Skip to main content
SpringerLink
Log in

Portraying Wildfires in Forest Landscapes as Discrete Complex Objects

  • Chapter
  • First Online:
Mapping Forest Landscape Patterns

  • 923 Accesses

Abstract

Boreal wildfires are characterized by internal heterogeneity that arises from variations in fuel availability, fuel moisture content, and weather conditions during a fire event. This heterogeneity extends from an uneven burn intensity that affects the degree of forest disturbance to inconsistency in boundary abruptness at the fire perimeter, in spot fires associated with the main fire, and in areas internal to the fire where residual vegetation and unburnable land cover types are encountered. We begin with a brief discussion of wildfire anatomy and how fires burn to create new and complex landscape patterns. We then describe some of the common approaches that are used to map wildfires, paying particular attention to the importance of scale in the mapping process. We address the complexities and heterogeneities of wildfire boundaries and internal structures by consistently linking their characterization and interpretation to spatial scale and statistical characteristics of mapping. Having outlined the variability in the formation and mapping of wildfire complexity, we propose a standardized terminology for describing these phenomena and provide some thoughts on the future of efforts to map dynamic and complex landscape entities such as wildfires.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Abbreviations

0D, 1D, 2D, 3D:

Zero-, one-, two-, and three-dimensional

FD:

Fractal dimension

GPS:

Global positioning system

LiDAR:

Light detection and ranging

MMU:

Minimum mapping unit

NDVI:

Normalized-difference vegetation index

References

  • Albini FA, Alexander ME, Cruz ME (2012) A mathematical model for predicting the maximum potential spotting distance from a crown fire. Int J Wildl Fire 21(5):609–627

    Article  Google Scholar 

  • Alonso-Benito A, Arroyro LA, Arbelo M, Hernández-Leal P (2016) Fusion of WorldView-2 and LiDAR data to map fuel types in the Canary Islands. Rem Sens 8:669

    Article  Google Scholar 

  • Araya YH, Remmel TK, Perera AH (2016a) What governs the presence of residual vegetation in boreal wildfires? J Geogr Syst 18(2):159–181

    Article  Google Scholar 

  • Araya YH, Remmel TK, Perera AH (2016b) Spatially explicit prediction of residual vegetation patch occurrence within boreal wildfires. Int J Geoinform 12(3):1–15

    Google Scholar 

  • Baker WL, Honaker JJ, Weisberg PJ (1995) Using aerial-photography and GIS to map the forest–tundra ecotone in Rocky Mountain National Park, Colorado, for global change research. Photogramm Eng Rem Sens 61:313–320

    Google Scholar 

  • Baldwin DJ, Weaver K, Schnekenburger F, Perera AH (2004) Sensitivity of landscape pattern indices to input data characteristics on real landscapes: implications for their use in natural disturbance emulation. Landsc Ecol 19:255–271

    Article  Google Scholar 

  • Boots B (2001) Using local statistics for boundary characterization. GeoJournal 53:339–345

    Article  Google Scholar 

  • Bourgeau-Chavez LL, Harrell PA, Kasischke ES, French NHF (1997) The detection and mapping of Alaskan wildfires using a spaceborne imaging radar system. Int J Rem Sens 18(2):355–373

    Article  Google Scholar 

  • Bourgeau-Chavez LL, Kasischke ES, Brunzell S, Mudd JP, Tukman M (2002) Mapping fire scars in global boreal forests using imaging radar data. Int J Rem Sens 23(20):4211–4234

    Article  Google Scholar 

  • Breidenbach J, Naesset E, Lien V, Gobakken T, Solberg S (2010) Prediction of species specific forest inventory attributes using a nonparametric semi-individual tree crown approach based on fused airborne laser scanning and multispectral data. Rem Sens Environ 114(4):911–924

    Article  Google Scholar 

  • de Casanave JL, Pelotto JP, Protomastro J (1995) Edge-interior differences in vegetation structure and composition in a Chaco semi-arid forest, Argentina. For Ecol Manage 72:61–69

    Article  Google Scholar 

  • Chandler C, Cheney P, Thomas P, Trabaud L, Williams D (1983) Fire in forestry: volume II. Forest fire management. Wiley-Interscience, New York, NY

    Google Scholar 

  • Congalton RG (1991) A review of assessing the accuracy of classifications of remotely sensed data. Rem Sens Environ 37:35–46

    Article  Google Scholar 

  • Cracknell AP (1998) Synergy in remote sensing—what’s in a pixel? Int J Rem Sens 19(11):2025–2047

    Article  Google Scholar 

  • Cromley RG (1991) Hierarchical methods of line simplification. Cartogr Geogr Inf Syst 18(2):125–131

    Article  Google Scholar 

  • Csillag F, Kabos S (1996) Hierarchical decomposition of variance with applications in environmental mapping based on satellite images. Mathem Geol 28(4):385–405

    Article  Google Scholar 

  • Csillag F, Kabos S (2002) Wavelets, boundaries, and the spatial analysis of landscape pattern. Ecoscience 9(2):177–190

    Article  Google Scholar 

  • Csillag F, Kabos S, Remmel TK (2006) Confidence in coincidence. Int J Rem Sens 27(6):1269–1276

    Article  Google Scholar 

  • Dickson BG, Prather JW, Xu YG, Hampton HM, Aumack EN, Sisk TD (2006) Mapping the probability of large fire occurrence in northern Arizona, USA. Landsc Ecol 21:747–761

    Article  Google Scholar 

  • Dunn R, Harrison AR, White JC (1990) Positional accuracy and measurement error in digital databases of land use: an empirical study. Int J Geogr Inf Syst 4(4):385–398

    Article  Google Scholar 

  • Elkie PC, Rempel RS (2001) Detecting scales of pattern in boreal forest landscapes. For Ecol Manage 147:253–261

    Article  Google Scholar 

  • Farmer E, Jones SD, Deakin RE (2011) Derivation of a resilient polygon centroid for natural resource management applications. Int J Geo Info Sci 25(9):1545–1558

    Article  Google Scholar 

  • Fernandez-Manso O, Quintano C, Fernandez-Manso A (2009) Combining spectral mixture analysis and object-based classification for fire severity mapping. Invest Agraria-Sist Recursos Forestales 18:296–313

    Google Scholar 

  • Finney MA, Cohen JD, McAllister SS, Jolly WM (2013) On the need for a theory of wildland fire spread. Int J Wildl Fire 22(1):25–36

    Article  Google Scholar 

  • Flamenco-Sandoval A, Ramos MM, Masera OR (2007) Assessing implications of land-use and land-cover change dynamics for conservation of a highly diverse tropical rain forest. Biol Conserv 138:131–145

    Article  Google Scholar 

  • Foody GM (2007) Map comparison in GIS. Progr Phys Geogr 31:439–445

    Article  Google Scholar 

  • Fortin MJ (1994) Edge detection algorithms for two dimensional ecological data. Ecology 75(4):956–965

    Article  Google Scholar 

  • Fortin MJ (1999) Effects of quadrat size and data measurement on the detection of boundaries. J Veg Sci 10:43–50

    Article  Google Scholar 

  • Fraser RH, Li Z, Cihlar J (2000) Hotspot and NDVI differencing synergy (HANDS): a new technique for burned area mapping over boreal forest. Rem Sens Environ 74:362–376

    Article  Google Scholar 

  • French NHF, Kasischke ES, Bourgeau-Chavez LL, Berry D (1995) Mapping the location of wildfires in Alaskan boreal forests using AVHRR imagery. Int J Wildl Fire 5(2):55–62

    Article  Google Scholar 

  • Gillis MD, Leckie DG (1996) Forest inventory update in Canada. For Chron 72(2):138–156

    Article  Google Scholar 

  • Gonzalez RC, Woods RE (2008) Digital image processing, 3rd edn. Pearson/Prentice Hall, Upper Saddle River, NJ

    Google Scholar 

  • Hall KR, Maruca SL (2001) Mapping a forest mosaic—a comparison of vegetation and bird distributions using geographic boundary analysis. Plant Ecol 156(1):105–120

    Article  Google Scholar 

  • Heath M, Sarkar S, Sanocki T, Bowyer K (1998) Comparison of edge detectors: a methodology and initial study. Comp Vision Image Understand 69(1):38–54

    Article  Google Scholar 

  • Hessl A, Miller J, Kernan J, Keenum D, McKenzie D (2007) Mapping paleo-fire boundaries from binary point data: comparing interpolation methods. Prof Geogr 59:87–104

    Article  Google Scholar 

  • Hirata Y, Takahashi T (2011) Image segmentation and classification of Landsat Thematic Mapper data using a sampling approach for forest cover assessment. Can J For Res 41(1):35–43

    Article  Google Scholar 

  • Holden ZA, Smith AMS, Morgan P, Rollins MG, Gessler PE (2005) Evaluation of novel thermally enhanced spectral indices for mapping fire perimeters and comparisons with fire atlas data. Int J Rem Sens 26:4801–4808

    Article  Google Scholar 

  • Jakubowski MK, Li W, Guo Q, Kelly M (2013) Delineating individual trees from Lidar data: a comparison of vector- and raster-based segmentation approaches. Rem Sens 5:4163–4186

    Article  Google Scholar 

  • James PMA, Fortin MJ, Fall A, Kneeshaw DD, Messier C (2007) The effects of spatial legacies following shifting management practices and fire on boreal forest age structure. Ecosystems 10:1261–1277

    Article  Google Scholar 

  • Johnson EA (1992) Fire and vegetation dynamics: studies from the North American boreal forest. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Johnson EA, Miyanishi K (eds) (2001) Forest fires: behavior and ecological effects. Academic Press, San Diego, CA

    Google Scholar 

  • Kasischke ES, French NHF (1995) Locating and estimating the areal extent of wildfires in Alaskan boreal forests using multiple-season AVHRR NDVI composite data. Rem Sens Environ 51(2):263–275

    Article  Google Scholar 

  • Kasischke ES, French NHF, Harrell P, Christensen NL, Ustin SL, Barry D (1993) Monitoring of wildfires in boreal forests using large-area AVHRR NDVI composite image data. Rem Sens Environ 45(1):61–71

    Article  Google Scholar 

  • Keeley JE (2009) Fire intensity, fire severity and burn severity: a brief review and suggested usage. Int J Wildl Fire 18:116–126

    Article  Google Scholar 

  • Kettig RL, Landgrebe DA (1976) Classification of multispectral image data by extraction and classification of homogeneous objects. IEEE Trans Geosci Electron 14:19–26

    Article  Google Scholar 

  • Kim JS, Cho HS (1994) A fuzzy logic and neural network approach to boundary detection for noisy imagery. Fuzzy Sets Syst 65:141–159

    Article  Google Scholar 

  • Knight JF, Lunetta RS (2003) An experimental assessment of minimum mapping unit size. IEEE Trans Geosci Rem Sens 41(9):2132–2134

    Article  Google Scholar 

  • Ko C, Sohn G, Remmel TK (2013) Tree genera classification with geometric features from high-density airborne LiDAR. Can J Rem Sens 39(s1):S73–S85

    Article  Google Scholar 

  • Leckie DG, Gillis MD (1995) Forest inventory in Canada with emphasis on map production. For Chron 71(1):74–88

    Article  Google Scholar 

  • Lim K, Treitz P, Baldwin K, Morrison I, Green J (2003) Lidar remote sensing of biophysical properties of tolerant northern hardwood forests. Can J Rem Sens 29(5):658–678

    Article  Google Scholar 

  • Liu Z, Yang J, He HS (2013) Studying the effects of fuel treatment based on burn probability on a boreal forest landscape. J Environ Manage 115:42–52

    Article  PubMed  Google Scholar 

  • Mancini F, Dubbini M, Gattelli M, Stecchi F, Fabbri S, Gabbianelli G (2013) Using unmanned aerial vehicles (UAV) for high-resolution reconstruction of topography: the structure from motion approach on coastal environments. Rem Sens 5:6880–6898

    Article  Google Scholar 

  • Mandelbrot B (1967) How long is the coast of Britain? Statistical self-similarity and fractional dimension. Science 156(3775):636–638

    Article  CAS  PubMed  Google Scholar 

  • McAlpine RS, Wotton BM (1993) The use of fractal dimension to improve wildland fire perimeter predictions. Can J For Res 23(6):1073–1077

    Article  Google Scholar 

  • McGarigal K, Marks BJ (1995) FRAGSTATS: spatial pattern analysis program for quantifying landscape structure. Gen Tech Rep PNW-GTR-351. USDA For Serv, Pacific Northwest Res Stn, Portland, OR

    Book  Google Scholar 

  • Merino-de-Miguel S, Huesca M, Gonzalez-Alonso F (2010) MODIS reflectance and active fire data for burn mapping and assessment at regional level. Ecol Model 221:67–74

    Article  Google Scholar 

  • Mitchell SW, Remmel TK, Csillag F, Wulder M (2008) Distance to second cluster as a measure of classification confidence. Rem Sens Environ 112(5):2615–2626

    Article  Google Scholar 

  • Morgan P, Hardy CC, Swetnam TW, Rollins MG, Long DG (2001) Mapping fire regimes across time and space: understanding coarse and fine-scale fire patterns. Int J Wildl Fire 10:329–342

    Article  Google Scholar 

  • Murphy KA, Reynolds JH, Koltun JM (2008) Evaluating the ability of the differenced normalized burn ratio (dNBR) to predict ecologically significant burn severity in Alaskan boreal forests. Int J Wildl Fire 17(4):490–499

    Article  Google Scholar 

  • Nadeau LB, Englefield P (2006) Fine-resolution mapping of wildfire fuel types for Canada: fuzzy logic modeling for an Alberta pilot area. Environ Monit Assess 120:127–152

    Article  CAS  PubMed  Google Scholar 

  • Oden NL, Sokal RR, Fortin MJ, Goebl H (2010) Categorical wombling: detecting regions of significant change in spatially located categorical variables. Geogr Anal 25(4):315–336

    Article  Google Scholar 

  • Oliva P, Martin P, Chuvieco E (2011) Burned area mapping with MERIS post-fire image. Int J Rem Sens 32:4175–4201

    Article  Google Scholar 

  • O'Neill RV, Krummel JR, Gardner RH, Sugihara G, Jackson B, DeAngelis DL, Milne BT, Turner MG, Zygmunt B, Christensen SW, Dale VH, Graham RL (1988) Indices of landscape pattern. Landsc Ecol 1(3):153–162

    Article  Google Scholar 

  • Ostapowicz K, Vogt P, Riitters KH, Kozak J, Estreguil C (2008) Impact of scale on morphological spatial pattern of forest. Landsc Ecol 23:1107–1117

    Article  Google Scholar 

  • Parisien MA, Parks SA, Miller C, Krawchuk MA, Heathcott M, Moritz MA (2011) Contributions of ignitions, fuels and weather to the spatial patterns of burn probability of a boreal landscape. Ecosystems 14:1141–1155

    Article  Google Scholar 

  • Park W, Yu K (2011) Hybrid line simplification for cartographic generalization. Pattern Recogn Lett 32(9):1267–1273

    Article  Google Scholar 

  • Perera AH, Buse LJ (2014) Ecology of wildfire residuals in boreal forests. Wiley, Hoboken, NJ

    Book  Google Scholar 

  • Perera AH, Buse LJ, Weber MG (eds) (2004) Emulating natural forest landscape disturbances. Columbia University Press, New York, NY

    Google Scholar 

  • Peters DPC, Groffman PM, Nadelhoffer KJ, Grimm NB, Collins SL, Michener WK, Huston MA (2008) Living in an increasingly connected world: a framework for continental-scale environmental science. Front Ecol Environ 6(5):229–237

    Article  Google Scholar 

  • Philibert MD, Fortin MJ, Csillag F (2008) Spatial structure effects on the detection of patches boundaries using local operators. Environ Ecol Stat 15:447–467

    Article  Google Scholar 

  • Pontius RG, Shusas E, McEachern M (2004) Detecting important categorical land changes while accounting for persistence. Agric Ecosyst Environ 101(2–3):251–268

    Article  Google Scholar 

  • Pourghasemi HR, Beheshtirad M, Pradhan B (2016) A comparative assessment of prediction capabilities of modified analytical hierarchy process (M-AHP) and Mamdani fuzzy logic models using Netcad-GIS for forest fire susceptibility mapping. Geomatics Nat Hazard Risk 7(2):861–885

    Article  Google Scholar 

  • Pozo D, Olmo FJ, Aladosarboledas L (1997) Fire detection and growth monitoring using a multitemporal technique on AVHRR mid-infrared and thermal channels. Rem Sens Environ 60:111–120

    Article  Google Scholar 

  • Prusinkiewicz P, Lindenmayer A (1990) The algorithmic beauty of plants. Springer-Verlag, New York, NY

    Book  Google Scholar 

  • Quattrochi DA, Goodchild MF (1997) Scale in remote sensing and GIS. CRC Press, Boca Raton, FL

    Google Scholar 

  • Rayfield BR, James PMA, Fall A, Fortin MJ (2007) Comparing static versus dynamic protected areas in dynamic boreal ecosystems. Biol Conserv 141(2):428–449

    Google Scholar 

  • Remmel TK (2009) Investigating global and local categorical map configuration comparisons based on coincidence matrices. Geogr Anal 41(1):113–126

    Google Scholar 

  • Remmel TK (2015) ShrinkShape2: a FOSS toolbox for computing rotation-invariant shape spectra for characterizing and comparing polygons. Can Geogr 59(4):532–547

    Article  Google Scholar 

  • Remmel TK, Csillag F (2003) When are two landscape pattern indices significantly different? J Geogr Syst 5(4):331–351

    Article  Google Scholar 

  • Remmel TK, Csillag F (2006) Mutual information spectra for comparing categorical maps. Int J Rem Sens 27(7):1425–1452

    Article  Google Scholar 

  • Remmel TK, Fortin MJ (2013) Categorical, class-focused map patterns: characterization and comparison. Landsc Ecol 28(8):1587–1599

    Article  Google Scholar 

  • Remmel TK, Perera AH (2001) Fire mapping in a northern boreal forest: assessing AVHRR/NDVI methods of change detection. For Ecol Manage 152(1–3):119–129

    Article  Google Scholar 

  • Remmel TK, Perera AH (2002) Accuracy of discontinuous surfaces: a case study of boreal forest fires. Int J Geogr Inf Sci 16(3):289–300

    Article  Google Scholar 

  • Remmel TK, Perera AH (2009) Mapping natural phenomena: boreal forest fires with non-discrete boundaries. Cartographica 44:274–288

    Article  Google Scholar 

  • Remmel TK, Csillag F, Mitchell S, Wulder MA (2005) Integration of forest inventory and satellite imagery: a Canadian status assessment and research issues. For Ecol Manage 207:405–428

    Article  Google Scholar 

  • Richardson LF (1961) The problem of contiguity: an appendix to statistics of deadly quarrels. In: General systems: yearbook of the society for the advancement of general systems theory, vol 61. Ann Arbor, Michigan, pp 139–187

    Google Scholar 

  • Riitters KH, O’Neill RV, Hunsaker CT, Wickham JD, Yankee DH, Timmins SP, Jones KB, Jackson BL (1995) A factor analysis of landscape pattern and structure metrics. Landsc Ecol 10(1):23–39

    Article  Google Scholar 

  • Rothermel RC (1972) A matpredicting fire spread in wildland fuels. USDA For Serv, Intermountain For Range Exp Stn, Ogden, UT. Research Paper INT-116

    Google Scholar 

  • Rouget M, Cowling RM, Lombard AT, Knight AT, Kerley GIH (2006) Designing large-scale conservation corridors for pattern and process. Conserv Biol 20(2):549–561

    Article  PubMed  Google Scholar 

  • Ruiz M, Lopez F, Paez A (2012a) Comparison of thematic maps using symbolic entropy. Int J Geogr Inf Sci 26:413–439

    Article  Google Scholar 

  • Ruiz JAM, Riano D, Arbelo M, French NHF, Ustin SL, Whiting ML (2012b) Burned area mapping time series in Canada (1984–1999) from NOAA-AVHRR LTDR: a comparison with other remote sensing products and fire perimeters. Rem Sens Environ 117:407–414

    Article  Google Scholar 

  • Saura S (2002) Effects of minimum mapping unit on land cover data spatial configuration and composition. Int J Rem Sens 23(22):4853–4880

    Article  Google Scholar 

  • Schroeder TA, Wulder MA, Healey SP, Moisen GG (2011) Mapping wildfire and clearcut harvest disturbances in boreal forests with Landsat time series data. Rem Sens Environ 115:1421–1433

    Article  Google Scholar 

  • Shi WZ, Cheung CK (2006) Performance evaluation of line simplification algorithms for vector generalization. Cartogr J 43(1):27–44

    Article  Google Scholar 

  • Siegert F, Hoffmann AA (2000) The 1998 forest fires in East Kalimantan (Indonesia): a quantitative evaluation using high resolution, multitemporal ERS-2 SAR images and NOAA-AVHRR hotspot data. Rem Sens Environ 72:64–77

    Article  Google Scholar 

  • Smith A (2010) Image segmentation scale parameter optimization and land cover classification using the Random Forest algorithm. J Spatial Sci 55(1):69–79

    Article  Google Scholar 

  • Spichtinger N, Damoah R, Eckhardt S, Forster C, James P, Beirle S, Marbach T, Wagner T, Novelli PC, Stohl A (2004) Boreal forest fires in 1997 and 1998: a seasonal comparison using transport model simulations and measurement data. Atmos Chem Phys 4(7):1857–1868

    Article  CAS  Google Scholar 

  • Sullivan AL (2009) Wildland surface fire spread modelling, 1990–2007. 3: Simulation and mathematical analogue modes. Int J Wildl Fire 18:387–403

    Article  Google Scholar 

  • Sun J, Southworth J (2013) Remote sensing-based fractal analysis and scale dependence associated with forest fragmentation in an Amazon tri-national frontier. Rem Sens 5:454–472

    Article  Google Scholar 

  • Turner MG (2005) Landscape ecology: what is the state of the science? Ann Rev Ecol Evol Syst 36:319–344

    Article  Google Scholar 

  • Vogt P, Riitters KH, Estreguil C, Kozak J, Wade TG, Wickham JD (2007) Mapping spatial patterns with morphological image processing. Landsc Ecol 22:171–177

    Article  Google Scholar 

  • van Wagner CE (1969) A simple fire-growth model. For Chron 45:103–104

    Article  Google Scholar 

  • Wang F, Hall GB (1996) Fuzzy representation of geographical boundaries in GIS. Int J Geogr Inf Syst 10(5):573–590

    Article  Google Scholar 

  • Wang G, Oyana T, Zhang M, Adu-Prah S, Zeng S, Lin H, Se J (2009) Mapping and spatial uncertainty analysis of forest vegetation carbon by combining national forest inventory data and satellite images. For Ecol Manage 258:1275–1283

    Article  Google Scholar 

  • Whelan RJ (1995) The ecology of fire. Cambridge Studies in Ecology, Cambridge Univ. Press, Cambridge

    Google Scholar 

  • Wu ST, Marquez MRG (2003) A non-self-intersection Douglas-Peucker algorithm. In: Proceedings of the XVI Brazilian symposium on computer graphics and image processing (SIBGRAPI’03) IEEE computer society. Unpaginated http://ieeexplore.ieee.org/document/1240992/authors

  • Wu B, Yu B, Yue W, Shu S, Tan W, Hu C, Huang Y, Wu J, Liu H (2013) A voxel-based method for automated identification and morphological parameters estimation of individual street trees from mobile laser scanning data. Rem Sens 5:584–611

    Article  Google Scholar 

  • Yu J, Chen D, Lin Y, Ye S (2017) Comparison of linear and nonlinear spectral unmixing approaches: a case study with multispectral TM imagery. Int J Remote Sens 38(3):773–795

    Article  Google Scholar 

  • Zhang J, Stuart N (2001) Fuzzy methods for categorical mapping with image-based land cover data. Int J Geogr Inf Sci 15(2):175–195

    Article  Google Scholar 

  • Zipperer WC (1993) Deforestation patterns and their effects on forest patches. Landsc Ecol 8(3):177–184

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Geography, York University, 4700 Keele Street, Toronto, ON, Canada, M3J 1P3

    Tarmo K. Remmel

  2. Ontario Forest Research Institute, Ministry of Natural Resources and Forestry, 1235 Queen Street East, Sault Ste. Marie, ON, Canada, P6A 2E5

    Ajith H. Perera

Authors
  1. Tarmo K. Remmel
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ajith H. Perera
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tarmo K. Remmel .

Editor information

Editors and Affiliations

  1. Department of Geography, York University, Toronto, Ontario, Canada

    Tarmo K. Remmel

  2. Ministry of Natural Resources and Forestry, Ontario Forest Research Institute, Sault Ste. Marie, Ontario, Canada

    Ajith H. Perera

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer Science+Business Media LLC

About this chapter

Cite this chapter

Remmel, T.K., Perera, A.H. (2017). Portraying Wildfires in Forest Landscapes as Discrete Complex Objects. In: Remmel, T., Perera, A. (eds) Mapping Forest Landscape Patterns. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-7331-6_3

Download citation

Publish with us

Policies and ethics

Search

Navigation