A time-integrated MODIS burn severity assessment using the multi-temporal differenced normalized burn ratio (dNBRMT)

International Journal of Applied Earth Observation and Geoinformation

Volumn 13, Issue 1, 2011, Pages 52-58

  Veraverbeke, S ^a   Lhermitte, S ^b   Verstraeten, W ^c   Goossens, R ^a  

^a GHENT UNIVERSITY   (Belgium)

^b DEPARTAMENTO DE BIOLOGÍA   (Chile)

^c UNIVERSITY OF LEUVEN   (Belgium)

Author keywords

Burn severity; Composite burn index; Differenced normalized burn ratio; Fire severity; Landsat Thematic Mapper; MODIS; Multi temporal; Vegetation regeneration

Indexed keywords

CORRELATION; ECOSYSTEM RESPONSE; FIRE MANAGEMENT; IMAGE ANALYSIS; IMAGE RESOLUTION; LANDSAT THEMATIC MAPPER; MODIS; PIXEL; REGRESSION ANALYSIS; REMOTE SENSING; TEMPORAL ANALYSIS; VEGETATION; WILDFIRE;

EID: 79952735408     PISSN: 15698432     EISSN: 1872826X     Source Type: Journal    
DOI: 10.1016/j.jag.2010.06.006     Document Type: Article

References (40)

1. Allen, J., Sorbel, B., 2008. Assessing the differenced normalized burn ratio's ability to map burn severity in the boreal forest and tundra ecosystems of Alaska's national parks. Int. J. Wildland Fire 17, 463-475.
2. Amiro, B., Barr, A., Black, T., Iwashita, H., Kljun, N., McCaughey, J., Morgenstern, K., Muruyama, S., Nesic, Z., Orchansky, A., Saigusa, N., 2006. Carbon, energy and water fluxes at mature and disturbed forest sites, Saskatchewan, Canada. Agric. Forest Meteorol. 136, 237-251.
3. Capitaino, R., Carcaillet, C., 2008. Post-fire Mediterranean vegetation dynamics and diversity: a discussion of succession models. Forest Ecol. Manage. 255, 431-439.
4. Chafer, C., 2008. A comparison of fire severity measures: an Australian example and implications for predicting major areas of soil erosion. Catena 74, 235-245.
5. Chander, G., Markham, L., Barsi, J., 2007. Revised Landsat-5 Thematic Mapper radio-metric calibration. IEEE Geosci. Remote Sens. Lett. 4, 490-494.
6. Chavez, P., 1996. Image-based atmospheric corrections-revisited and improved. Photogramm. Eng. Remote Sens. 6, 1025-1036.
7. Chuvieco, E., Ventura, G., Martin, P., Gomez, I., 2005. Assessment of multitemporal compositing techniquesof MODIS and AVHRR images for burned land mapping. Remote Sens. Environ. 94, 450-462.
8. Coppin, P., Jonckheere, I., Nackaerts, K., Muys, B., 2004. Digital change detection techniques in ecosystem monitoring: a review. Int. J. Remote Sens. 25, 1565-1595.
9. 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 Sens. Environ. 113, 554-562.
10. Eidenshink, J., Schwind, B., Brewer, K., Zhu, Z., Quayle, B., Howard, S., 2007. A project for monitoring trends in burn severity. Fire Ecol. 3, 3-21.
11. Epting, J., Verbyla, D., 2005. Landscape-level interactions of prefire vegetation, burn severity, and postfire vegetation over a 16-year period in interior Alaska. Can. J. Forest Res. 35, 1367-1377.
12. French, N., Kasischke, E., Hall, R., Murphy, K., Verbyla, D., Hoy, E., Allen, J., 2008. Using Landsat datato assess fire and burn severityin the North American boreal forest region: an overview and summary of results. Int. J. Wildland Fire 17, 443-462.
13. Garmin, 2005. Garmin eTrex Vista Personal Navigator. Owner's Manual and Reference Guide, Available from: http://buy.garmin.com/shop/store/manual.jsp?product=010-00243-00&cID=167&pID=163 (Last visited on 22/04/2010).
14. Heumann, B., Seaquist, J., Eklundh, L., Jonsson, P., 2007. AVHRR derived phenological change in the Sahel and Soudan, Africa, 1982-2005. Remote Sens. Environ. 108, 385-392.
15. Hilker, T., Wulder, M., Coops, N., Linke, J., McDermid, G., Masek, J., Gao, F., White, J., 2009. A new data fusion model for high spatial- and temporal-resolution mapping of forest disturbance based on Landsat and MODIS. Remote Sens. Environ. 113, 1623-1627.
16. Holben, B., 1986. Characteristics of maximum-value composite images from temporal AVHRR data. Int. J. Remote Sens. 7, 1417-1434.
17. Jain, T., Pilliod, D., Graham, R., 2004. Tongue-tied. Wildfire 4, 22-26.
18. Jarvis, A., Reuter, H., Nelson, A., Guevara, E., 2006. Hole-filled Seamless SRTM Data V3, Available from: http://srtm.csi.cgiar.org (Last visited on 22/04/2010).
19. Jonsson, P., Eklundh, L., 2004. TIMESAT-a program for analyzing time-series of satellite sensor data. Comput. Geosci. 30, 833-845.
20. Ju, J., Roy, D., 2008. The availability of cloud-free Landsat ETM+ data over the conterminous United States and globally. Remote Sens. Environ. 112, 1196-1211.
21. Keeley, J., 2009. Fire intensity, fire severity and burn severity: a brief review and suggested usage. Int. J. Wildland Fire 18, 116-126.
22. Key, C., Benson, N., 2005. Landscape assessment: ground measure of severity; the composite burn index, and remote sensing of severity, the normalized burn index. In: Lutes, D., Keane, R., Caratti, J., Key, C., Benson, N., Sutherland, S., Gangi, L. (Eds.), FIREMON: Fire Effects Monitoring and Inventory System. USDA Forest Service, Rocky Mountains Research Station, General Technical Report RMRS-GTR-164-CD LA, pp. 1-51.
23. Keeley, J., Fotheringham, C., Bear-Keeley, M., 2005. Factors affecting plant diversity during post-fire recovery and succession of mediterranean-climate shrublands in California, USA. Divers. Distrib. 11, 525-537.
24. Key,C.,2006.Ecologicaland samplingconstraintsondefininglandscapefireseverity. Fire Ecol. 2, 34-59.
25. Lee, B., Kim, S., Chung, J., Park, P., 2008. Estimation of fire severity by use of Landsat TM images and its relevance to vegetation and to pography in the 2000 Samcheok forest fire. J. Forest Res. 13, 197-204.
26. Lentile, L., Holden, Z., Smith, A., Falkowski, M., Hudak, A., Morgan, P., Lewis, S., Gessler, P., Benson, N., 2006. Remote sensing techniques to assess active fire characteristics and post-fire effects. Int. J. Wildland Fire 15, 319-345.
27. Lhermitte, S., Verbesselt, J., Verstraeten, W.W., Veraverbeke, S. Coppin, P., in review. Assessing intra-annual vegetation regrowth after fire using the pixel based regeneration index. ISPRS J. Photogramm. Remote Sens.
28. Lhermitte, S., Verbesselt, J., Verstraeten, W.W., Coppin, P., 2010. A pixel based regeneration index using time series similarity and spatial context. Photogramm. Eng. Remote Sens. 76, 673-682.
29. Lopez-Garcia, M., Caselles, V., 1991. Mapping burns and natural reforestation using Thematic Mapper data. Geocarto Int. 6, 31-37.
30. Nepstad, D., Verssimo, A., Alencar, A., Nobre, C., Lima, E., Lefebvre, P., Schlesinger, P., Potter, C., Moutinho, P., Mendoza, E., Cochrane, M., Brooks, V., 1999. Large-scale impoverishment of Amazonian forests by logging and fire. Nature 398, 505-508.
31. Pausas, J., 2004. Changes in fire and climate in the eastern Iberian peninsula (Mediterranean Basin). Clim. Change 63, 337-350.
32. Reed, B., Brown, J., Vanderzee, D., Loveland, T., Merchant, J., Ohlen, D., 1994. Measuring phenological variability from satellite imagery. J. Veg. Sci. 15, 703-714.
33. Riano, D., Moreno-Ruiz, J., Isidoros, D., Ustin, S., 2007. Global spatial patterns and temporal trends of burned area between 1981 and 2000 using NOAA-NASA Pathfinder. Glob. Change Biol. 13, 40-50.
34. Teillet, P., Guindon, B., Goodenough, D., 1982. On the slope-aspect correction of multispectral scanner data. Can. J. Remote Sens. 8, 84-106.
35. Veraverbeke, S., Verstraeten, W.W., Lhermitte, S., Goossens, R., 2010. Illumination effects on the differenced normalized burn ratio's optimality for assessing fire severity. Int. J. Appl. Earth Observation Geoinf. 12, 60-70.
36. Veraverbeke, S., Verstraeten, W., Lhermitte, S., Goossens, R., in press. Evaluation Landsat Thematic Mapper spectral indices for estimating burn severity of the 2007 Peloponnese wildfires in Greece. Int. J. Wildland Fire.
37. Veraverbeke, S., Lhermitte, S., Verstraeten, W.W., Goossens, R., in press. The temporal dimension of differenced normalized burn ratio (dNBR) fire/burn severity studies: the case of the large 2007 Peloponnese wildfires in Greece.Remote Sens. Environ.
38. Verbyla, D., Kasischke, E., Hoy, E., 2008. Seasonal and topographic effects on estimating fire severity from Landsat TM/ETM+ data. Int. J. Wildland Fire 17, 527-534.
39. Vermote, E., El Saleous, N., Justice, C., 2002. Atmospheric correction of MODIS data in the visible to middle infrared: first results. Remote Sens. Environ. 83, 97-111.
40. White, J., Ryan, K., Key, C., Running, S., 1996. Remote sensing of forest fire severity and vegetation recovery. Int. J. Wildland Fire 6, 125-136.