Remote sensing approach to detect post-fire vegetation regrowth in Siberian boreal larch forest

Ecological Indicators

Volumn 62, Issue , 2016, Pages 32-46

  Chu, Thuan ^a   Guo, Xulin ^a   Takeda, Kazuo ^b  

^a UNIVERSITY OF SASKATCHEWAN   (Canada)

^b OBIHIRO UNIVERSITY OF AGRICULTURE AND VETERINARY MEDICINE   (Japan)

Author keywords

Burn severity; Larch forest; Post fire forest regeneration; Remote sensing; Trajectory

Indexed keywords

DEFORESTATION; FIRES; PLANTS (BOTANY); RECOVERY; REFORESTATION; REMOTE SENSING; TIME SERIES; TRAJECTORIES; VEGETATION;

BURN SEVERITY; FOREST REGENERATION; FOREST SUCCESSIONAL STAGES; FRACTIONAL VEGETATION COVER; LARCH FOREST; REMOTE SENSING APPROACHES; REMOTE SENSING INDEX; VEGETATION RECOVERY;

FORESTRY;

BIOINDICATOR; BOREAL FOREST; BURNING; CONIFEROUS FOREST; FOREST FIRE; LANDSAT; REGENERATION; REGROWTH; REMOTE SENSING; TIME SERIES; TRAJECTORY; VEGETATION COVER;

SIBERIA;

LARIX; LARIX SIBIRICA; POACEAE;

EID: 84949009958     PISSN: 1470160X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ecolind.2015.11.026     Document Type: Article

References (50)

1. L.T. Berner, P.S.A. Beck, A.G. Bunn, A.H. Lloyd, and S.J. Goetz High-latitude tree growth and satellite vegetation indices: correlations and trends in Russia and Canada (1982-2008) J. Geophys. Res. 116 2010 G01015
2. W. Cai, J. Yang, Z. Liu, Y. Hu, and P.J. Weisberg Post-fire tree recruitment of a boreal larch forest in Northeast China For. Ecol. Manage. 307 2013 20 29
3. M.J. Canty, and A.A. Nielsen Automatic radiometric normalization of multitemporal satellite imagery with the iteratively re-weighted MAD transformation Remote Sens. Environ. 112 2008 1025 1036
4. T.N. Carlson, and D.A. Ripley On the relation between NDVI, fractional vegetation cover, and leaf area index Remote Sens. Environ. 62 1997 241 252
5. M. Cuevas-González, F. Gerard, H. Balzter, and D. Riaño Studying the change in fAPAR after forest fires in Siberia using MODIS Int. J. Remote Sens. 29 2008 6873 6892
6. M. Cuevas Gonzalez, F. Gerard, H. Balzter, and D. Riano Analysing forest recovery after wildfire disturbance in boreal Siberia using remotely sensed vegetation indices Global Change Biol. 15 2009 561 577
7. R. Diaz-Delgado, F. Lloret, and X. Pons Influence of fire severity on plant regeneration by means of remote sensing imagery Int. J. Remote Sens. 24 2003 1751 1763
8. C. Dorisuren Post-fire successions of the larch forests in Mongolia First International Central Asian Wildland Fire Joint Conference and Consultation Ulaanbaatar, Mongolia 2008 24
9. F. Enßle, J. Heinzel, and B. Koch Accuracy of vegetation height and terrain elevation derived from ICESat/GLAS in forested areas Int. J. Appl Earth Observ. Geoinf. 31 2014 37 44
10. J. Epting, and D. Verbyla Landscape-level interactions of prefire vegetation, burn severity, and postfire vegetation over a 16-year period in interior Alaska Can. J. For. Res. 35 2005 1367 1377
11. M.A. Farukh, H. Hayasaka, and O. Mishigdorj Recent tendency of Mongolian wildland fire incidence: analysis using MODIS hotspot and weather data J. Nat. Disast. Sci. 31 2009 23 33
12. N.H.F. French, E.S. Kasischke, R.J. Hall, K.A. Murphy, D.L. Verbyla, E.E. Hoy, and J.L. Allen Using Landsat data to assess fire and burn severity in the North American boreal forest region: an overview and summary of results Int. J. Wildl. Fire 17 2008 443 462
13. S. Frolking, M. Palace, D. Clark, J. Chambers, H. Shugart, and G. Hurtt Forest disturbance and recovery: a general review in the context of spaceborne remote sensing of impacts on aboveground biomass and canopy structure J. Geophys. Res. 114 2009 G00E02
14. A.A. Gitelson, Y.J. Kaufman, R. Stark, and D. Rundquist Novel algorithms for remote estimation of vegetation fraction Remote Sens. Environ. 80 2002 76 87
15. S.J. Goetz, G.J. Fiske, and A.G. Bunn Using satellite time-series data sets to analyze fire disturbance and forest recovery across Canada Remote Sens. Environ. 101 2006 352 365
16. J.A. Hicke, G.P. Asner, E.S. Kasischke, N.H. French, J.T. Randerson, G. James Collatz, B.J. Stocks, C.J. Tucker, S.O. Los, and C.B. Field Postfire response of North American boreal forest net primary productivity analyzed with satellite observations Global Change Biol. 9 2003 1145 1157
17. C. Huang, S.N. Goward, J.G. Masek, N. Thomas, Z. Zhu, and J.E. Vogelmann An automated approach for reconstructing recent forest disturbance history using dense Landsat time series stacks Remote Sens. Environ. 114 2010 183 198
18. C. Huang, S.N. Goward, K. Schleeweis, N. Thomas, J.G. Masek, and Z. Zhu Dynamics of national forests assessed using the Landsat record: case studies in eastern United States Remote Sens. Environ. 113 2009 1430 1442
19. C. Huang, K. Song, S. Kim, J.R. Townshend, P. Davis, J.G. Masek, and S.N. Goward Use of a dark object concept and support vector machines to automate forest cover change analysis Remote Sens. Environ. 112 2008 970 985
20. Iffn The forest fire situation in Mongolia Int. For. Fire News (IFFN) 36 2007 46 66
21. T.M. James Temperature sensitivity and recruitment dynamics of Siberian larch (Larix sibirica) and Siberian spruce (Picea obovata) in northern Mongolia's boreal forest For. Ecol. Manage. 262 2011 629 636
22. Y. Jin, J.T. Randerson, S.J. Goetz, P.S.A. Beck, M.M. Loranty, and M.L. Goulden The influence of burn severity on postfire vegetation recovery and albedo change during early succession in North American boreal forests J. Geophys. Res. 117 2012 G01036
23. J.F. Johnstone, F. Chapin Iii, J. Foote, S. Kemmett, K. Price, and L. Viereck Decadal observations of tree regeneration following fire in boreal forests Can. J. For. Res. 34 2004 267 273
24. J.F. Johnstone, T.S. Rupp, M. Olson, and D. Verbyla Modeling impacts of fire severity on successional trajectories and future fire behavior in Alaskan boreal forests Landsc. Ecol. 26 2011 487 500
25. M.O. Jones, J.S. Kimball, and L.A. Jones Satellite microwave detection of boreal forest recovery from the extreme 2004 wildfires in Alaska and Canada Global Change Biol. 19 2013 3111 3122
26. E. Kasischke, and N. French Constraints on using AVHRR composite index imagery to study patterns of vegetation cover in boreal forests Int. J. Remote Sens. 18 1997 2403 2426
27. E.S. Kasischke, and B.J. Stocks Fire, Climate Change and Carbon Cycling in the Boreal Forest 2000 Springer Science & Business Media New York, USA
28. C.H. Key, and N.C. Benson Landscape assessment: ground measure of severity, the Composite Burn Index and remote sensing of severity, the Normalized Burn Ratio FIREMON Fire Effects Monitoring and Inventory System 2004 2005
29. L.B. Lentile, Z.A. Holden, A.M.S. Smith, M.J. Falkowski, A.T. Hudak, P. Morgan, S.A. Lewis, P.E. Gessler, and N.C. Benson Remote sensing techniques to assess active fire characteristics and post-fire effects Int. J. Wildl. Fire 15 2006 319 345
30. J.R.R. Leon, W.J.D. Van Leeuwen, and G.M. Casady Using MODIS-NDVI for the modeling of post-wildfire vegetation response as a function of environmental conditions and pre-fire restoration treatments Remote Sens. 4 2012 598 621
31. F.J. Lozano, S. Suárez-Seoane, and E. De Luis-Calabuig Does fire regime affect both temporal patterns and drivers of vegetation recovery in a resilient Mediterranean landscape? A remote sensing approach at two observation levels Int. J. Wildland Fire 21 2012 666 679
32. Mathworks MATLAB - The Language of Technical Computing 2008 The MathWorks, Inc. Natick, MA
33. C.W. McHugh, and T.E. Kolb Ponderosa pine mortality following fire in northern Arizona Int. J. Wildland Fire 12 2003 245
34. R. Richter A fast atmospheric correction algorithm applied to Landsat TM images Int. J. Remote Sens. 11 1990 159 166
35. A. Roder, J. Hill, B. Duguy, J.A. Alloza, and R. Vallejo Using long time series of Landsat data to monitor fire events and post-fire dynamics and identify driving factors. A case study in the Ayora region (eastern Spain) Remote Sens. Environ. 112 2007 259 273
36. R Core Team R: A Language and Environment for Statistical Computing 2014 R Foundation for Statistical Computing Vienna, Austria 3-900051-07-0 http://www.R-project.org/
37. T.A. Schroeder, W.B. Cohen, C. Song, M.J. Canty, and Z. Yang Radiometric correction of multi-temporal Landsat data for characterization of early successional forest patterns in western Oregon Remote Sens. Environ. 103 2006 16 26
38. J.P. Solans Vila, and P. Barbosa Post-fire vegetation regrowth detection in the Deiva Marina region (Liguria-Italy) using Landsat TM and ETM+ data Ecol. Model. 221 2010 75 84
39. K. Takeda, H. Torita, Y. Nobori, C.M.L. Lopez, and J. I. Regeneration in burned Larch forests of Hovsgol region northern Mongolia K. TAKEDA, Multidisciplinary Research on Mongolian Ecosystem 2013 Japan Society of Forest Planning Press Ulaanbaatar, Mongolia
40. S. Taki, Y. Nobori, C.M.L. Lopez, K. Takeda, S. Ishida, and C. M. A simulation of larch forest dynamics associated with fire in northern Mongolia K. TAKEDA, Multidisciplinary Research on Mongolian Ecosystem 2013 Japan Society of Forest Planning Press Ulaanbaatar, Mongolia
41. M. Tanase, J. De La Riva, M. Santoro, F. Pérez-Cabello, and E. Kasischke Sensitivity of SAR data to post-fire forest regrowth in Mediterranean and boreal forests Remote Sens. Environ. 115 2011 2075 2085
42. P. Teillet, B. Guindon, and D. Goodenough On the slope-aspect correction of multispectral scanner data Can. J. Remote Sens. 8 1982 84 106
43. C.J. Tucker Red and photographic infrared linear combinations for monitoring vegetation Remote Sens. Environ. 8 1979 127 150
44. USFWS Role of Fire in Alaska February 2003 ed. 2003 National Wildfire Refuge System Anchorage, Alaska
45. S. Veraverbeke, B. Somers, I. Gitas, T. Katagis, A. Polychronaki, and R. Goossens Spectral mixture analysis to assess post-fire vegetation regeneration using Landsat Thematic Mapper imagery: Accounting for soil brightness variation Int. J. Appl. Earth Observ. Geoinf. 14 2012 1 11
46. S. Veraverbeke, W.W. Verstraeten, S. Lhermitte, and R. Goossens Evaluating Landsat Thematic Mapper spectral indices for estimating burn severity of the 2007 Peloponnese wildfires in Greece Int. J. Wildland Fire 19 2010 558 569
47. K. Wittich, and O. Hansing Area-averaged vegetative cover fraction estimated from satellite data Int. J. Biometeorol. 38 1995 209 215
48. G. Yang, R. Pu, J. Zhang, C. Zhao, H. Feng, and J. Wang Remote sensing of seasonal variability of fractional vegetation cover and its object-based spatial pattern analysis over mountain areas ISPRS J. Photogram. Remote Sens. 77 2013 79 93
49. K. Yi, H. Tani, J. Zhang, M. Guo, X. Wang, and G. Zhong Long-term satellite detection of post-fire vegetation trends in boreal forests of China Remote Sens. 5 2013 6938 6957
50. O. Zyryanova, A. Abaimov, T. Bugaenko, and N. Bugaenko Recovery of forest vegetation after fire disturbance Permafrost Ecosystems 2010 Springer