Exploring the relationship between burn severity field data and very high resolution GeoEye images: The Case of the 2011 Evros wildfire in Greece

Remote Sensing

Volumn 8, Issue 7, 2016, Pages

  Dragozi, Eleni ^a   Gitas, Ioannis Z ^a   Bajocco, Sofia ^b   Stavrakoudis, Dimitris G ^a  

^a ARISTOTLE UNIVERSITY OF THESSALONIKI   (Greece)

^b ISTITUTO NAZIONALE DELLA NUTRIZIONE   (Italy)

Author keywords

Burn severity; Composite Burn Index (CBI); Post fire dynamics; Redundancy analysis

Indexed keywords

DEFORESTATION; DYNAMICS; FIRE HAZARDS; REDUNDANCY; REMOTE SENSING; SATELLITE IMAGERY; VEGETATION;

BURN SEVERITY; COMPOSITE BURN INDICES; NORMALIZED DIFFERENCE VEGETATION INDEX; POST-FIRE; REDUNDANCY ANALYSIS; REDUNDANCY ANALYSIS (RDA); REMOTELY SENSED IMAGES; TOPOGRAPHIC CONDITIONS;

FIRES;

EID: 85010407312     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs8070566     Document Type: Letter

References (55)

1. Moreira, F.; Viedma, O.; Arianoutsou, M.; Curt, T.; Koutsias, N.; Rigolot, E.; Barbati, A.; Corona, P.; Vaz, P.; Xanthopoulos, G. Landscape-wildfire interactions in southern Europe: Implications for landscape management. J. Environ. Manag. 2011, 92, 2389-2402.
2. Hoscilo, A.; Tansey, K.J.; Page, S.E. Post-fire vegetation response as a proxy to quantify the magnitude of burn severity in tropical peatland. Int. J. Remote Sens. 2013, 34, 412-433.
3. 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. Remote sensing techniques to assess active fire characteristics and post-fire effects. Int. J. Wildland Fire 2006, 15, 319-345.
4. Gouveia, C.; DaCamara, C.; Trigo, R. Post-fire vegetation recovery in Portugal based on spot/vegetation data. Nat. Hazards Earth Syst. Sci. 2010, 10, 673-684.
5. Chen, X.; Vogelmann, J.E.; Rollins, M.; Ohlen, D.; Key, C.H.; Yang, L.; Huang, C.; Shi, H. 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. Int. J. Remote Sens. 2011, 32, 7905-7927.
6. FAO. State of the World's Forests-2014; FAO: Rome, Italy, 2014.
7. Gitas, I.; Polychronaki, A.; Mitri, G.; Veraverbeke, S. Advances in Remote Sensing of Post-Fire Vegetation Recovery Monitoring-A Review; InTech: Vienna, Austria, 2012.
8. Key, C.H.; Benson, N.C. Landscape assessment (LA). FIREMON: Fire Effects Monitoring and Inventory System; General Technical Report RMRS-GTR-164-CD. Rocky Mountain Research Station, US Department of Agriculture, Forest Service: Fort Collins, CO, USA, 2006; pp. LA-1-LA-51.
9. Birch, D.S.; Morgan, P.; Kolden, C.A.; Abatzoglou, J.T.; Dillon, G.K.; Hudak, A.T.; Smith, A.M. Vegetation, topography and daily weather influenced burn severity in central Idaho and western Montana forests. Ecosphere 2015, 6, 1-23.
10. Naveh, Z. Mediterranean uplands as anthropogenic perturbation dependent systems and their dynamic conservation management. In Terrestrial and Aquatic Ecosystems, Perturbation and Recovery; Ellis Horwood: New York, NY, USA, 1991; pp. 544-556.
11. Ryan, K.C. Dynamic interactions between forest structure and fire behavior in boreal ecosystems. Silva Fenn. 2002, 36, 13-39.
12. Schepers, L.; Haest, B.; Veraverbeke, S.; Spanhove, T.; Vanden Borre, J.; Goossens, R. Burned area detection and burn severity assessment of a heathland fire in Belgium using Airborne Imaging Spectroscopy (APEX). Remote Sens. 2014, 6, 1803-1826.
13. Ireland, G.; Petropoulos, G.P. Exploring the relationships between post-fire vegetation regeneration dynamics, topography and burn severity: A case study from the Montane Cordillera Ecozones of Western Canada. Appl. Geogr. 2015, 56, 232-248.
14. Catry, F.; Rego, F.; Moreira, F.; Fernandes, P.; Pausas, J. Post-fire tree mortality in mixed forests of central Portugal. For. Ecol. Manag. 2010, 260, 1184-1192.
15. Driscoll, D.A.; Lindenmayer, D.B.; Bennett, A.F.; Bode, M.; Bradstock, R.A.; Cary, G.J.; Clarke, M.F.; Dexter, N.; Fensham, R.; Friend, G. Fire management for biodiversity conservation: Key research questions and our capacity to answer them. Biol. Conserv. 2010, 143, 1928-1939.
16. Moreira, F.; Arianoutsou, M.; Vallejo, V.R.; de las Heras, J.; Corona, P.; Xanthopoulos, G.; Fernandes, P.; Papageorgiou, K. Setting the scene for post-fire management. In Post-Fire Management and Restoration of Southern European Forests; Springer: Berlin, Germany; Heidelberg, Germany, 2012; pp. 1-19.
17. Viedma, O.; Quesada, J.; Torres, I.; De Santis, A.; Moreno, J.M. Fire severity in a large fire in a Pinus pinaster forest is highly predictable from burning conditions, stand structure, and topography. Ecosystems 2014, 18, 237-250.
18. 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. Challenges of assessing fire and burn severity using field measures, remote sensing and modelling. Int. J. Wildland Fire 2014, 23, 1045-1060.
19. Karaman, M.; Özelkan, E.; örmeci, C. Determination of the forest fire potential by using remote sensing and geographical information system, case study-Bodrum/Turkey. In Advances in Remote Sensing and GIS Applications in Forest Fire Management From Local to Global Assessments; Publications office of the European Union: Stressa, Italy, 2011; pp. 51-55.
20. Collins, B.M.; Kelly, M.; van Wagtendonk, J.W.; Stephens, S.L. Spatial patterns of large natural fires in Sierra Nevada wilderness areas. Landsc. Ecol. 2007, 22, 545-557.
21. Turner, M.G.; Hargrove,W.W.; Gardner, R.H.; Romme,W.H. Effects of fire on landscape heterogeneity in Yellowstone National Park,Wyoming. J. Veg. Sci. 1994, 731-742.
22. Pinto, A.; Fernandes, P.M. Microclimate and modeled fire behavior differ between adjacent forest types in Northern Portugal. Forests 2014, 5, 2490-2504.
23. Boiffin, J.; Aubin, I.; Munson, A.D. Ecological controls on post-fire vegetation assembly at multiple spatial scales in eastern North American boreal forests. J. Veg. Sci. 2014.
24. Mouillot, F.; Ratte, J.-P.; Joffre, R.; Mouillot, D.; Rambal, S. Long-term forest dynamic after land abandonment in a fire prone Mediterranean landscape (central Corsica, France). Landsc. Ecol. 2005, 20, 101-112.
25. Key, C.; Benson, N. Measuring and remote sensing of burn severity. In Proceedings of the Joint Fire Science Conference and Workshop, Boise, Idaho, 15-17 June 1999; p. 284.
26. Key, C.; Benson, N. FIREMON: Fire Effects Monitoring and Inventory System; USDA Forest Service, Rocky Mountain Research Station: Fort Collins, CO, USA, 2006.
27. Chuvieco, E. Earth Observation of Wildland Fires in Mediterranean Ecosystems; Springer: Berlin/Heidelberg, Germany, 2009.
28. Keeley, J.E. Fire intensity, fire severity and burn severity: A brief review and suggested usage. Int. J. Wildland Fire 2009, 18, 116-126.
29. Mitri, G.H.; Gitas, I.Z. Mapping the severity of fire using object-based classification of IKONOS imagery. Int. J. Wildland Fire 2008, 17, 431-442.
30. Amato, V.J.; Lightfoot, D.; Stropki, C.; Pease, M. Relationships between tree stand density and burn severity as measured by the Composite Burn Index following a ponderosa pine forest wildfire in the American Southwest. For. Ecol. Manag. 2013, 302, 71-84.
31. Chen, G.; Metz, M.R.; Rizzo, D.M.; Dillon,W.W.; Meentemeyer, R.K. Object-based assessment of burn severity in diseased forests using high-spatial and high-spectral resolution MASTER airborne imagery. ISPRS J. Photogramm. Remote Sens. 2015, 102, 38-47.
32. Keane, R.E.; Dillon, G.; Jain, T.; Hudak, A.; Morgan, P.; Karau, E.; Sikkink, P.; Silverstein, R. The Problems with Fire Severity and Its Application in Fire Management; USDA Forest Service, Rocky Mountain Research Station: Missoula, MT, Canada, 2012.
33. Díaz-Delgado, R.; Lloret, F.; Pons, X. Influence of fire severity on plant regeneration by means of remote sensing imagery. Int. J. Remote Sens. 2003, 24, 1751-1763.
34. Edwards, A.C.; Maier, S.W.; Hutley, L.B.; Williams, R.J.; Russell-Smith, J. Spectral analysis of fire severity in north Australian tropical savannas. Remote Sens. Environ. 2013, 136, 56-65.
35. Dzwonko, Z.; Loster, S.; Gawrónski, S. Impact of fire severity on soil properties and the development of tree and shrub species in a Scots pine moist forest site in southern Poland. For. Ecol. Manag. 2015, 342, 56-63.
36. Wang, G.G.; Kemball, K.J. The effect of fire severity on early development of understory vegetation following a stand-replacing wildfire. In Proceedings of the 5th Symposium on Fire and Forest Meteorology Jointly with 2nd InternationalWildland Fire Ecology and Fire Management Congress, Orlando, FL, USA, 16-20 November 2003; pp. 16-20.
37. Johnstone, J.F.; Chapin, F.S., III. Effects of soil burn severity on post-fire tree recruitment in boreal forest. Ecosystems 2006, 9, 14-31.
38. Blaschke, T.; Hay, G.J.; Kelly, M.; Lang, S.; Hofmann, P.; Addink, E.; Feitosa, R.Q.; van der Meer, F.; van derWerff, H.; van Coillie, F. Geographic object-based image analysis-Towards a new paradigm. ISPRS J. Photogramm. Remote Sens. 2014, 87, 180-191.
39. Cansler, C.A.; McKenzie, D. How robust are burn severity indices when applied in a new region? Evaluation of alternate field-based and remote-sensing methods. Remote Sens. 2012, 4, 456-483.
40. Demirel, N.; Emil, M.K.; Duzgun, H.S. Surface coal mine area monitoring using multi-temporal high-resolution satellite imagery. Int. J. Coal Geol. 2011, 86, 3-11.
41. Epting, J.; Verbyla, D. Landscape-level interactions of prefire vegetation, burn severity, and postfire vegetation over a 16-year period in interior Alaska. Can. J. For. Res. 2005, 35, 1367-1377.
42. Tucker, C.J. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens. Environ. 1979, 8, 127-150.
43. Casady, G.M.; van Leeuwen,W.J.; Marsh, S.E. Evaluating post-wildfire vegetation regeneration as a response to multiple environmental determinants. Environ. Model. Assess. 2010, 15, 295-307.
44. Wu, Z.; Middleton, B.; Hetzler, R.; Vogel, J.; Dye, D. Vegetation burn severity mapping using Landsat-8 and WorldView-2. Photogramm. Eng. Remote Sens. 2015, 81, 143-154.
45. Deng, Y.; Goodchild, M.F.; Chen, X. Using NDVI to define thermal south in several mountainous landscapes of California. Comput. Geosci. 2009, 35, 327-336.
46. Wimberly, M.C.; Reilly, M.J. Assessment of fire severity and species diversity in the southern Appalachians using Landsat TM and ETM+ imagery. Remote Sens. Environ. 2007, 108, 189-197.
47. Dillon, G.K.; Holden, Z.A.; Morgan, P.; Crimmins, M.A.; Heyerdahl, E.K.; Luce, C.H. Both topography and climate affected forest and woodland burn severity in two regions of the western US, 1984 to 2006. Ecosphere 2011, 2, 1-33.
48. Rao, C.R. The use and interpretation of principal component analysis in applied research. In Sankhya: The Indian Journal of Statistics, Series A; Springer: Berlin, Germany; Heidelberg, Germany, 1964; pp. 329-358.
49. Legendre, P.; Legendre, L.F. Numerical Ecology; Elsevier: Amsterdam, The Netherlands, 2012.
50. Legendre, P.; Oksanen, J.; ter Braak, C.J. Testing the significance of canonical axes in redundancy analysis. Methods Ecol. Evol. 2011, 2, 269-277.
51. Gittins, R. Canonical Analysis: A Review with Applications in Ecology; Springer: Berlin, Germany; Heidelberg, Germany, 1985.
52. Van den Brink, P.J.; ter Braak, C.J. Principal response curves: Analysis of time-dependent multivariate responses of biological community to stress. Environ. Toxicol. Chem. 1999, 18, 138-148.
53. Bajocco, S.; Rosati, L.; Ricotta, C. Knowing fire incidence through fuel phenology: A remotely sensed approach. Ecol. Model. 2010, 221, 59-66.
54. Ter Braak, C.J.; Prentice, I.C. A theory of gradient analysis. Adv. Ecol. Res. 1988, 18, 271-317.
55. Legendre, P.; Legendre, L. Numerical Ecology, 2nd ed.; Elsevier: Amsterdam, The Netherlands, 1998.