Mapping canopy damage from understory fires in Amazon forests using annual time
series of Landsat and MODIS data
Douglas C. Morton
a,
⁎
, Ruth S. DeFries
b,c
, Jyoteshwar Nagol
a
, Carlos M. Souza Jr.
d
, Eric S. Kasischke
a
,
George C. Hurtt
e,f
, Ralph Dubayah
a
a
Department of Geography, 2181 LeFrak Hall, University of Maryland, College Park, MD 20742, United States
b
Department of Ecology, Evolution, and Environmental Biology, Columbia University, New York, NY 10027, United States
c
Lamont-Doherty Earth Observatory, Palisades, NY 10964, United States
d
Instituto do Homem e Meio Ambiente da Amazônia (IMAZON), Belém, Pará, Brazil
e
Institute for the study of Earth, Oceans, and Space (EOS), University of New Hampshire, Durham, NH 03824, United States
f
Department of Natural Resources, University of New Hampshire, Durham, NH 03824, United States
abstractarticle info
Article history:
Received 8 February 2010
Received in revised form 28 February 2011
Accepted 6 April 2011
Available online 6 April 2011
Keywords:
Forest degradation
REDD+
Deforestation
Fire
Time series
Understory fires in Amazon forests alter forest structure, species composition, and the likelihood of future
disturbance. The annual extent of fire-damaged forest in Amazonia remains uncertain due to difficulties in
separating burning from other types of forest damage in satellite data. We developed a new approach, the
Burn Damage and Recovery (BDR) algorithm, to identify fire-related canopy damages using spatial and
spectral information from multi-year time series of satellite data. The BDR approach identifies understory fires
in intact and logged Amazon forests based on the reduction and recovery of live canopy cover in the years
following fire damages and the size and shape of individual understory burn scars. The BDR algorithm was
applied to time series of Landsat (1997–2004) and MODIS (2000–2005) data covering one Landsat scene
(path/row 226/068) in southern Amazonia and the results were compared to field observations, image-
derived burn scars, and independent data on selective logging and deforestation. Landsat resolution was
essential for detection of burn scars b50 ha, yet these small burns contributed only 12% of all burned forest
detected during 1997–2002. MODIS data were suitable for mapping medium (50–500 ha) and large
(N500 ha) burn scars that accounted for the majority of all fire-damaged forests in this study. Therefore,
moderate resolution satellite data may be suitable to provide estimates of the extent of fire-damaged Amazon
forest at a regional scale. In the study region, Landsat-based understory fire damages in 1999 (1508 km
2
) were
an order of magnitude higher than during the 1997–1998 El Niño event (124 km
2
and 39 km
2
, respectively),
suggesting a different link between climate and understory fires than previously reported for other Amazon
regions. The results in this study illustrate the potential to address critical questions concerning climate and
fire risk in Amazon forests by applying the BDR algorithm over larger areas and longer image time series.
Published by Elsevier Inc.
1. Introduction
Fire is an important cause of tropical forest degradation with
myriad impacts on forest structure, biodiversity, and nutrient cycling
(Cochrane, 2003; Goldammer, 1990). In Amazonia, forest fires occur
when human ignitions for deforestation or land management escape
their intended boundaries and burn into neighboring forest areas
(e.g., Cochrane et al., 1999; Uhl & Buschbacher, 1985). Understory
forest fires are surface fires that burn leaf litter and coarse woody
debris in both logged and intact Amazon forests (Balch et al., 2008;
Holdsworth & Uhl, 1997; Matricardi et al., 2010; Souza et al., 2005a).
Damages from understory fires in tropical forests can be severe,
reducing species richness by 30% and above-ground live biomass by
up to 50% (Cochrane & Schulze, 1999). Even moderate-intensity
understory fires can result in high canopy mortality, as few Amazon
forest species have fire-adapted traits (Uhl & Kauffman, 1990).
Widespread forest fires in Amazonia were reported during drought
conditions associated with the El Niño Southern Oscillation (ENSO) in
1997–1998 (Alencar et al., 2006; Barbosa & Fearnside, 1999; Elvidge
et al., 2001; Phulpin et al., 2002), yet the interannual variation in
burned forest extent remains uncertain due to difficulties in
separating fires from other forest damages using satellite data.
Remote Sensing of Environment 115 (2011) 1706–1720
⁎ Corresponding author at: Present Address: NASA Goddard Space Flight Center,
Biospheric Sciences Branch, Code 614.4, Greenbelt, MD 20771, United States. Tel.: +1
301 614 6688; fax: +1 301 614 6695.
E-mail addresses: douglas.morton@nasa.gov (D.C. Morton), rd2402@columbia.edu
(R.S. DeFries), jnagol@geog.umd.edu (J. Nagol), souzajr@imazon.org.br (C.M. Souza),
ekasisch@mail.umd.edu (E.S. Kasischke), george.hurtt@unh.edu (G.C. Hurtt),
dubayah@umd.edu (R. Dubayah).
0034-4257/$ – see front matter. Published by Elsevier Inc.
doi:10.1016/j.rse.2011.03.002
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Remote Sensing of Environment
journal homepage: www.elsevier.com/locate/rse