Sch2006q

Sch2006q
Remote Sensing of Environment 113 (2009) 380–391
Contents lists available at ScienceDirect
Remote Sensing of Environment
j o u r n a l h o m e p a g e : w w w. e l s e v i e r. c o m / l o c a t e / r s e
Land cover classification of tundra environments in the Arctic Lena Delta based on
Landsat 7 ETM+ data and its application for upscaling of methane emissions
Julia Schneider 1, Guido Grosse 2, Dirk Wagner ⁎
Alfred Wegener Institute for Polar and Marine Research, Research Unit Potsdam, 14473, Potsdam, Germany
a r t i c l e
i n f o
Article history:
Received 2 August 2007
Received in revised form 9 October 2008
Accepted 11 October 2008
Keywords:
Land cover classification
Methane emission
Upscaling
Tundra environments
Northeast Siberia
Lena River Delta
a b s t r a c t
The Lena River Delta, situated in Northern Siberia (72.0–73.8° N, 122.0–129.5° E), is the largest Arctic delta
and covers 29,000 km2. Since natural deltas are characterised by complex geomorphological patterns and
various types of ecosystems, high spatial resolution information on the distribution and extent of the delta
environments is necessary for a spatial assessment and accurate quantification of biogeochemical processes
as drivers for the emission of greenhouse gases from tundra soils. In this study, the first land cover
classification for the entire Lena Delta based on Landsat 7 Enhanced Thematic Mapper (ETM+) images was
conducted and used for the quantification of methane emissions from the delta ecosystems on the regional
scale. Nine land cover classes of aquatic and terrestrial ecosystems in the wetland dominated (72%) Lena
Delta could be defined by this classification approach. The mean daily methane emission of the entire Lena
Delta was calculated with 10.35 mg CH4 m− 2 d− 1. Taking our multi-scale approach into account we find that
the methane source strength of certain tundra wetland types is lower than calculated previously on coarser
scales.
© 2008 Elsevier Inc. All rights reserved.
1. Introduction
Beside carbon dioxide and water vapour, the atmospheric trace gas
methane (CH4) is one of the most important greenhouse gases.
Methane is chemically very reactive and more efficient in absorbing
infrared radiation than carbon dioxide. Its contribution to the radiative
forcing from pre-industrial to present time is estimated with about
20% of all greenhouse gases (IPCC, 2001; Le Mer & Roger, 2001).
Methane has a wide variety of natural and anthropogenic sources
(Wuebbles & Hayhoe, 2002). Although the major sources of atmospheric methane are relatively well known, the quantification of
methane emissions from these sources is difficult due to high spatial
and temporal variability (IPCC, 2001). The most important natural
sources are wetlands (Bartlett & Harriss, 1993; Wuebbles & Hayhoe,
2002). They cover about 4–6% of the Earth's land surface (Mitsch et al.,
1994). 28% of these wetlands are located in the high latitudes north of
60°N in the Arctic and Subarctic climate zone (Matthews & Fung,
1987). Wetlands emit about 100 Tg methane annually, or about 20% of
overall global emissions of 450–550 Tg a− 1 (Matthews, 2000).
Estimates of the methane emissions of Arctic and Subarctic wetlands
range between 10 and 39 Tg a− 1, or between 2.2 and 8.6% of the overall
global methane emissions (Bartlett & Harriss, 1993; Bartlett et al.,
⁎ Corresponding author. Tel.: +49 331 288 2159; fax: +49 331 288 2137.
E-mail address: [email protected] (D. Wagner).
1
Present address: University of Greifswald, Institute of Botany and Landscape
Ecology, 17487, Greifswald, Germany.
2
Present address: Geophysical Institute, University of Alaska, Fairbanks, USA.
0034-4257/$ – see front matter © 2008 Elsevier Inc. All rights reserved.
doi:10.1016/j.rse.2008.10.013
1992). Recently, methane bubbling from thermokarst lakes in ice-rich
and organic-rich permafrost regions is included as an additional,
previously not considered methane emission source that is increasing
the rates of northern wetland methane emission by 10–63% (Walter
et al., 2006).
Biogenic methane emissions from wetlands are determined by two
different microbial processes: methane production and methane
oxidation (Wagner, 2008). Methane production is mainly controlled
by quality of soil organic matter and vegetation; methane oxidation
depends strongly on availability of oxygen, while both processes are
influenced by soil temperature and pH (Bartlett et al., 1992; Morrissey
& Livingston, 1992; Christensen et al., 1995; Whalen et al., 1996;
MacDonald et al., 1998; Wagner et al., 2005). These factors are of high
temporal and spatial variability and thus also the CH4 emissions.
Major factors determining the methane emission from Arctic
tundra are vegetation, geology, soils and hydrological conditions
(Bartlett et al., 1992; Gross et al., 1990; Morrissey & Livingston, 1992;
Christensen et al., 2000). The strong correlation between methane
emissions, prevailing vegetation cover, soil moisture is vital for remote
sensing based land cover classifications focusing on the quantification
of methane emission from tundra wetlands. Extensive field knowledge of individual land cover classes in an investigation area allows
the upscaling of methane emission rates from individual study sites to
large study regions. Land cover classifications are a standard
application for remote sensing data and several global or circumarctic classifications for land cover or vegetation types exist. However,
the number of classes, the scale, and the accuracy of these small-scale
maps is not sufficient i.e. for remote northern regions (see e.g. Frey &
J. Schneider et al. / Remote Sensing of Environment 113 (2009) 380–391
Smith, 2007). In their study, Frey and Smith (2007) demonstrate the
very poor accuracy of current coarse-resolution land cover datasets
versus a ground truth dataset from the West Siberian lowlands. Major
limitations for the satellite-based classifications are coarse-scale
satellite data, limited or no ground truth data for very large regions,
and a strong generalization of classes. Their finding of exceptionally
low accuracies i.e. for wetland and water body classification would
pose a fatal error source when trying to estimate methane emissions
from regional northern wetlands based on such data. Therefore, we
decided to generate our own dataset of recent and high-resolution
land cover using high-resolution multispectral data of the Landsat-7
ETM+ sensor for our study area. Within the last 15 years, some studies
on land cover classifications utilizing Landsat remote sensing data
with different thematic focus have been conducted in Alaska and
Canada (Ferguson, 1991; Gross et al., 1990; Joria & Jorgenson, 1996;
Muller et al., 1999; Stow et al., 1998; Brook & Kenkel, 2002). Land cover
classifications of Arctic areas in Russia are rare and most of them have
been accomplished within the last years (Rees et al., 2003; Takeuchi
et al., 2003; Virtanen et al., 2004; Grosse et al., 2006).
In our study we apply remote sensing techniques for the
quantification of methane emission focusing on the tundra region of
the Lena Delta in northeast Siberia. The purposes of this study were:
(i) to classify the land cover types of the Lena Delta based on their
methane emission potential and by using Landsat-7 ETM+ satellite
data; (ii) to determine the spatial distribution and coverage of the
various land cover classes; (iii) to measure the methane emissions of
the major landscape types in the Lena Delta and attribute them to our
land cover classes; and (iv) to quantify the methane emissions of the
individual land cover classes and of the Lena Delta in total.
With our approach we provide a detailed insight into the land
cover and site specific methane emissions of a large, highly heterogeneous tundra wetland landscape in the Arctic and the spatial
and temporal upscaling of this data using remote sensing and GIS
techniques.
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2. Study area
The study area is the Lena Delta, located in Northern Siberia at the
Laptev Sea coast between the Taimyr Peninsula and the New Siberian
Islands (Fig. 1). Occupying an area of about 29,000 km2, it is the largest
delta in the Arctic and one of the largest in the world. The delta is
characterised by a network of small and large rivers and channels, and
more than 1000 islands. The Lena Delta can be divided into three
geomorphologically different terraces and active floodplain levels (Are
& Reimnitz, 2000; Schwamborn et al., 2002; Fig. 1). The active floodplain and the first terrace (1–12 m a.s.l.) are the youngest parts of
the Lena Delta. The first terrace was formed during the Middle
Holocene and mainly occupies the eastern part of the Lena Delta. It is
characterised by the patterned ground of ice-wedge polygons and
relatively ice-rich sediments. The second terrace (11–30 m a.s.l.),
formed between the Late Pleistocene and Early Holocene occupies
about 23% of the delta and is characterised by sandy sediments with
low ice content. The polygonal microrelief is less expressed; thermokarst lake assemblages are typical. The third terrace (30–60 m a.s.l.) is
the oldest terrace in the Lena Delta. It is not a fluvial–deltaic unit but
an erosional remnant of a Late Pleistocene plain consisting of finegrained, organic-rich and ice-rich sediments that accumulated in front
of the Chekanovsky and Kharaulakh mountain ridges in the southern
zone of the study area (Schirrmeister et al., 2003). The surface of the
third terrace is characterised by polygonal ground and thermokarst
processes.
The region is characterised by an Arctic continental climate with
low mean annual air temperatures of −13 °C, a mean temperature in
January of −32 °C, and a mean temperature in July of 6.5 °C. The mean
annual precipitation is low and amounts to about 190 mm (WWIS,
2004). The Lena Delta is located in the zone of continuous permafrost
with a thickness of about 500–600 m (Romanovskii & Hubberten,
2001). The thickness of active layer is usually in the range of 30–50 cm
during summer. The Lena Delta is covered by tundra vegetation of
Fig. 1. Location of the Lena Delta in NE Siberia. The subset map shows the distribution of the three main geomorphological terraces in the delta (based on Schwamborn et al., 2002).
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J. Schneider et al. / Remote Sensing of Environment 113 (2009) 380–391
various types. Major components are grasses, sedges, mosses, lichens,
herbs, and dwarf shrubs (Kutzbach et al., 2004).
The island Samoylov, situated in the central delta (72°22′ N,
126°29′ E), is the main study site for methane emission measurements
in the Lena Delta since 1998 (Hubberten et al., 2006). Samoylov covers
an area of about 5 km2 and is representative for the first terrace and
the floodplains (Boike et al., 2008). The western part of Samoylov is
formed by recent fluvial and aeolian processes. Three floodplain levels
can be distinguished by inundation frequency and vegetation cover.
The sediments are characterised by fine to coarse sands. The Middle
Holocene deposits of the first terrace cover about 3 km2 in the eastern
part of Samoylov. This area is dominated by active ice-wedge formation, low-centre polygons and small thermokarst ponds. The vegetation and soil patterns are complex due to high lateral variability of the
polygonal microrelief consisting of polygon rims and trenches, and
polygonal depressions (Kienast & Tsherkasova, 2001; Kutzbach et al.,
2003).
3. Materials and methods
3.1. Image data and processing
The study was based on land cover classification of three almost
cloud free Landsat-7 ETM+ satellite images covering more than 98%
of the Lena Delta. The acquisition dates are 27 July 2000 (path 131,
rows 8 and 9) and 26 July 2001 (path 135, row 8). Both were taken
approximately at the peak of the vegetation period (snow free
months between June to September). ERDAS Imagine™ software was
used to carry out all image processing tasks. In addition to the ETM+
satellite imagery, we acquired and utilized numerous other ancillary
data for determination of typical land cover classes and field training sites: vegetation field data, soil information, field and aerial
photography.
The three Landsat-7 images were rectified using ground control
points from three already orthorectified Landsat-7 ETM+ images
(August 2000, path 130, row 9; July 2001, path 133, rows 8 and 9)
and by applying a first-order polynomial transformation. The scenes
were resampled to 30 m × 30 m pixels using the nearest neighbour
approach. The RMS error was less than 1 pixel, while the base imagery
has a horizontal accuracy of approximately 50 m. To minimize radiometric differences between the three scenes due to different atmospheric conditions between two acquisition dates, a basic radiometric
and image-based atmospheric correction according to Chavez (1996)
was applied. As a result the image digital numbers were converted to
reflectance values, the effects of the atmosphere, sun illumination
geometry, and instrument calibration on the image data were lowered,
and land cover class signatures across the three satellite scenes were
normalized. Finally, the three scenes were projected to UTM Zone 52
with the geodetic datum WGS 1984 and a mosaic of the Lena Delta was
composed.
Image classifications were conducted using both unsupervised and
supervised techniques. Cloud cover was identified by an unsupervised
classification and masked out from the image mosaic. The unsupervised classification was also used to identify spectrally similar areas
and possible training sites for the supervised classification. The unsupervised ISODATA algorithm was used to derive classifications during
a number of classification runs with a varying number of classes (6 to
40). However, checking with ground truth data revealed that most of
the spectral classes determined in these unsupervised classifications did not represent homogeneous land cover classes. Therefore, a
supervised classification was carried out using the spectral bands 1–5
and 7 (VIS, NIR, SWIR). For the supervised classification, the minimum
distance algorithm was used, because it can be more effective than the
often used maximum likelihood algorithm when the number of training
sites per class is limited (Richards & Jia, 1999). Ancillary data was used
to select the training areas for each class, including topographic maps
(1:200,000), a vegetation and soil map (1:1,000,000; Solomonov et al.,
1998), a geomorphological map (1:500,000; Grigoriev, 1993), and field
knowledge. Our field knowledge comprises almost 10 years of field
work in the delta by us and other German and Russian colleagues,
resulting in an extensive dataset of geological, geomorphological and
biological characteristics, as well as numerous aerial and field photos.
This process resulted in 34 training areas for ten land cover classes.
After evaluation of the classes regarding their methane emission
two classes were merged. The final number of classes is nine. The size
of the training areas varied between 0.09 km2 and 1.6 km2. The
training areas were distributed on the active floodplain and first
terrace (21 sites), on the second terrace (8 sites), and the third
terrace (5 sites). The accuracy assessment (e.g. Story & Congalton,
1986; Congalton, 1991) for our classification was based on 36 validation sites spread over the delta and its terraces. The sites were
selected using a random point selection algorithm. As base data for
our accuracy assessment we generated an image mosaic of Hexagon
satellite images, providing a dataset independent from the Landsat-7
images. The Hexagon satellite series (synonymous with ‘Keyhole-9’)
was part of the United States photographic reconnaissance satellite
program and was launched between 1971 and 1986. The satellites
carried a photographic mapping camera using 9″ film. Almost all
imagery was declassified in 2002 and transferred to the United
States Geological Survey Earth Resources Observation System (USGS
EROS Data Center). Two panchromatic Hexagon images with about
10 m resolution were acquired over the study area on 16th July 1975
and 9th August 1980. The images were rectified to the Landsat-7
mosaic (all with RMSE smaller than 18 m), contrast-stretched, and
then merged into a mosaic covering the majority of the delta.
Landscape changes between the acquisition dates of Hexagon and
Landsat-7 appear to be negligible at the 30 m Landsat-7 image
resolution, except for changes related to differences in the river
water level. The validation was further guided by the 1:200,000
topographic maps and field knowledge. The validation sites were
classified according to our class scheme and then compared in a
correlation matrix to derive an absolute accuracy for our Landsat-7
classification.
3.2. Methane emission rates and upscaling
To relate the derived land cover classes with methane emission
rates, measurements were carried out in a variety of landscape types
in the Lena Delta within the scope of long-term investigations of trace
gas emissions during the years 1999 to 2006. The methane emission
rates of these study sites were determined by closed chamber
measurements (Wagner et al., 2003). The variation limit of the flux
measurements was between 5 and 15%. Due to the large extent of the
study area not all of the identified classes could be studied with
emission measurements in the field. For the missing classes we
adopted site-specific methane emission rates published in the
scientific literature. This method seems appropriate given the good
comparability of site characteristics and the type and limited number
of classes affected by this approach (basically only lake water classes;
see Table 1).
Long-term measurements of more than 1 month have been
conducted at various polygonal tundra sites of the first terrace on
Samoylov Island and sites located on the lower floodplain. For all other
landscape types the methane emission rates are based on a shorter
measurement period. Kutzbach and Kurchatova (2002) measured
methane emission rates in dry tundra sites of the second terrace of the
Lena Delta. We assume that emission rates of other tundra sites with
similar dry characteristics are equally low. From the general characteristics of sandy non-vegetated sites we assume also very low
methane emission rates nearly zero. This assumption is supported by a
measurement of Kutzbach and Kurchatova (2002) at a sandy deflation
cliff in the delta.
J. Schneider et al. / Remote Sensing of Environment 113 (2009) 380–391
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Table 1
Mean daily methane emission rates for July and annual emission rates for all land cover classes in the Lena Delta
Code
Class
Area
%
km²
WT
MT
NV
MDD
DMSD
DG
DT
WB
SW
a
b
c
d
e
f
g
h
i
Wet sedge- and moss-dominated tundra
Moist grass- and moss-dominated tundra
Non-vegetated areas
Moist to dry dwarf shrub-dominated tundra
Dry moss-, sedge- and dwarf shrub-dominated tundra
Dry grass-dominated tundra
Dry tussock tundra
Water bodies
Rivers and coastal waters
Lakes (N 0.36 ha = 4 Landsat-7 pixel)
Thermokarst lakes on 3rd terrace
All other lakes
Shallow water
Vegetated lake margins and shoals
Sandbanks and shoals in rivers and along the coast
Total
8277
2173
1697
1832
3519
610
444
8894
5886
3008d
88.9d
2919.1d
1590
159
1431
29,036
28.5
7.5
5.8
6.3
12.1
2.1
1.5
30.6
66.2
33.8
3.0
97.0
5.5
10g
90g
100
Mean daily emission July
Annual emission
mg m− 2 d− 1
106 g d− 1
mg m− 2 a− 1
106 g a− 1
16.8
17.2
0
58.4a
0.4b
0.4b
0.4b
139.1
37.4
0
107
1.4
0.2
0.2
1452.3
1486.9
0
5048.5
34.6
34.6
34.6
12,020.7
3231
0
9248.9
121.8
21.1
15.4
0c
0
0
–
3.1f
–
9.0
24,900
268
40.3h
0
10.35i
6.4
0
300.7i
3483.8
0
972.14
0
e
2213.6e
782.3
553.9
0
28,208.7
Values for class MDD measured in June.
Values adopted from Kutzbach and Kurchatova (2002); measured in the Lena Delta.
According to Semiletov (1999) methane concentrations in the Lena Delta channels and offshore waters were close to his analytical measurement limit (b 0.015 μM/l). We therefore
set these emissions to zero.
Area of lakes based on Morgenstern (2005).
Value adopted from Walter et al. (2006); measurements cover the whole annual cycle, incl. winter emissions; measured in NE Siberia.
Value adopted from Morrissey and Livingston (1992); measured in Alaskan North Slope region.
Percentage ratio between subclasses is based on visual interpretation of the classification image and the Landsat 7 data.
Values from this study, Wagner et al. (2003), and Spott (2003); all measured in the Lena Delta.
Daily emissions of thermokarst lakes are not included.
The assignment of methane emission rates to water habitats is
more challenging because of the strong diversity of water bodies in
the delta (coastal waters, rivers, and lakes) and their very different
emission characteristics depending on genesis, hydrological properties, cryolithological setting, size, and depth. The area in the delta
covered by water bodies is nearly 8900 km2, and according to
Morgenstern (2005) lakes N0.36 ha occupy about 3008 km2 or 33.8%
of the water surfaces. High emission rates can be expected from most
shallow water areas occurring as vegetated lake margins and shoals.
On the contrary, non-vegetated shoals and sandbanks in rivers, lakes
and along the coast are likely to have very low methane emission
rates. From a visual interpretation of the classification and the
Landsat-7 data we estimate that about 90% of the shallow water
areas consist of sandbanks in the river channels and on the coast, and
only about 10% are vegetated lake margins.
Methane emission rates for the delta channels and offshore areas
are more difficult to estimate due to the dynamic fluvial environment.
According to measurements by Semiletov (1999), rivers and coastal
waters around the Lena Delta had methane concentrations below his
analytical measurement limit (b0.015 μM/l) and thus appear to emit
only traces at best. Therefore we consider emissions from these areas
negligible when compared to terrestrial emissions from the delta.
Therefore, only the methane emission rates of the lakes are included
in our balance. There are different types of lakes in the delta in terms
of lake genesis and substrate. Due to lacking measurements of the
methane emission rates of the various lake types in the Lena Delta, we
adopted rates measured for comparable lakes in Alaska north of 68°N
by Morrissey and Livingston (1992). We are aware that especially
thermokarst lakes located in ice-rich and organic-rich substrates, as
they are exist on the third terrace of the delta, are a large source for
methane emissions by decomposition of old Pleistocene carbon and
subsequent methane ebullition. Therefore, we adopted values for this
kind of thermokarst lakes in the Lena Delta from similar lakes in NE
Siberia (Walter et al., 2006).
Table 1 shows the methane emission rates we used for the calculation of the methane emissions of the Lena Delta. These are the mean
values measured in July; only the rates for the land cover class moist to
dry dwarf shrub-dominated tundra (MDD) have been measured in June.
The daily methane emission of the entire Lena Delta is a sum of the
methane emissions from all individual classes, which in turn are
products of the area of the individual class and the daily methane
emission rate for this class.
To upscale methane emissions from classes with limited field
measurements we developed a ratio-based method. We calculated the
ratio of June–October versus July emissions for the extensively studied
class wet sedge- and moss dominated tundra (WT), assuming that
this ratio is a basic characteristic of the seasonal cycle of methane
emissions in the region and is also valid for other land cover classes.
Then we used the ratio to upscale methane emissions from classes with
short measurement periods towards the full June–October period.
The annual methane emission of the Lena Delta area is a sum of
the emissions from all land cover classes, which in turn are the product
of the area of the individual class and the methane emission rate of
each class within the period from June to October. Based on our measurements in early winter (Oct. 2003), we assume that the methane
emission in winter is about zero (Ganzert et al., 2004). Although
methane is still produced at sub-zero temperatures by microorganisms, this methane can not diffuse through the frozen ground and will
be trapped into the frozen sediments until the next spring (Wagner
et al., 2007). However, based on values adopted from Walter et al.
(2006) we include the methane produced during winter in deep
thermokarst lakes located in ice-rich and organic-rich permafrost,
which is then released in spring.
4. Results
4.1. Supervised classification
Nine land cover classes characterised by their vegetation, surface
moisture, and topography plus one cloud mask class could be defined
for the Lena Delta area:
Wet sedge- and moss-dominated tundra (WT): sites with watersaturated substrate and a nearly continuous cover of sedges, especially Carex aquatilis, and other hydrophilic graminoids growing
in shallow water (e.g. Eriophorum scheuchzeri) or mosses (Fig. 2f).
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J. Schneider et al. / Remote Sensing of Environment 113 (2009) 380–391
Fig. 2. Field photographs showing some of the most important classes: a. mainly non-vegetated areas (NV); b. moist to dry, dwarf shrub dominated tundra (MDD); c. dry grassdominated tundra (DG); d. dry moss-, sedge-, and dwarf shrub-dominated tundra (DMSD); e. moist sedge and moss dominated tundra (MT) and f. wet sedge and moss dominated
tundra (WT; photos AWI).
Moist grass- and moss-dominated tundra (MT): areas are characterised by moist tundra on poorly drained soils and a continuous
vegetation cover of grasses, mosses and dwarf shrubs (Betula nana,
Salix spp.; Fig. 2e).
Moist to dry dwarf shrub-dominated tundra (MDD): this class is
dominated by dwarf shrubs and is found on moist to dry sites. It
occupies large areas of the lower floodplain and is dominated by
dwarf willows; on moist sites cotton grass occurs. Seasonal
inundations of these areas result in a high content of nutrients in
the soils and a dense vegetation cover (Fig. 2b).
Dry moss-, sedge- and dwarf shrub-dominated tundra (DMSD):
well drained sites with sand as predominant substrate, found
often close to cliffs. The vegetation cover can vary: there are
sites dominated by sedges, and cotton grass and mosses as
dominant vegetation with isolated occurring lichens and dwarf
shrubs, other sites are dominated by dwarf shrubs and lichens
(Fig. 2d).
Dry grass-dominated tundra (DG): this cover type occurs predominantly on the lower floodplain, the substrates are mostly
dry and temporary moist after the inundation. The areas are
J. Schneider et al. / Remote Sensing of Environment 113 (2009) 380–391
characterised by grasses (e.g. Deschampsia brevifolia), some sites
are only sparsely vegetated (Fig. 2c).
Dry tussock tundra (DT): this land cover class is characteristic for
dry, very well-drained sites of upper slopes and pingos. The vegetation cover consists of Eriophorum vaginatum tussocks.
Mainly non-vegetated areas (NV): barren or partially vegetated
areas on active river bars, along the coast line, or deflation cliffs.
These sites are mostly sandy and vary in soil moisture (Fig. 2a).
Shallow water (SW): this class consists of shallow recurrent or
steadily inundated areas: a) shallow coastal waters including intertidal areas, shallow waters of riverbanks, and mainly barren
385
sand bars, or b) shallow parts of lakes and rivers with typical
partially submerged vegetation of sedges and hydrophilic grasses.
Water bodies (WB): water bodies include the open water of lakes,
rivers, streams and coastal waters.
Cloud mask: clouds and cloud shadows.
Notably, the land cover classification reflects the different terraces
and floodplains of the Lena Delta (Fig. 3). Nearly one third of the total
area of the Lena Delta is occupied by water bodies (WB 30.6%; Table 1).
Together with the land cover classes SW (5.5%), WT (28.5%) and MT
(7.5%) the wetland classes amount to 72.1% of the Lena Delta area,
indicating the dominance and importance of wetland areas for the
Fig. 3. Supervised classification of the Lena Delta and detailed subset showing the class distribution around Samoylov Island in the central delta.
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J. Schneider et al. / Remote Sensing of Environment 113 (2009) 380–391
delta ecosystem. The composition and distribution of non-water cover
classes strongly varies for the three main river terraces. Whereas the
first and the third terrace are dominated by moist to wet classes, the
second terrace is dominated by classes indicating mainly dry
conditions. The first terrace is mainly composed of WT and MT, but
classes related to active fluvial processes are also abundant (especially
classes NV and SW in the delta apex area and along the major
channels). The second terrace is clearly dominated by the class DMSD,
with some WT and MT in thermokarst basins, and MDD in the
southern part of the terrace. The third terrace is characterised by the
MT and DT mainly in the thermokarst valleys but also on the plateau.
4.2. Upscaling of methane emissions: case study for the land cover class
wet sedge- and moss-dominated tundra (WT)
Within the scope of this study the most detailed measurements
were done for the land cover class wet sedge- and moss-dominated
tundra (WT). There are several reasons for concentrating on the
detailed and systematic investigation of the methane emissions from
this class. First, from our previous measurement campaigns we know
that this land cover class is the most important source of methane in
the Lena Delta. Second, extensive ancillary data about the soil
composition, soil moisture, soil physics, vegetation, microrelief, and
microbiology are available for the systematic investigation of the
determining factors for methane emission (Fiedler et al., 2004;
Kutzbach et al., 2004; Wagner et al., 2005; Liebner and Wagner,
2007). Third, a high-grade long-term dataset based on daily summer
methane emission measurements from two representative areas
within this class were available for our calculations (e.g. Wagner
et al., 2003). These preconditions allow the investigation of small-scale
heterogeneities of important parameters and their influence on the
methane emission from this individual land cover class. The land cover
class WT consists of polygonal microrelief and lakes of different sizes
with high emission rates in wet polygon centres and the vegetated lake
margins, and lower emission rates from drier polygon rims and open
water ponds. Therefore, we determined methane emission rates for
this class at a sub-class scale by doing separate measurements for the
various microrelief and water body features (Table 2). An overevaluation of extreme flux events, which can lead to a significant
error in the up-scaling, could be largely excluded based on the available
long-term flux record for this class. Supervised classification of
helicopter-borne, visible wavelength aerial imagery (ca. 0.3 m ground
resolution) was used to assess the percentage coverage for each subclass in the class WT on Samoylov Island. The weighted calculation
shows that methane emission rates of this class range from 10.8 to
23.3 mg CH4 m− 2 d− 1, with a mean at 16.8 mg CH4 m− 2 d− 1 in July.
Table 2
Daily methane emission rates measured in different sub-classes of the land cover class
WT (wet sedge- and moss-dominated tundra) in the months June to October
Sub-class
Very wet sites
Methane emission (mg CH4 m− 2 d− 1)
Cover
(%)
7.8
Dry sites
62.2
Water
15.2
Overgrown water
14.8
Mean
Min
Max
Mean
Min
Max
Mean
Min
Max
Mean
Min
Max
June
July
August
September
October
54.1
13.7
89.4
2.5
0.7
4.6
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
93.7
60.3
119.6
4.7
3.3
6.2
4.1a
2.0a
7.9a
40.3a
25.6a
59.9a
44
32.9
72.6
6.1
3.1
11.4
7.9a
3.3a
15.7a
48.1a
31.9a
67.1a
17.9
7.0
25.8
2.1
0.6
4.0
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
11.2
2.3
25.3
1.7
0.7
3.9
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
The percentage of sub-class cover was determined by aerial image analysis of key sites
on the first delta terrace.
n.d.—not determined.
a
Values from Spott (2003).
Table 3
Methane emissions of the land cover class WT (wet sedge- and moss-dominated tundra)
in the months June to October (weighted calculation)
Methane emission (mg CH4 m− 2 d− 1)
Wet sedge- and
moss-dominated tundra
Junea
July
August
Septembera
Octobera
Mean
Minimum
Maximum
8.25
2.15
14.05
16.82
10.84
23.25
15.55
9.72
25.07
3.86
1.31
6.43
2.76
0.88
6.28
a
Due to missing values for the sub-classes ‘water’ and ‘overgrown water’ the
weighted calculation is based only on values for the sub-class types ‘very wet sites’ and
‘dry sites’.
Temporal variations during the vegetation period are another
central objective of long-term investigation of methane emissions in
the Lena Delta. While methane emission rates for the polygon rims
and centres have been determined in the field for the period from June
to October, the rates for the open water and vegetated rims of lakes
have been determined only in July and August. We conducted a
weighted calculation of the methane emission rates for the different
months for this land cover class (Table 3).
4.3. Upscaling of methane emissions in the Lena Delta
The methane emission rates vary strongly among the individual
land cover classes. While the highest amounts are emitted by the
class MDD, followed by the vegetated lake margins and the classes
MT and WT, the lowest rates are emitted by the classes with dry
substrate characteristics (DMSD, DG, and DT; Table 1). The land cover
classes WT and MT represent the wetlands of the Lena Delta. The
methane emission rate of these wetlands is 16.8 mg CH4 m− 2 d− 1
(weighted calculation). The daily methane emission of the entire
Lena Delta was calculated with 300.7 × 106 g (standard error b15%;
Table 1).
Based on our measurements we calculated temporal trends of
methane emissions for the class WT (Table 3). In the data we observe a
fast increase of emissions in June, then a maximum in July, and the
slow decrease of methane emission rates in the following months. The
total methane emission of the class WT for the measurement period
from June–October (153 days) amounts to 1452 mg CH4 m− 2. The
calculation of the methane emissions from all other land cover classes
during the vegetation period is based on the ratio of the methane
emissions of each individual land cover class and the methane
emission of the class WT.
The upscaling of emissions for the Lena Delta is a weighted calculation using the methane emission rates of the individual classes
(Table 1). The highest amounts of methane are emitted by the classes
WT (12 × 109 g CH4 per year) and MDD (9.2 × 109 g CH4 per year),
followed by MT (3.2 × 109 g CH4 per year). The various “dry” tundra
classes cover a large area of the Lena Delta and their contribution to
the total methane emission of the delta is very low (0.2 × 109 g CH4 per
year) compared to the “moist” and “wet” tundra classes.
5. Discussion
5.1. Land cover classification
A common method for a general land cover classification of large
heterogeneous datasets is the automatic unsupervised classification
based on a chain algorithm and the subsequent labelling of land cover
classes with real land cover features (Joria & Jorgenson, 1996; Stow
et al., 1998; Cihlar, 2000). Such unsupervised classifications with a
very large number of classes proved unsuitable for the land cover
classification of wetlands with a focus on methane balancing, as
usually only a limited number of measurement sites are available.
Furthermore, the classes obtained with such an unsupervised
approach are ecologically very heterogeneous and thus unsuitable
J. Schneider et al. / Remote Sensing of Environment 113 (2009) 380–391
387
Table 4
Error matrix, user's, producer's and overall accuracy for supervised classification of the Lena Delta
Reference data
Classified data
WT
MT
MDD
DMDS
NV
SW
WB
Total
Producer's accuracy (%)
WT
MT
MDD
4
1
2
1
1
3
1
DMDS
NV
1
SW
WB
Total
User's accuracy (%)
1
7
3
5
6
5
5
4
36
57.1
66.7
60
83.3
100
80
100
1
5
5
1
5
80
4
3
66.7
6
50
5
100
Overall accuracy (%)
κ
6
83.3
5
80
5
6
83.3
77.8
0.74
for the upscaling of local datasets. Thus, we used a supervised
classification approach based on a relatively small number of classes
for the classification of the Lena Delta. We obtained the best results
with the supervised minimum distance algorithm using nine classes.
The Landsat 7 derived classes reflect especially the local soil moisture
and vegetation conditions, both important parameters for the
methane emissions of a site (MacDonald et al., 1998; Wagner et al.,
2003; Kutzbach et al., 2004). Therefore, the land cover classes could be
related to locally measured methane emissions.
Within this study we used class area calculations based on the land
cover classification of a Landsat 7 image mosaic from July 2000 and
2001. This mosaic provides a snapshot of the mid-summer situation in
the highly dynamic environment of the Lena Delta. Seasonal variations, like changes in vegetation cover density, soil moisture, or the
annual inundation of the floodplain levels during spring flood, are
currently not considered in our calculations. However, by carefully
characterizing and choosing classes based not only on vegetation but
also on geomorphological and hydrological properties we can strongly
decrease possible temporal heterogeneities in the classification.
The accuracy assessment based on the Hexagon satellite images
indicated an overall relative accuracy of 66.7%. A first error matrix
indicated accuracies for individual classes ranging from 20 to 100%
(data not shown). The poorest producers' accuracy of 20% was
achieved for the class SW which was frequently misclassified as WB.
This is related to the fact that there is a temporal difference between
the classified dataset and the validation dataset, resulting in different
water levels and thus an erroneous accuracy assessment for shallow
water classes. However, it is usually not difficult to spectrally separate
water classes from other land cover, and also to differentiate between
deep and shallow water using Landsat-7 data. By visually checking the
questionable SW and WB validation sites in the Landsat-7 data we
found that our Landsat-7 classification was correct and could adjust
our validation dataset accordingly. These results were now included
into the final error matrix (Table 4). Our accuracy assessment of the
Landsat-7 supervised classification indicates a reasonable well overall
accuracy of 77.8% (Kappa = 0.74) for such a large and remote study area.
Relative accuracies for individual classes ranged from 50 to 100%.
Misclassifications usually occurred within neighboring classes with
higher similarity in environmental parameters (e.g. between WT and
MT). A considerable uncertainty is left in this relative accuracy assessment because the Hexagon-based reference data may not be more
reliable than the Landsat-derived land cover maps.
Despite the described challenges, we were able to classify the land
cover of the Lena Delta and to relate these classes to methane emission
rates based on currently available field data. This land cover classification is the first encompassing the entire Lena Delta at high
resolution.
5.2. Case study for the land cover class wet sedge- and moss-dominated
tundra (WT)
The small-scaled heterogeneity of vegetation cover, soils and water
balance in the Lena Delta have a direct effect on the methanogenesis
and the amount of the emitted methane. The most detailed balance of
methane emissions could be realised for the land cover class WT. It
mostly consists of typical polygonal tundra and covers large areas of
the Lena Delta. We demonstrated that drier sites consisting of polygon
rims dominate the polygonal tundra, covering nearly 62% of this class.
Bartlett et al. (1992) and Christensen et al. (1995) measured lower
methane emissions for dry tundra sites in polygonal tundra than in this
study (Table 5). The mean daily methane emission rates of the
polygonal lakes of the Lena Delta are within the range of the methane
emissions from polygonal lakes at other study sites (Table 5). The
importance of lakes for the methane emissions from tundra and the
Table 5
Methane emission [mg CH4 m− 2 d− 1] of various sub-classes in different studies
Sub-class region
Wet polygon
centres
Polygon rims and
other dry sites
Polygonal
lakes
Vegetated
lake margins
Tussock tundra
Reference
Northeast Siberia, Lena Delta
Yukon-Kuskokwim Delta, Alaska
Siberian and European tundra
North Slope of Alaska
North Slope of Alaska
North Siberia
North Slope of Alaska
Northeastern Siberia
Northeastern Siberia
Northeastern Siberia
93.7
144 ± 31
46.8 ± 5.9
90
–
–
–
290
–
7.92 ± 3.6 (2004)
1.2 ± 1.92 (2005)
5.28 ± 4.8 (2006)
4.7
2.3 ± 1.1
2.3 ± 0.7
–
–
–
–
–
–
4.1
0.4–16
–
21
1.28 – 16.32
7.6 ± 1.3
3.1
–
–
40.3
89
–
–
–
–
79.3
–
–
This study, Wagner et al. (2003), Spott (2003)
Bartlett et al. (1992)
Christensen et al. (1995)
Whalen and Reeburgh (1990)
Kling et al. (1992)
Zimov et al. (1997)
Morrissey and Livingston (1992)
Nakano et al. (2000)
Corradi et al. (2005)
Van der Molen et al. (2007)
–
–
–
–
–
–
–
–
–
–
–
195.8 ± 80.7
−0.48 ± 0.24 (2004)
0.24 ± 0.00 (2005)
−4.32 ± 1.44 (2006)
388
J. Schneider et al. / Remote Sensing of Environment 113 (2009) 380–391
global methane emissions is not yet sufficiently clarified. According to
Semiletov et al. (1996), the limnic ecosystems of the tundra are one of
the most important recent methane sources to the atmosphere. This is
confirmed by a study of Walter et al. (2006) focusing on the ebullition
of methane from thermokarst lakes. On the contrary, Morrissey and
Livingston (1992) determined that lakes have a considerably lower
methane emission potential than other sites in the tundra. Bartlett
et al. (1992) suggest a close connection between methane emissions
and the size of the lakes. Small lakes (less than 10 km2) emit significantly more methane than the large lakes (more than 10 km2). In
contrary, Kling et al. (1992) reported in their study that there is no
correlation between the methane emission of a lake and its size, depth,
or its latitudinal location. For deep thermokarst lakes the frozen
sediment, in which they are growing, and sediment carbon content are
important factors for their methane emission potential. Icy and
organic-rich sediments can provide additional old carbon for methanogenesis in these thaw lakes resulting in higher emissions (Zimov
et al., 1997). However, the importance of the vegetated lake margins for
the methane balance of the tundra is well known. The mean daily
methane emissions estimated by Bartlett et al. (1992) and Morrissey
and Livingston (1992) amount double the methane emissions of vegetated lake margins in our study. Differences in methane emissions
between these studies appear largely due to differences in the location
of the study sites and the individual site and lake characteristics. The
correlation between temperature and the plant mediated transport of
methane in the vegetated lake margins determined by King et al.
(1998) can be an explanation for higher methane emissions of vegetated lake margins found by Bartlett et al. (1992) and Morrissey and
Livingston (1992) comparing to the results of this study.
The mean daily methane emission rate of wet polygon centres in
the Lena Delta is 93.7 mg CH4 m− 2 d− 1 (Table 5). Rates about one third
higher were measured by Bartlett et al. (1992) at wet meadow sites,
and nearly half of this rate by Christensen et al. (1995) at wet tundra
sites. Both sites are comparable to the sites in the Lena Delta because
these sites are also characterised by water saturated soils and
vegetation of Carex spp. and Eriophorum spp. The measurements in
the Lena Delta and those of Whalen and Reeburgh (1990) at wet
tundra sites are highly consistent. The methane emissions reported by
Nakano et al. (2000) for water saturated sites in the tundra are much
higher than the methane emissions in our study. Differences between
the measurements appear also due to the different length of the
investigation period. If the study period is short, the methane
emissions strongly reflect short-term weather conditions (Christensen, 1993). In our study the methane emission rates have been
measured during field trips of several weeks since 1998. Summarizing,
the differences in methane emission at different study sites are
obvious, and the measured methane emissions from the various subclasses of the land cover class WT in the Lena Delta are within the
range of those reported from analogous areas in the high latitudes.
The mean daily methane emission of the class WT amounts to
16.8 mg CH4 m− 2 d− 1. The high emission rates of the wet polygon
centres are not reflected in the emission of this class due to the low
percentage (7.8%) of the area of this particular sub-class type in this
class. In contrast, the low methane emissions of the drier sub-class
and the lakes have a strong influence on the total amount of methane
emission from this class.
Generally, the length of the measurement period is an important
factor for the quality and the applicability of measured methane
emission rates for temporal and spatial upscaling. Most of the previous
studies were conducted during July and August only (Whalen &
Reeburgh, 1990; Bartlett et al., 1992; Martens et al., 1992; Christensen
et al., 1995). Some provide only imprecise information about the investigation period (Morrissey & Livingston, 1992; Nakano et al., 2000;
Takeuchi et al., 2003). This also results in difficulties when comparing
these methane emission rates to our long-term multi-annual measurements of the class WT. A study by Christensen et al. (2000)
covering an investigation period from the middle of June to the end of
August is an exception. Their study covers the high-arctic Zackenberg
Valley in Greenland, which strongly differs in climatic and substrate
conditions to the sites in the Lena Delta. In Zackenberg Valley, the fast
increase of the emissions at the beginning of the vegetation period is
missing and the methane emission is nearly zero mg CH4 m− 2 d− 1 in
June. Methane emission rates throughout the year are considerably
lower than in the Lena Delta.
5.3. Upscaling of methane emissions in the Lena Delta
The local-scale heterogeneity in vegetation and soil moisture and,
thus, in methane emission was analysed only within the land cover
class WT. The coverage of this class in the Lena Delta is 28.5% and the
percentage of methane emission is 42.6% (Fig. 4). The small-scaled
mosaic of the class MT could not be investigated with the same level of
detail. The coverage of this class in the Lena Delta is 7.5% and the
percentage of methane emission is about 11.5% (Fig. 4). In this study,
the land cover class MDD emits 32.8% of the methane in the Lena Delta
but covers only 6.3% of the delta (Fig. 4). Although the vegetated lake
margins cover only 0.55% of the Lena Delta area, they contribute to 2%
of the delta emissions.
Methane emission rates of rivers in the Lena Delta are estimated to
be low. Results of Heikkinen et al. (2004) and Whalen and Reeburgh
Fig. 4. Percentage of methane emissions of individual land cover classes based on the total methane emission of the Lena Delta.
J. Schneider et al. / Remote Sensing of Environment 113 (2009) 380–391
(1990) indicate that arctic rivers and thermokarst lakes are important
methane sources. However, a study of CH4 in the surface waters of the
Lena Delta by Semiletov et al. (1996) shows that the rivers and coastal
waters are not significant factors in the present methane budget of the
Lena Delta area. Thermokarst lakes are with 7.8% of the total emission
important contributors to the annual methane emissions of the Lena
Delta. Their importance becomes obvious comparing their annual
emission to those of all other lakes. Only 3% of all lakes are thermokarst lakes in ice-rich and organic-rich permafrost, but they probably
emit nearly the 3-fold of the methane emission of all other lakes
within the Lena Delta. Although the open water areas cover 30% of the
Lena Delta, their total share on the methane emission is only 10.5%
(Fig. 4).
Compared to the methane emissions measured by Corradi et al.
(2005) at tussock sites of the Kolyma river floodplain the mean daily
methane emissions (0.4 mg CH4 m− 2 d− 1) of dry tussock sites in the
Lena Delta are relatively low but they are well within the range of the
methane emission reported by Van der Molen et al. (2007; Table 5).
According to Heikkinen et al. (2004), the methane emission rates of
dry sites are in general very low or negative. In the Lek Vorkuta
catchment they estimated methane emissions between −8.1 and
10.5 mg CH4 m− 2 d− 1, averaging around zero. The more dry sites cover
nearly 15% of the delta area, and their methane emission amounts to
only 0.6% of the total Lena Delta emission (Fig. 4).
The mean daily methane emission of the Lena Delta is 10.35 mg
CH4 m− 2 d− 1. This value is about 20% of the value for the Arctic tundra
calculated by Whalen and Reeburgh (1990) (52 mg CH4 m− 2 d− 1).
The mean daily methane emissions of the wetlands in the Lena Delta
amount to 16.8 mg CH4 m− 2 d− 1. That is below the range of 40 to 50 mg
CH4 m− 2 d− 1 estimated by Christensen et al. (1995) for northern wetlands. Earlier estimates have been much higher, for example the
calculation by Matthews and Fung (1987) of about 200 mg CH4 m− 2 d− 1.
The methane emissions presented here are based on measurements in the period from June to October. We did not measure during
the whole winter time. We assume that the methane emission during
the cold season is nearly zero due to the low temperatures. This
assumption is based on measurements in October, which show the
methane emission rates decreasing to zero (Ganzert et al., 2004). The
discussion about the amount of methane emitted in winter is still
ongoing. Winter methane fluxes have been estimated only in North
America and West Siberia (Whalen & Reeburgh, 1988; Dise, 1992;
Melloh & Crill, 1996; Panikov & Dedysh, 2000). The reported winter
emission rates amounted from about 4 to 41% of the annual methane
fluxes. Zimov et al. (1997) demonstrated that methane is produced in
Arctic lakes under ice during winter. The gas is largely released to the
atmosphere from holes in the ice during winter or during water
column circulation after the ice melt in spring. According to Zimov
et al. (1997), the north Siberian lakes could release about 75% of their
annual methane emission during winter. Christensen et al. (1995)
underline that the methane emissions in winter are not well investigated and that they may contribute significantly to the total
emission from permafrost environments.
However, the results of a study by Worthy et al. (2000) in the
Hudson Bay Lowland support our observations that the largest
emissions occur in July and August decrease in September and
become very weak in October. The emissions become observable again
in June and are around zero or negative in the winter period.
The annual methane emission of the Lena Delta amounts to about
0.03 Tg. The emissions presented here are very conservative and most
probably underestimate the annual gas release since we chose very
conservative values for classes that were not measured directly in the
Lena Delta and did not include possible emissions during the winter
due to lacking base data. A comparison of the annual methane
emission of the Lena Delta with those of other study sites is difficult
due to lacking upscaling efforts of the methane emissions from
measurement sites to larger study areas.
389
6. Conclusions
The results of this study show that remote sensing and supervised
image classification are excellent tools to provide a base for the
upscaling of local methane emission measurements in high-latitude
landscapes. The supervised classification of the Landsat 7 ETM+ images
is particularly suitable for detection of ecosystem types in the Lena Delta.
The methane emission of tundra environments is influenced by
numerous factors, e. g. microrelief, soil moisture, temperature, amount
and quality of organic matter, thickness of active layer, availability of
oxygen and nutrients, and vegetation. The tundra land cover type is
directly or indirectly influenced by these parameters, enabling the
correlation of local methane measurements with land cover classes and
the upscaling of emission rates to the entire Lena Delta. The applied
supervised minimum distance classification was very effective with the
few ancillary data that were available for training site selection. It is
possible to easily adapt our land cover classes and the Lena Delta
methane budget to new field data that will become available during the
ongoing research efforts in the Lena Delta ecosystem.
The three main river terraces of the Lena Delta were found to have
different associations of land cover classes. The first terrace is characterised by wet sites and lakes, the second terrace appears to be
drier and differs also in vegetation, and the third terrace is dominated
by moist sites. Accordingly, the first terrace has the highest methane
emission potential. There is a strong variation in between the
individual land cover classes regarding the methane emissions. The
methane emissions of the classes in the Lena Delta are within the
currently known natural range of emissions from tundra sites. Taking
our multi-scale approach into account, the methane source strength
of certain tundra wetland types is expected to be lower than calculations based on coarser scales. This study is the first attempt to
assess the methane emission of the Lena Delta based on satellite data
and field measurements. Although there is still large potential for
intensifying research on resolving uncertainties of methane measurements for different land cover types, on the estimation of variability of emissions from sub-class features, and on expanding
emission measurements to all classes in the field, our results suggest
that the Lena Delta contributes significantly to the global methane
emission because of its extensive wetland areas.
The approach we used for the balance of methane emission
contributes to the improvement of the global balance of methane
emissions.
Acknowledgments
The authors wish to thank the Russian–German field parties
during several expeditions to the Lena Delta since 1998. Special
thanks go to all our Russian partners, in particular Dimitry Yu. Bolshiyanov (Arctic Antarctic Research Institute), Alexander Yu. Dereviagin (Moscow State University), Mikhail N. Grigoriev (Permafrost
Institute Yakutsk), Dmitri V. Melnitschenko (Hydro Base Tiksi) and
Alexander Yu. Gukov (Lena Delta Reserve). Many thanks go to Lars
Kutzbach for critical reading of an early version of the manuscript. We
are also very grateful to the detailed and constructive comments of
four anonymous reviewers.
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