Compositing MODIS time series for reconstructing burned areas in the taiga–steppe transition zone of northern Mongolia
Thuan Chu A B C and Xulin Guo A
+ Author Affiliations
- Author Affiliations
A Department of Geography and Planning, Kirk Hall, University of Saskatchewan, 117 Science Place, Saskatoon, SK S7N5C8, Canada.
B Department of Forest Inventory and Planning, Forestry University, Xuan Mai town, Chuong My district, Hanoi, Vietnam.
C Corresponding author. Email: thuan.chu@usask.ca
International Journal of Wildland Fire 24(3) 419-432 https://doi.org/10.1071/WF14124
Submitted: 17 July 2014 Accepted: 10 November 2014 Published: 3 March 2015
Abstract
Wildfire is the main natural disturbance in forest ecosystems; it controls and modifies vegetation compositions, landscape properties and global carbon cycle. Estimates of areas burned by wildfires vary greatly depending on the environmental conditions, data availability and methods used. This paper aims to develop a framework for reconstructing time series of burned areas in the taiga–steppe transition zone using MODIS composites. The estimated accuracy of the developed mapping algorithm and other statistical indications denote that the clear land surface composites of MODIS data in spring (Julian dates, JD 97–177), logistic regression and MODIS active fire product can be integrated successfully for reconstructing burned areas in the taiga–steppe transition zone. Time series of burned areas between 2000 and 2012 derived from the MODIS spring composite algorithm were validated using Landsat-based burned areas, showing average omission and commission errors of 18% and 31%. Compared with the MCD45A1 burned area product, the developed algorithm significantly improved the prediction of burned areas and successfully separated late-season from early-season burns. The derived long-term burned areas will assist in understanding the complex relationships among forest dynamics, forest recovery and fire in the vulnerable boreal forest ecosystem as well as its transition zone under climate change in northern Mongolia and Central Asia.
Additional keywords: boreal forest, logistic regression, spring composite.
References
Babintseva R, Titova YV (1996) Effects of fire on the regeneration of larch forests in the Lake Baikal Basin. Forestry Sciences 48, 358–365.| Effects of fire on the regeneration of larch forests in the Lake Baikal Basin.Crossref | GoogleScholarGoogle Scholar |
Bartalev S, Belward A, Erchov D, Isaev A (2003) A new SPOT4-VEGETATION derived land cover map of Northern Eurasia. International Journal of Remote Sensing 24, 1977–1982.
| A new SPOT4-VEGETATION derived land cover map of Northern Eurasia.Crossref | GoogleScholarGoogle Scholar |
Bartholomé E, Belward A (2005) GLC2000: a new approach to global land cover mapping from Earth observation data. International Journal of Remote Sensing 26, 1959–1977.
| GLC2000: a new approach to global land cover mapping from Earth observation data.Crossref | GoogleScholarGoogle Scholar |
Bastarrika A, Chuvieco E, Martín MP (2011a) Automatic burned land mapping from MODIS time series images: assessment in Mediterranean ecosystems. IEEE Transactions on Geoscience and Remote Sensing 49, 3401–3413.
| Automatic burned land mapping from MODIS time series images: assessment in Mediterranean ecosystems.Crossref | GoogleScholarGoogle Scholar |
Bastarrika A, Chuvieco E, Martãn MP (2011b) Mapping burned areas from Landsat TM/ETM+ data with a two-phase algorithm: balancing omission and commission errors. Remote Sensing of Environment 115, 1003–1012.
| Mapping burned areas from Landsat TM/ETM+ data with a two-phase algorithm: balancing omission and commission errors.Crossref | GoogleScholarGoogle Scholar |
Batkhuu NO, Lee DK, Tsogtbaatar J (2011) Forest and forestry research and education in Mongolia. Journal of Sustainable Forestry 30, 600–617.
| Forest and forestry research and education in Mongolia.Crossref | GoogleScholarGoogle Scholar |
Bergeron Y, Gauthier S, Kafka V, Lefort P, Lesieur D (2001) Natural fire frequency for the eastern Canadian boreal forest: consequences for sustainable forestry. Canadian Journal of Forest Research 31, 384–391.
| Natural fire frequency for the eastern Canadian boreal forest: consequences for sustainable forestry.Crossref | GoogleScholarGoogle Scholar |
Boschetti L, Roy D, Hoffmann A (2009) MODIS Collection 5 Burned Area Product-MCD45. User’s Guide, Ver. 2.
Chang D, Song Y (2009) Comparison of L3JRC and MODIS global burned area products from 2000 to 2007. Journal of Geophysical Research, D, Atmospheres 114, D16106
| Comparison of L3JRC and MODIS global burned area products from 2000 to 2007.Crossref | GoogleScholarGoogle Scholar |
Chu T, Guo X (2014) Remote sensing techniques in monitoring post-fire effects and patterns of forest recovery in boreal forest regions: a review. Remote Sensing 6, 470–520.
| Remote sensing techniques in monitoring post-fire effects and patterns of forest recovery in boreal forest regions: a review.Crossref | GoogleScholarGoogle Scholar |
Chuvieco E, Englefield P, Trishchenko AP, Luo Y (2008a) Generation of long time series of burn area maps of the boreal forest from NOAA – AVHRR composite data. Remote Sensing of Environment 112, 2381–2396.
| Generation of long time series of burn area maps of the boreal forest from NOAA – AVHRR composite data.Crossref | GoogleScholarGoogle Scholar |
Chuvieco E, Opazo S, Sione W, Valle HD, Anaya J, Bella CD, Cruz I, Manzo L, Lopez G, Mari N (2008b) Global burned-land estimation in Latin America using MODIS composite data. Ecological Applications 18, 64–79.
| Global burned-land estimation in Latin America using MODIS composite data.Crossref | GoogleScholarGoogle Scholar | 18372556PubMed |
de Groot WJ, Flannigan MD, Cantin AS (2013) Climate change impacts on future boreal fire regimes. Forest Ecology and Management 294, 35–44.
| Climate change impacts on future boreal fire regimes.Crossref | GoogleScholarGoogle Scholar |
De Santis A, Chuvieco E (2007) Burn severity estimation from remotely sensed data: performance of simulation versus empirical models. Remote Sensing of Environment 108, 422–435.
| Burn severity estimation from remotely sensed data: performance of simulation versus empirical models.Crossref | GoogleScholarGoogle Scholar |
Dubinin M, Potapov P, Lushchekina A, Radeloff VC (2010) Reconstructing long time series of burned areas in arid grasslands of southern Russia by satellite remote sensing. Remote Sensing of Environment 114, 1638–1648.
| Reconstructing long time series of burned areas in arid grasslands of southern Russia by satellite remote sensing.Crossref | GoogleScholarGoogle Scholar |
Dwyer MJ, Schmidt G (2006) The MODIS reprojection tool. In ‘Earth science satellite remote sensing.’ (Eds J. J. Qu, W. Gao, M. Kafatos, R. E. Murphy, V. V. Salomonson) pp. 162–177 (Springer: Berlin, Heidelberg)
EARSEL (2008) Disaster management and emergency response in the Mediterranean region. In ‘First International Conference on Remote Sensing Techniques in Disaster Management and Emergency Response in the Mediterranean Region’, 22–24 September 2008, Zagreb, Croatia. (Ed. M Oluic) European Association of Remote Sensing Laboratories (EARSEL) (Zagreb, Croatia).
FAO (2010) Global Forest Resources Assessment 2010 – main report. Food and Agriculture Organization of the United Nations (FAO), Forestry Paper 163 (Rome, Italy)
Farukh MA, Hayasaka H, Mishigdorj O (2009) Recent tendency of Mongolian wildland fire incidence: analysis using MODIS hotspot and weather data. Journal of Natural Disaster Science 31, 23–33.
| Recent tendency of Mongolian wildland fire incidence: analysis using MODIS hotspot and weather data.Crossref | GoogleScholarGoogle Scholar |
Flannigan M, Amiro B, Logan K, Stocks B, Wotton B (2006) Forest fires and climate change in the 21 st century. Mitigation and Adaptation Strategies for Global Change 11, 847–859.
| Forest fires and climate change in the 21 st century.Crossref | GoogleScholarGoogle Scholar |
Giglio L (2010) MODIS Collection 5 active fire product user’s guide Ver. 2.4. Science Systems and Applications, University of Maryland.
Giglio L, Randerson J, Werf G, Kasibhatla P, Collatz G, Morton D, DeFries R (2010) Assessing variability and long-term trends in burned area by merging multiple satellite fire products. Biogeosciences 7, 1171–1186.
| Assessing variability and long-term trends in burned area by merging multiple satellite fire products.Crossref | GoogleScholarGoogle Scholar |
Giglio L, Randerson JT, van der Werf GR (2013) Analysis of daily, monthly, and annual burned area using the fourth-generation global fire emissions database (GFED4). J. Geophys. Res.: Biogeosci. 118, 317–328.
| Analysis of daily, monthly, and annual burned area using the fourth-generation global fire emissions database (GFED4).Crossref | GoogleScholarGoogle Scholar |
Hantson S, Padilla M, Corti D, Chuvieco E (2013) Strengths and weaknesses of MODIS hotspots to characterize global fire occurrence. Remote Sensing of Environment 131, 152–159.
| Strengths and weaknesses of MODIS hotspots to characterize global fire occurrence.Crossref | GoogleScholarGoogle Scholar |
Hessl AE, Ariya U, Brown P, Byambasuren O, Green T, Jacoby G, Sutherland EK, Nachin B, Maxwell RS, Pederson N (2012) Reconstructing fire history in central Mongolia from tree-rings. International Journal of Wildland Fire 21, 86–92.
| Reconstructing fire history in central Mongolia from tree-rings.Crossref | GoogleScholarGoogle Scholar |
IFFN (2007) The forest fire situation in Mongolia. International Forest Fire News 36, 46–66.
James TM (2011) Temperature sensitivity and recruitment dynamics of Siberian larch (Larix sibirica) and Siberian spruce (Picea obovata) in northern Mongolia’s boreal forest. Forest Ecology and Management 262, 629–636.
| Temperature sensitivity and recruitment dynamics of Siberian larch (Larix sibirica) and Siberian spruce (Picea obovata) in northern Mongolia’s boreal forest.Crossref | GoogleScholarGoogle Scholar |
Jin Y, Randerson JT, Goetz SJ, Beck PSA, Loranty MM, Goulden ML (2012) The influence of burn severity on postfire vegetation recovery and albedo change during early succession in North American boreal forests. Journal of Geophysical Research 117, G01036
| The influence of burn severity on postfire vegetation recovery and albedo change during early succession in North American boreal forests.Crossref | GoogleScholarGoogle Scholar |
Johnstone JF, Chapin FS, Hollingsworth TN, Mack MC, Romanovsky V, Turetsky M (2010) Fire, climate change, and forest resilience in interior Alaska. Canadian Journal of Forest Research 40, 1302–1312.
| Fire, climate change, and forest resilience in interior Alaska.Crossref | GoogleScholarGoogle Scholar |
Kasischke ES, Johnstone JF (2005) Variation in postfire organic layer thickness in a black spruce forest complex in interior Alaska and its effects on soil temperature and moisture. Canadian Journal of Forest Research 35, 2164–2177.
| Variation in postfire organic layer thickness in a black spruce forest complex in interior Alaska and its effects on soil temperature and moisture.Crossref | GoogleScholarGoogle Scholar |
Kasischke ES, Bourgeau-Chavez LL, Johnstone JF (2007) Assessing spatial and temporal variations in surface soil moisture in fire-disturbed black spruce forests in Interior Alaska using spaceborne synthetic aperture radar imagery – implications for post-fire tree recruitment. Remote Sensing of Environment 108, 42–58.
| Assessing spatial and temporal variations in surface soil moisture in fire-disturbed black spruce forests in Interior Alaska using spaceborne synthetic aperture radar imagery – implications for post-fire tree recruitment.Crossref | GoogleScholarGoogle Scholar |
Kasischke ES, Verbyla DL, Rupp TS, McGuire AD, Murphy KA, Jandt R, Barnes JL, Hoy EE, Duffy PA, Calef M (2010) Alaska’s changing fire regime – implications for the vulnerability of its boreal forests. Canadian Journal of Forest Research 40, 1313–1324.
| Alaska’s changing fire regime – implications for the vulnerability of its boreal forests.Crossref | GoogleScholarGoogle Scholar |
Kasischke ES, Loboda T, Giglio L, French NH, Hoy E, de Jong B, Riano D (2011) Quantifying burned area for North American forests: implications for direct reduction of carbon stocks. Journal of Geophysical Research 116, G04003
| Quantifying burned area for North American forests: implications for direct reduction of carbon stocks.Crossref | GoogleScholarGoogle Scholar |
Key CH, Benson NC (2005) Landscape assessment: ground measure of severity, the Composite Burn Index; and remote sensing of severity, the Normalized Burn Ratio. In ‘FIREMON: Fire Effects Monitoring And Inventory System.’ (Eds D.Lutes, R Keane, J Caratti, C Key, N Benson, S Sutherland, L Gangi) USDA Forest Service, Rocky Mountain Research Station, General Technical Report RMRS-GTR-164-CDLA, pp. 1–51. (Fort Collins, CO)
Koutsias N, Karteris M (2000) Burned area mapping using logistic regression modeling of a single post-fire Landsat-5 Thematic Mapper image. International Journal of Remote Sensing 21, 673–687.
| Burned area mapping using logistic regression modeling of a single post-fire Landsat-5 Thematic Mapper image.Crossref | GoogleScholarGoogle Scholar |
Kukavskaya EA, Soja AJ, Petkov AP, Ponomarev EI, Ivanova GA, Conard SG (2013) Fire emissions estimates in Siberia: evaluation of uncertainties in area burned, land cover, and fuel consumption. Canadian Journal of Forest Research 43, 493–506.
| Fire emissions estimates in Siberia: evaluation of uncertainties in area burned, land cover, and fuel consumption.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3sXntV2ls7Y%3D&md5=2fae7067277068760d615f27ca66aae3CAS |
Lacaze R, Balsamo G, Baret F, Bradley A, Calvet J, Camacho F, D’Andrimont R, Freitas S, Makhmara H, Naeimi V (2010) Geoland2 – Towards an operational GMES land monitoring core service: first results of the biogeophysical parameter core mapping service. In ‘ISPRS TC VII Symposium – 100 Years ISPRS’, 5–7 July 2010, Vienna, Austria. IAPRS. (Eds W. Wagner, B. Székely) pp. 354–359 (Vienna, Austria)
Lentile LB, Holden ZA, Smith AMS, Falkowski MJ, Hudak AT, Morgan P, Lewis SA, Gessler PE, Benson NC (2006) Remote sensing techniques to assess active fire characteristics and post-fire effects. International Journal of Wildland Fire 15, 319–345.
| Remote sensing techniques to assess active fire characteristics and post-fire effects.Crossref | GoogleScholarGoogle Scholar |
Loboda TV, Hoy EE, Giglio L, Kasischke ES (2011) Mapping burned area in Alaska using MODIS data: a data limitations-driven modification to the regional burned area algorithm. International Journal of Wildland Fire 20, 487–496.
| Mapping burned area in Alaska using MODIS data: a data limitations-driven modification to the regional burned area algorithm.Crossref | GoogleScholarGoogle Scholar |
Loepfe L, Lloret F, Román-Cuesta RM (2012) Comparison of burnt area estimates derived from satellite products and national statistics in Europe. International Journal of Remote Sensing 33, 3653–3671.
| Comparison of burnt area estimates derived from satellite products and national statistics in Europe.Crossref | GoogleScholarGoogle Scholar |
Lozano FJ, Suarez-Seoane S, de Luis E (2007) Assessment of several spectral indices derived from multi-temporal Landsat data for fire occurrence probability modelling. Remote Sensing of Environment 107, 533–544.
| Assessment of several spectral indices derived from multi-temporal Landsat data for fire occurrence probability modelling.Crossref | GoogleScholarGoogle Scholar |
Mallinis G, Koutsias N (2012) Comparing ten classification methods for burned area mapping in a Mediterranean environment using Landsat TM satellite data. International Journal of Remote Sensing 33, 4408–4433.
| Comparing ten classification methods for burned area mapping in a Mediterranean environment using Landsat TM satellite data.Crossref | GoogleScholarGoogle Scholar |
Miller JD, Thode AE (2007) Quantifying burn severity in a heterogeneous landscape with a relative version of the delta Normalized Burn Ratio (dNBR). Remote Sensing of Environment 109, 66–80.
| Quantifying burn severity in a heterogeneous landscape with a relative version of the delta Normalized Burn Ratio (dNBR).Crossref | GoogleScholarGoogle Scholar |
Mouillot F, Schultz MG, Yue C, Cadule P, Tansey K, Ciais P, Chuvieco E (2014) Ten years of global burned area products from spaceborne remote sensing – a review: analysis of user needs and recommendations for future developments. International Journal of Applied Earth Observation and Geoinformation 26, 64–79.
| Ten years of global burned area products from spaceborne remote sensing – a review: analysis of user needs and recommendations for future developments.Crossref | GoogleScholarGoogle Scholar |
Murray M (2004) Dynamics of biodiversity loss and permafrost melt in Lake Hovsgol National Park, Mongolia. Hovsgol GEF/WB Project TF028988, Geo-Ecology Institute 301, Hovsgol, Mongolia.
Pereira JMC (1999) A comparative evaluation of NOAA/AVHRR vegetation indexes for burned surface detection and mapping. IEEE Transactions on Geoscience and Remote Sensing 37, 217–226.
| A comparative evaluation of NOAA/AVHRR vegetation indexes for burned surface detection and mapping. Crossref | GoogleScholarGoogle Scholar |
Plummer S, Arino O, Simon M, Steffen W (2006) Establishing a earth observation product service for the terrestrial carbon community: the GLOBCARBON initiative. Mitigation and Adaptation Strategies for Global Change 11, 97–111.
| Establishing a earth observation product service for the terrestrial carbon community: the GLOBCARBON initiative.Crossref | GoogleScholarGoogle Scholar |
Pu R, Li Z, Gong P, Csiszar I, Fraser R, Hao W-M, Kondragunta S, Weng F (2007) Development and analysis of a 12-year daily 1-km forest fire dataset across North America from NOAA/AVHRR data. Remote Sensing of Environment 108, 198–208.
| Development and analysis of a 12-year daily 1-km forest fire dataset across North America from NOAA/AVHRR data.Crossref | GoogleScholarGoogle Scholar |
Randerson JT, Chen Y, van der Werf GR, Rogers BM, Morton DC (2012) Global burned area and biomass burning emissions from small fires. J. Geophys. Res.: Biogeosci. 117, G04012
| Global burned area and biomass burning emissions from small fires.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3sXhtFCnsLjL&md5=4620faafabc3d7e9fd4e95fb1250f56bCAS |
Roy DP, Boschetti L (2009) Southern Africa validation of the MODIS, L3JRC, and GlobCarbon burned-area products. IEEE Transactions on Geoscience and Remote Sensing 47, 1032–1044.
Roy D, Jin Y, Lewis P, Justice C (2005) Prototyping a global algorithm for systematic fire-affected area mapping using MODIS time series data. Remote Sensing of Environment 97, 137–162.
| Prototyping a global algorithm for systematic fire-affected area mapping using MODIS time series data.Crossref | GoogleScholarGoogle Scholar |
Sofronov M, Volokitina A (2010) Wildfire ecology in continuous permafrost zone. In ‘Permafrost ecosystems: Siberian larch forests.’ (Eds A. Osawa, O. A. Zyryanova, Y. Matsuura, R. Kajimoto, R. W. Wein) pp. 59–82 (Springer: New York)
Stroppiana D, Bordogna G, Carrara P, Boschetti M, Boschetti L, Brivio P (2012) A method for extracting burned areas from Landsat TM/ETM+ images by soft aggregation of multiple spectral indices and a region-growing algorithm. ISPRS Journal of Photogrammetry and Remote Sensing 69, 88–102.
| A method for extracting burned areas from Landsat TM/ETM+ images by soft aggregation of multiple spectral indices and a region-growing algorithm.Crossref | GoogleScholarGoogle Scholar |
Tansey K, Grégoire JM, Defourny P, Leigh R, Pekel JF, van Bogaert E, Bartholomé E (2008) A new, global, multi-annual (2000–2007) burnt area product at 1-km resolution. Geophysical Research Letters 35, L01401
| A new, global, multi-annual (2000–2007) burnt area product at 1-km resolution.Crossref | GoogleScholarGoogle Scholar |
Tsela P, van Helden P, Frost P, Wessels K, Archibald S (2010) Validation of the MODIS burned-area products across different biomes in South Africa. In ‘International Geoscience and Remote Sensing Symposium (IGARSS)’, 25–30 July 2010, Honolulu, HI, pp. 3652–3655 (Danvers, MA)
Tucker CJ (1979) Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment 8, 127–150.
| Red and photographic infrared linear combinations for monitoring vegetation.Crossref | GoogleScholarGoogle Scholar |
Vermote E, Kotchenova S (2011) MOD09 (Surface Reflectance) User’s Guide. Available at http://modis-sr.ltdri.org/products/MOD09_UserGuide_v1_3.pdf [Verified 4 December 2014]
Wilson EH, Sader SA (2002) Detection of forest harvest type using multiple dates of Landsat TM imagery. Remote Sensing of Environment 80, 385–396.
| Detection of forest harvest type using multiple dates of Landsat TM imagery.Crossref | GoogleScholarGoogle Scholar |
Yoshikawa K, Bolton WR, Romanovsky VE, Fukuda M, Hinzman LD (2003) Impacts of wildfire on the permafrost in the boreal forests of Interior Alaska. Journal of Geophysical Research Atmospheres 108, FFR 4-1–FFR 4-14.
| Impacts of wildfire on the permafrost in the boreal forests of Interior Alaska.Crossref | GoogleScholarGoogle Scholar |
Zyryanova O, Abaimov A, Bugaenko T, Bugaenko N (2010a) Recovery of forest vegetation after fire disturbance. In ‘Permafrost ecosystems: Siberian larch forests.’ (Eds A. Osawa, O. A. Zyryanova, Y. Matsuura, R. Kajimoto, R. W. Wein) pp. 83–96 (Springer: New York)
Zyryanova O, Abaimov A, Daimaru H, Matsuura Y (2010b) Floristic diversity and its geographical background in central Siberia. In ‘Permafrost ecosystems: Siberian larch forests.’ (Eds A. Osawa, O. A. Zyryanova, Y. Matsuura, R. Kajimoto, R. W. Wein) pp. 17–39 (Springer: New York)
