, Denver, Colorado, US Department of Agriculture, Forest Service.
Whelan, R. J., 1995, The ecology of fire, Cambridge university press, p.
White, J. D., Ryan, K. C., Key, C. C. Running, S. W., 1996, Remote sensing of forest fire severity and vegetation recovery, International Journal of Wildland Fire, 6 (3): 125-136. https://doi.org/10.1071/WF9960125
White, P. S. Pickett, S. T. A., 1985, Natural Disturbance and Patch Dynamics: An Introduction, In: Pickett, S.T.A., White, Peter S., The Ecology of Natural Disturbance and Patch Dynamics, Eds: Academic Press, p. 313. https://doi.org/10.1016/C2009-0-02952-3
Willard, E. E., Wakimoto, R. H. Ryan, K. C., 1995, Vegetation Recovery in Sedge Meadow Communities Within the Red Bench Fire, Glacier National Park, Fire in wetlands: a management perspective. Proceedings of the Tall Timbers Fire Ecology Conference, No. 19., Tall Timbers Research Station, Tallahassee, FL., 102-110.
URL 1, 2022, Wildfire Rank-Province of British Columbia, https://www2.gov.bc.ca/gov/content/safety/wildfire-status/wildfire-response/about-wildfire/wildfire- rank: Son Erişim Tarihi: 26.10.2022.

Toplam 90 adet kaynakça vardır.

Ayrıntılar

Birincil Dil	Türkçe
Konular	Mühendislik
Bölüm	Makaleler
Yazarlar	Coşkun Okan Güney 0000-0003-4664-8024 Ahmet Mert 0000-0001-6859-0308 Serkan Gülsoy 0000-0003-2011-8324
Yayımlanma Tarihi	31 Mart 2023
Kabul Tarihi	7 Mart 2023
Yayımlandığı Sayı	Yıl 2023 Cilt: 6 Sayı: 1

Kaynak Göster

APA	Güney, C. O., Mert, A., & Gülsoy, S. (2023). Orman Yangınları Sonrası Ekosistem Tabanlı Planlamaya Doğru: Yanma Derinliğinin Sınıflandırılması. Afet Ve Risk Dergisi, 6(1), 206-225. https://doi.org/10.35341/afet.1197031
AMA	Güney CO, Mert A, Gülsoy S. Orman Yangınları Sonrası Ekosistem Tabanlı Planlamaya Doğru: Yanma Derinliğinin Sınıflandırılması. Afet ve Risk Dergisi. Mart 2023;6(1):206-225. doi:10.35341/afet.1197031
Chicago	Güney, Coşkun Okan, Ahmet Mert, ve Serkan Gülsoy. “Orman Yangınları Sonrası Ekosistem Tabanlı Planlamaya Doğru: Yanma Derinliğinin Sınıflandırılması”. Afet Ve Risk Dergisi 6, sy. 1 (Mart 2023): 206-25. https://doi.org/10.35341/afet.1197031.
EndNote	Güney CO, Mert A, Gülsoy S (01 Mart 2023) Orman Yangınları Sonrası Ekosistem Tabanlı Planlamaya Doğru: Yanma Derinliğinin Sınıflandırılması. Afet ve Risk Dergisi 6 1 206–225.
IEEE	C. O. Güney, A. Mert, ve S. Gülsoy, “Orman Yangınları Sonrası Ekosistem Tabanlı Planlamaya Doğru: Yanma Derinliğinin Sınıflandırılması”, Afet ve Risk Dergisi, c. 6, sy. 1, ss. 206–225, 2023, doi: 10.35341/afet.1197031.
ISNAD	Güney, Coşkun Okan vd. “Orman Yangınları Sonrası Ekosistem Tabanlı Planlamaya Doğru: Yanma Derinliğinin Sınıflandırılması”. Afet ve Risk Dergisi 6/1 (Mart 2023), 206-225. https://doi.org/10.35341/afet.1197031.
JAMA	Güney CO, Mert A, Gülsoy S. Orman Yangınları Sonrası Ekosistem Tabanlı Planlamaya Doğru: Yanma Derinliğinin Sınıflandırılması. Afet ve Risk Dergisi. 2023;6:206–225.
MLA	Güney, Coşkun Okan vd. “Orman Yangınları Sonrası Ekosistem Tabanlı Planlamaya Doğru: Yanma Derinliğinin Sınıflandırılması”. Afet Ve Risk Dergisi, c. 6, sy. 1, 2023, ss. 206-25, doi:10.35341/afet.1197031.
Vancouver	Güney CO, Mert A, Gülsoy S. Orman Yangınları Sonrası Ekosistem Tabanlı Planlamaya Doğru: Yanma Derinliğinin Sınıflandırılması. Afet ve Risk Dergisi. 2023;6(1):206-25.

Kapak Resmi İndir

Makale Dosyaları

Tam Metin