int. j. remote sensing, 2000, vol. 21, no. 6 & 7, 1139–1157
Satellite estimation of tropical secondary forest above-ground biomass:
data from Brazil and Bolivia
M. K. STEININGER
Department of Geography, University of Maryland, College Park,
Maryland 20742, USA
Abstract. This paper reports on a test of the ability to estimate above-ground biomass
of tropical secondary forest from canopy spectral reflectance using satellite optical data.
Landsat Thematic Mapper data were acquired concurrent with field surveys conducted
in secondary forest fallows near Manaus, Brazil and Santa Cruz de la Sierra, Bolivia.
Measurements of age and above-ground live biomass were made in 34 regrowth
stands. Satellite data were converted to surface reflectances and compared with
regrowth stand age, biomass and structural variables.
Among the Brazilian stands, significant relationships were observed between
middle-infrared reflectance and stand age, height, volume and biomass. The canopy
reflectance-biomassrelationshipsaturatedat around 15.0kg m2, or over 15 years of age
(r> 0.80, p< 0.01). In the Bolivian study area, no significant relationship between
canopy spectral reflectance and biomass was observed. These contrasting results are
probably caused by a low Sun angle during the satellite measurements from Bolivia.
However, regrowth structural and general compositional differences between the two
study areas could explain the lack of a significant relationship in Bolivia. The results
demonstrate a current potential for biomass estimation of secondary forests with
satellite optical data in some, but not all, tropical regions. A discussion of the potential
for regional extrapolation of spectral relationships and future satellite imagery is
included.
1.
Introduction
The proliferation of human settlements in the Amazon basin results in the conversion of large
areas of mature tropical forest to landscapes primarily consisting of pasture, agriculture and
secondary forest. Most land use in the Amazon is characterized by high rates of land abandonment
and re-clearance, yielding mosaics of land under cultivation and secondary vegetation of different
stages of regrowth (Uhl et al. 1988, Turner et al. 1993, Moran et al. 1994). Current estimates of the
annual carbon release to the atmosphere by tropical land use are around 1.6 gigatons (Schimel et al.
1996, Schimel 1998). Fearnside (1996) estimated that in 1990, 0.27 gigatons of carbon were
released to the atmosphere from the burning of forest and cerrado in the legal Brazilian Amazon
alone.
An unknown amount of carbon is re-sequestered in secondary forests growing in fallowed or
abandoned agricultural lands. Debate continues over whether the many abandoned lands in the
Amazon are actually supporting rapid secondary forest regrowth (Lugo 1988), or whether most do not
have a chance to revert to forest (Myers 1991). There are also uncertainties about fallow periods and
rates of biomass accumulation during regrowth. Because of these uncertainties, we are unable
International Journal of Remote Sensing
ISSN 0143-1161 print/ISSN 1366-5901 online © 2000 Taylor & Francis Ltd
http://www.tandf.co.uk/journals/tf/01431161 .html
1140
M. K. Steininger
to determine the net impact of land use on carbon sequestration in the Amazon. While
current remote sensing efforts such as the NASA Landsat Pathfinder Tropical
Deforestation Project (Lawrence and Chomentowski 1992, Lambin 1994) seek to provide
precise estimates of tropical deforestation, they will not provide information on the
subsequent patterns of land cover and utilization.
Analysis of optical satellite data, such as those from the Thematic Mapper (TM)
sensor on the Landsat platform, permits accurate estimation of deforestation areas and
rates. Most local studies of deforestation report accuracy levels of over 95% (Roy et al.
1991, Sader et al. 1991, Steininger 1996), and several global deforestation monitoring
programs have been implemented during the past decade (Lawrence and Chomentowski
1992, Lambin 1994). Progress has also been made in estimating the area of secondary
forests with high resolution optical data. The estimation of regrowth biomass over large
areas with satellite imagery would, however, enable many additional questions about the
ecological functioning of natural and human-modified landscapes to be addressed,
including the net carbon exchange associated with tropical agriculture.
Three independent studies using TM observations have reported similar changes in
canopy spectra with age over the first 15 years of forest regrowth in the Brazilian Amazon
(Foody and Curran 1994, Moran et al. 1994, Steininger 1996). Typically, visible (TM
channel 3, 0.63-0.69 mm) reflectance is low for all ages of regrowth while near-infrared
(TM channel 4, 0.76-0.90 mm) reflectance increases for four to eight years and then
decreases for the following five to ten years of forest regeneration. Reflectances in both
middle-infrared TM channels (channel 5, 1.55-1.75mm; channel 7, 2.08-2.35 mm)
gradually decrease throughout the first 15 years of regrowth. However, the most reliable
estimates of regrowth age are made when images from many years are available (Kimes
et al. 1998).
These common trends in regrowth canopy reflectance with age have been attributed
to the changes in canopy leaf area and geometry as secondary forests regrow. Field
studies of secondary forests in the Amazon and elsewhere show that, for recovery from
light to moderate use, leaf area rapidly increases, with light capture often over 80% within
five years of regrowth (Jordan 1989, Saldarriaga and Luxmoore 1991). Thus visible
reflectance is low for most secondary forests over a few years old. Increases in leaf area
during early (< 5 years old) regrowth cause an increase in near-infrared reflectance via
multiplicative scattering.
Middle-infrared radiation is not absorbed by plant pigments and, due to lower leaf
transmissivity, is less subject to multiplicative scattering than is near-infrared radiation.
The gradual decrease in middle-infrared reflectance throughout the first 14 years of
regrowth and the decrease in near-infrared reflectance in older (> 8 years old) regrowth
has been attributed to increased canopy shading caused by an increasingly complex
canopy geometry. Applications of spectral mixture modelling, where multispectral images
are decomposed into estimates of proportions of leaf cover, background cover and shade,
have been applied to demonstrate changes in canopy shade among tropical forest types
(Shimabukuro and Smith 1991, Adams et al. 1995). This has also been applied to
Advanced Very High Resolution Radiometer (AVHRR) imagery, where similar patterns of
reflectances among Amazonian forest types have been observed in its middle-infrared
channel 3 (Shimabukuro et al. 1994, Lucas et al. 1999).
Leaf ageing has also been shown to reduce near-infrared reflectance for both crops
and several Amazonian tree species (Gausman et al. 1973, Lin and Ehleringer
Global and regional land cover characterization
1141
1982, Rock et al. 1994, Roberts et al. 1998). Roberts et al. (1998) have reported lowered
near-infrared reflectance for leaves from Amazonian caatinga trees which have epiphyll
growth or have been damaged. Leaf reflectances in the near-infrared of both Protium
heptaphyllum and Pradosia schomburgkiana with heavy epiphyll growth were nearly half
those with little to moderate epiphyll growth. Roberts et al. argue that such differences in
leaf spectral properties account for spectral differences among different types of mature
forest. Such effects on leaf spectra could also play a role in the differences in canopy
reflectances among early regrowth dominated by short-lived shrubs and trees and older
regrowth with forest species with significant leaf necrosis and epiphyll growth. This poses
a challenge to the assumption of non-variant spectral end members in the mixture
modelling approach to image decomposition.
A brightness-based distinction of regrowth appears to be possible only for stages of
regrowth when the canopy changes drastically, namely the first 14 years of regrowth
during which the canopy progresses from low shrubs to a tall multi-layered forest. Yet
within these stages, it is logical that if infrared canopy reflectance is related to regrowth
stand parameters such as leaf area, canopy height and complexity, as well as leaf
parameters such as leaf age, necrosis, epiphyll growth, then canopy reflectance should
be related to stand age. Since older and taller regrowth is usually of higher biomass, then
infrared canopy reflectance should also be related to stand biomass. While one study has
reported a poor relationship between near-infrared reflectance and stand biomass for a
series of Puerto Rican regrowth (Sader et al. 1989), there are no comparisons of regrowth
biomass with respect to middle-infrared reflectance. The research reported in this paper is
a test of the potential for estimation of tropical secondary forest above-ground biomass
with Landsat TM images using data from a series of stands near Manaus, Brazil and
Santa Cruz de la Sierra, Bolivia.
Three study areas included samples of secondary forests regrowing in abandoned
pasture and agricultural fields, mostly manioc in Brazil and rice and corn in Bolivia. The
two study areas in Manaus have an average annual temperature of 25.6C, precipitation of
2400 mm yr 1 and a dry season from July to September (Sioli 1984, Leemans and
Cramer 1991). The soils at AM10, the northern study area along the AM10 and BR174
highways ( 6 0 W 2 5 0 N), are mostly clayey Oxisols (EMBRAPA-CPAC 1981, Dias and
Nortcliff 1985). The second Brazilian study area is Lago Janauaca (60 15 W, 330 S), 40
km south of Manaus, where a large caboclo community practices rotational agriculture on
soils classified as Plinthic Dystric Podsols (EMBRAPA-CPAC 1981). The Bolivian study
area lies in the Yapacani and Surutu basins in western Santa Cruz, along the new Santa
Cruz-Cochabamba highway. The area, centred at 6330 W 1 7 3 0 S, receives around
1600mm of rain and has an average annual temperature of 2 3 C (Roche and Rocha
1985). The winter is dry, with seven months with less than 100 mm of rain, and
experiences strong, cool winds originating in the South Atlantic and the Pacific and lasting
three to five days (Ronchail 1986). The soils at Surutu can be grouped into dissected
terraces and alluvial plains. The soils of the terraces are mostly Quartzipsammentic
Haplothorps on dissected terraces to the north and Typic Paleudults on the piedmont to
the southwest (Montenegro Hurtado 1987).
2. Methods
2.1. Field surveys.
20 secondary forest stands in Brazil were visited from September to November 1995,
and 14 stands in Bolivia were visited from May to June 1996. The secondary
1142
M. K. Steininger
forest stands were all cases of regrowth in abandoned small (< 10 ha) agricultural fields
and pastures (table 1). Most of the stands had bordering mature or secondary forest, and
all stands were dominated by woody vegetation. Plots ranging from 0.07 to 0.10 ha in size
were surveyed in each stand, and structural measurements of all trees with a diameter at
breast height (dbh, 1.3 m above ground) greater than 5 cm were made. Volumes were
estimated using a tree form factor of 0.62 (Brown and Lugo 1990, Brown et al. 1995).
Canopy height was estimated as the mean plus two standard deviations of the heights of
all trees in the stand. This estimate approximates the height of the taller canopy trees but
not unusually tall trees in the stand.
All structural and biomass data were calculated and compared for pioneer and climax
genera. Following Uhl (1987), Swaine and Whitmore (1988) and Faber-Langendoen and
Gentry (1991), the terms ‘pioneer’ and ‘climax’ are used here to refer to trees of different
life history strategies. The term pioneer refers to trees which rapidly colonize disturbed
areas and rapidly senesce when shaded by over-storey trees. Based, in part, on Uhl
(1987), Saldarriaga et al. (1988) and Faber-Langendoen and Gentry (1991), genera
recorded as pioneer in the Brazilian stands for this study are Bellucia and Miconia
(MELASTOMATACEAE), Vismia (GUTTIFERAE), Cecropia (MORACEAE), and Isertia (RUBIACEAE).
Genera recorded as pioneer in the Bolivian stands are Miconia (MELASTOMATACEAE),
Vernonia and Senecio (COMPOSITAE), Piper (PIPERACEAE), Psidium (MYRTACEAE), Guadua
(GRAMINEAE), Psychotria (RUBIACEAE), Cecropia and Pourouma (MORACEAE),
Pseudobombax, and Ochroma (BOMBACACEAE), and Heliocarpus (TILIACEAE). All other
trees recorded are considered climax, and thus this is a broad group which includes many
late successional taxa.
A series of allometric equations derived from destructive samples of other neotropical
secondary forests were applied to estimate the biomass of each measured tree (table 2).
The equations were chosen because they are based on similar genera to those in the
surveyed stands and because they enabled a specification of wood density. The
allometric equations used were from the works of Uhl (1987) for trees shorter than 16m,
Scatena and Silver (1993) for softwooded pioneer trees taller than 16 m, and Saldarriaga
et al. (1988) for hardwoods taller than 16 m. The latter group was further divided into five
wood density classes, ranging in specific density from 0.42 to 0 . 8 5 g m m 3 (dry
weight/green volume). The majority of sampled trees was identified to genus, thus
allowing for a general grouping based on wood density and tree form. Taxonomic
identification was to either genus or family, referring to Gentry (1993) and Killeen et al.
(1993). Tree wood density values for common genera were obtained from Hidayat and
Simpson (1994), Brown et al. (1995) and Finegan (1996).
Above-ground standing live biomass density (hereafter referred to as stand biomass)
was calculated as the sum of tree biomass estimates divided by plot area. Sampling
errors for stand biomass were estimated from two stands in Bolivia, one five-year old and
one 15 year-old, following the approach used by Brown et al. (1995). In these stands,
0.28 and 0.30ha plots were surveyed, marking each 0.01 ha sub-plot. Based on the
running means and the coeffcient of variation of the standard errors of the sub-plot
biomass estimates, sampling errors for both stands were estimated to be 9% for plot
sizes of 0.70 ha and larger. This estimate was taken as the error for all sampled stands.
Further discussion of stand structure and composition and field estimation of stand
biomass is provided in Steininger (1998).
2.2. Image geo-registration
Prior to conducting the field surveys, TM images from 1991 for Manaus and 1995 for
Santa Cruz were obtained from the NASA Landsat Pathfinder Humid
Global and regional land cover characterization
1143
Table 1. Stands surveyed in all study areas. S.T. =short-term agriculture, L.P.= long-term
pasture, M.F.=medium-fallow agriculture, S.F.=short-fallow agriculture (one case in
Brazil), and L.T.= long-term agriculture (one case in Brazil). S/B indicates clearing
by the slash-and-burn method.
Stand
Stand
Stand
Sampled
Land
Id.
age (y)
Area (ha)
area (ha)
use
4
0.09
M.F.
Land use history, notes
Bolivia, Piedmont
S3
10
S4
15
S12
20
S13
4
S14
10
S15
12
Bolivia, Alluvial
S5
25
4
2
2
4
5
0.08
0.10
0.10
0.10
0.10
S.T.
S.T.
S.T.
S.T.
S.T.
3
0.10
M.F.
S6
15
3
0.80
M.F.
S7
5
4
0.10
L.P.
S8
6
4
0.10
M.F.
S10
8
3
0.10
M.F.
S16
8
S17
15
S18
5
Brazil, AM10
5
4
4
0.10
0.28
0.30
S.T.
S.T.
S.T.
A2
A3
A5
8
4
2
0.07
0.07
0.08
S.T.
L.T.
S.T.
A6
20
A7
23
A8
20
A9
15
A10
12
A11
12
A12
7
Brazil, Janauaca
6
5
4
4
2.5
3
1.5
0.07
0.09
0.10
0.07
0.10
0.08
0.08
S.T.
S.T.
S.T.
L.P.
S.T.
S.T.
L.P.
J1
J2
J3
J4
30
26
15
8
6
4
3
2
0.10
0.10
0.10
0.07
L.P.
S.T.
S.T.
S.F.
J5
J6
12
15
4
3
0.08
0.09
S.T.
L.P.
J7
20
8
0.07
L.P.
J9
10
2
0.10
L.P.
J10
5
1.5
0.08
L.P.
J11
5
2
0.08
S.T.
10
4
12
Forest, 4+ cycles of S/B, 1 year rice, 7
year fallow
Forest, S/B, 1 year rice
Forest, S/B, 1 year rice
Forest, S/B, 1 year rice
Forest, S/B, 1 year rice
Forest, S/B, 1 year rice
Forest, 4+ cycles of S/B, 1 year rice, 5
year fallow
Forest, 4+ cycles of S/B, 1 year rice, 5
year fallow
Forest, 3 cycles of S/B, 1 year rice, 5
year fallow, 7 year pasture
Forest, 4+ cycles of S/B, 1 year rice, 5
year fallow
Forest, 3 cycles of S/B, 1 year rice, 8
year fallow
Forest, S/B, 1 year manioc
Forest, S/B, 1 year manioc
Forest, S/B, 1 year rice
Forest, S/B, 1 year rice
Forest, S/B, 6 year rice
Forest, S/B, seeded w/rice
only+abandoned, sandy hilltop
Forest, S/B, 1 year rice
Forest, S/B, 1 year rice
Forest, S/B, 1 year pasture
Forest, S/B, 7 year pasture
Forest, S/no-burn, no cultivation
Forest, S/B, 1 year pasture
Forest, S/B, 6 year pasture
Forest, S/B, 10 years pasture
Forest, S/B, 1 year manioc
Forest, S/B, 1 year manioc
Forest, 4 cycles of S/B, 1 year manioc, 3
year fallow
Forest, S/B, 1 year manioc
Forest, S/B, 1 year manioc, 5 year fallow,
S/B, 5 year pasture
Forest, S/B, 1 year manioc, 3 year fallow,
S/B, 10 year pasture
Forest, S/B, 1 year manioc, 3 year fallow,
S/B, 5 year pasture
Forest, S/B, 1 year manioc, 3 year fallow,
S/B, 6 year pasture
Forest, S/B, 1 year manioc
1144
M. K. Steininger
Global and regional land cover characterization
1145
Tropical Deforestation Project (Lawrence and Chomentowski 1992). These images were
geographically registered using GPS measurements collected during previous site visits.
The corrected positional errors of the imagery were estimated to be within 30 m, based on
the GPS points used in registration. During the field surveys, additional GPS
measurements were collected along roads, clearance edges and canopy gaps within
stands.
2.3. Image atmospheric correction
For this study, the 6S atmospheric correction program (Vermote et al. 1997) was
used. This is a multiple-stream simulation of atmospheric absorption and scattering based
on user-defined inputs of optical depth and aerosol composition. Estimates of optical
depth over dark, closed canopy forested sites were derived from a program developed at
the University of Maryland Institute of Advanced Computer Studies (UMIACS) (table 3).
This program employs the approach of Kaufman and Remer (1994) by taking differences
in top-of-atmosphere (TOA) reflectances in the blue and middle-infrared channels for
forest sites to estimate optical depth in a given satellite image (Fallah-Adl 1996). Aerosol
composition was defined as 80% water-soluble, 15% soot, 5% dust-like and 0% oceanic
(Holben 1996 personal communication).
A comparison of estimated surface reflectances for dark water and closed-canopy
primary forest, surface features that can be assumed to have constant reflectance, in
images from different years is shown in figure 1. The 6S corrected spectra produced
between-year differences of one to two per cent reflectance in all channels except
channel 7.
2.4. Analysis of canopy spectra
Surveyed stands were identified in the geo-referenced imagery. Means of the
corrected stand reflectances in each of the TM channels were calculated and plotted
against stand above-ground biomass and structural variables. Linear regressions of each
channel reflectance against biomass were performed using a general linear model (Neter
et al. 1990). An F test was used to test for an effect of study area on the regression.
Finally, step-wise regression was used to compare biomass estimation using single
versus multiple band reflectances. Based on the correlation matrix, stand canopy
reflectances were plotted against the other stand structural characteristics to assist
interpretation of the biomass-canopy reflectance relationship.
Table 3. Summary of Landsat 5 TM images and aerosol optical depth estimates. Optical
depth was estimated with the University of Maryland Instituteof Advanced Computer
Studies correction program (UMIACS O.D.).
Study area
Scene date
AM10, Janauaca 15 August 1988
Surutu
8 August 1991
20 September 1995
25 July 1986
9 July 1992
5 August 1996
Path/
Solar
zenith
row
()
0.49mm
0.66mm
231/62
43
0.16–0.28
< 0.01–0.19
231/72
44
38
68
69
66
0.24–0.33
0.33–0.52
0.12–0.21
0.16–0.24
0.38–0.46
0.15–0.32
0.32–0.51
0.01–0.19
0.16–0.23
0.36–0.45
UMIACS O.D.
1146
Figure 1.
M. K. Steininger
Means of Thematic Mapper digital numbers (DN) and atmospherically-corrected
surface reflectances for dark targets.
3. Results
3.1. Patterns of biomass and canopy reflectance in Brazil
Most of the early regrowth stands surveyed in Brazil were dominated by a mix of
Vismia, Miconia and Bellucia (Steininger 1998). None of the stands surveyed in this study
were dominated by Cecropia, in contrast to the early regrowth stands surveyed by Foody
and Curran (1994). The most common taxa in the Brazilian stands older than 10 years of
age were Inga (MIMOSOIDEAE), Goupia (CELASTRACEAE), Didymoponax (ARALIACEAE), and
genera of the ANNONACEAE, LAURACEAE and BURSERACEAE. The range of total aboveground live biomass among the stands in Brazil was from 0.2 to 20kgm 2 .
The highest correlations among stand variables were those among stand age, basal
area, volume and canopy height (table 4). These variables were all inversely correlated to
canopy reflectance in all three infrared bands. The highest correlations between canopy
reflectances and structural variables were between middle-infrared reflectance and stand
basal area (r2 = 0.715) and biomass (r2 = 0.701).
Reflectances in the visible channels rapidly decreased from over 0.06 in pastures
Global and regional land cover characterization
1147
1148
Figure 2.
M. K. Steininger
Means of estimated canopy reflectances in Thematic Mapper channels 3, 4, 5 and
7 versus above-ground biomass for all regrowth stands surveyed in Brazil.
and agricultural fields to below 0.03 in low to high biomass regrowth stands (figure 2(a)).
Reflectances in the near-infrared were around 0.30 for young, low biomass stands and
decreased thereafter to around 0.27 for the older, high biomass stands (figure 2(b)).
Reflectances in both middle-infrared channels decreased linearly with both stand age and
biomass (figure 2(c),(d), table 4).
The best spectral estimator of biomass among the Brazilian stands was an
exponential relationship with channel 5 reflectance for all stands and mature forest (r =
0.714, p< 0.05, n=18). For all stands less than 1 5 k g m 2 , a linear relationship best
predicted stand biomass from channel 5 reflectance (r = 0.854, p< 0.01, n = 12; figure 3,
table 5). Step-wise regression only slightly increased this relationship by incorporating
channels 4 and 3 in the regression model. Because of this, the linear model based on
channel 5 alone was used to estimated regrowth biomass in the two Brazilian study areas
(figures 4 and 5). The estimated average biomass of secondary forests at Janauaca is
7.2kgm2 and at AM10 is 7 . 6 kg m 2 .
Observation of reflectance changes over a 4- and 7-year time period showed a
decrease in middle-infrared reflectance for almost all of the stands surveyed, although the
magnitude of this decrease was only from near zero to 0.045 reflectance over 7 years
(figure 6).
Global and regional land cover characterization
1149
Figure 3. Above-ground standing biomass of secondary forest regrowth versus Thematic
Mapper channel 5 reflectance based on stands surveyed in Brazil. The linear regression
model is based on stands up to 15 kgm2.
Table 5. Linear and exponential regressions of regrowth above-ground standing biomass
versus Landsat TM channel 5 reflectance based on all the stands surveyed in Brazil.
The linear model is based on stands up to 15.0k g m 2 .
Equation
Y = 4.166e+5e(
73.936X) Y=50.77
287.62X
Slope n
18
13
p
<
<
0.01
0.01
% error
r
0.10
0.08
0.714
0.854
Y= above-ground standing dry weight (kgm2). X = Landsat TM
channel 5 atmospherically corrected reflectance. e = natural
logarithm.
3.2. Patterns of canopy reflectance in Bolivia
In Bolivia, stands were generally of lower stature and biomass. Stand canopy heights
ranged from 8 m in an 8-year old to almost 30 m in a 15-year old stand. Stand total
above-ground biomass in Bolivia ranged from 2.4 to 13.4kgm2. The youngest stands in
Bolivia were dominated by a shrub layer of Vernonia, Senecio, Psychotria and Miconia
(Steininger 1998a, b). Stands up to 10 years old were dominated by Ochroma, Cecropia,
Heliocarpus and Inga. Cecropia was the most common genus among all the stands in
Bolivia.
Many of the older stands in Bolivia had an upper canopy composed of the same
softwooded pioneer tree taxa which dominated the younger stands. These were mostly
Cecropia spp., Pourouma spp., Heliocarpus spp., and Ochroma pyrimidale. In stands that
were not dominated by these genera, Anadenanthera spp. and Swartzia spp. were most
common in more open canopies over a dense shrub layer. These stands had relatively
lower infrared reflectances among the sample of Bolivian regrowth than similarly aged
stands dominated by the softwood trees.
The correlation coeffcients among stand structural variables reported in table 4 reveal
further differences between the regrowth in Brazil and Bolivia. In the Brazilian study sites,
all height variables for both pioneer and climax trees were highly correlated with stand
total biomass (r2>0.79), particularly tree height variables (r2>0.89). This strong
relationship between stand height variables and biomass was not found in Bolivia. Among
the stands surveyed at Surutu, the correlation between
1150
M. K. Steininger
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AM10 (Amazonas, Brazil). Cleared land is shown in white, mature forest is shown
in grey, colours are estimates of regrowth above-ground biomass. This image was
produced using the linear regression model reported in table 5.
stand height variables and biomass ranged from 0.34 to 0.73. Furthermore, stand
biomass was most highly correlated with the pioneer canopy height, revealing the
greater importance of pioneer trees in the biomass of the Bolivian regrowth stands.
The canopy spectral reflectances of the secondary forests in Bolivia were
Global and regional land cover characterization
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.
_w
60°10'W
Figure 5. Distribution of secondary regrowth above-ground standing biomass in 1995 at
Lago Janauaca (Amazonas, Brazil). Cleared land is shown in white, mature forest is
shown in grey, colours are estimates of regrowth above-ground biomass. This image
was produced using the linear regression model reported in table 5.
Figure 6. Changes in regrowth canopy reflectance versus age in 1995 for all stands surveyed
in Brazil. Open triangles are reflectance differences between 1995 and 1988, full triangles
are reflectance differences between 1995 and 1991.
1152
Figure 7.
M. K. Steininger
Means of canopy reflectances in Thematic Mapper channels 3, 4, 5 and 7 for all
regrowth stands surveyed in Bolivia.
consistently higher than those in Brazil. Among stands of up to 7 years old in Bolivia,
visible reflectance was from 0.04 to 0.06. Near-infrared reflectance was from 0.45 to 0.70
and middle-infrared reflectance was from 0.22 to 0.30 (figure 7). Moreover, the patterns of
change in canopy spectra with age reported in the 1995 Brazilian data in this study, and
in other studies, were not observed in the Bolivian data. Only near-infrared reflectance
showed a slight decline with stand age and biomass density.
4. Discussion
The patterns of canopy reflectance among the regrowth stands surveyed in Brazil
agree with those previously reported for regrowth near Manaus and in eastern Para
(Foody and Curran 1994, Moran et al. 1994, Steininger 1996). In this and earlier studies,
most secondary forest stands of 15 years and older appeared spectrally similar to nearby
mature forest. The optical band most sensitive to canopy changes during succession was
the middle-infrared. Visible reflectance was low throughout the chronosequence. Nearinfrared reflectance was high for all stands, presumably because of high canopy leaf
cover. In Landsat TM data, the 1.55-1.75/am band (channel 5), is more sensitive than the
2.1-2.3/am band (channel 7).
Global and regional land cover characterization
1153
Stands surveyed in Brazil demonstrated a rapid progression from a canopy
dominated by shrubs to an even tree canopy dominated by softwooded pioneers, to an
uneven canopy dominated by later successional trees. The most common pioneer trees
in the Brazilian stands are Cecropia spp., which have a planophile distribution of large
leaves. These trees rapidly senesce once later successional species such as Miconia
spp., Inga spp., Bellucia spp., and Goupia glabra reach the canopy. Spectral canopy
models suggest that it is primarily the changes in the upper canopy structure, i.e. canopy
height, upper-canopy leaf area density and angle distribution, during these stages of
regeneration that cause the observed increases in canopy shading and decreases in
middle-infrared reflectance.
Since the scenes were all acquired from nearly the same time of year (table 3), Sun
angle variation is an unlikely explanation of between year differences in the retrieved
surface reflectances. Soil moisture is also an unlikely explanation since all images were
from the late dry season and since canopy cover was high for most stands. Between-year
differences in rainfall may have caused between-year differences in leaf area, which could
vary near- and middle-infrared canopy reflectances among regrowth stands of similar age
and biomass stocks. Figure 6 shows that the estimated changes in middle-infrared
reflectance over 4 and 7 years are around 0.01 to 0.02, and the pattern of reflectance
versus stand biomass in figure 2 agrees with this. Thus between-year errors of 0.01 to
0.02 reflectance in atmospheric correction remain a limit to accurate estimation of
biomass changes using multi-date optical imagery.
There are at least three possible explanations for the significant relationship between
stand age, biomass and middle-infrared reflectance in the two study areas in Brazil and
the lack of one in the Bolivian study area. The first is the low Sun angle during the 1996
satellite pass over Santa Cruz (table 3). A second hypothesis is that a relationship
between canopy infrared reflectance and stand variables such as age, height and
biomass is not valid for regrowth in areas of tropical deciduous forest, as in Santa Cruz,
Bolivia. Measurements of leaf area were not collected in this study, although it is possible
that canopy leaf senescence during the dry season reduces the effects of upper-canopy
structure on surfaces reflectances. In Maraba, mature forest showed increases in nearinfrared reflectance during the dry season, becoming nearly as bright as forest regrowth
and suggesting a leaf flush of under-storey vegetation in the dry season (Bohlman 1998).
Another possible cause for the different spectral relationships to regrowth biomass in
Brazil and Bolivia is a difference in the development of regrowth canopy structure
between the two areas. Among the stands surveyed in Bolivia, the stage of succession
dominated by pioneer trees persists through the first 20 years of regrowth, considerably
longer than in Brazil. Other than Cecropia spp., these trees included Pourouma spp.,
Ochroma pyrimidale and Heliocarpus spp., all which typically have large leaves and
Cecropia-like planophile leaf angle distributions (Uhl 1987, Finegan 1996). Canopy
heights of the Bolivian regrowth were lower than those in Brazil. Furthermore, canopy
height was strongly correlated to stand biomass in Brazil and poorly correlated to biomass
in Bolivia (table 4). Thus, in Bolivia, while the stands increased in height and biomass with
age, the structural changes of the upper canopy probably had a lesser effect on canopy
shading and thus were poorly related to stand age and biomass. The compositional
differences between the Brazilian and Bolivian regrowth suggest that differences in
canopy structure could account for the contrasting patterns of infrared reflectance and its
relationship to vegetation properties in the two study areas.
1154
M. K. Steininger
The potential for monitoring changes with multi-date imagery will most certainly
improve with data from the sensors onboard the soon to be launched Earth Observing
System (EOS-1) and Landsat-7 satellites. Specifically, improved radiometric sensitivity
and atmospheric correction based on simulation models and data internal to the images
will allow more precise comparisons of multi-date imagery. The Moderate Resolution
Imaging Spectroradiometer (MODIS), to be onboard EOS-1, has 36 channels in visible to
thermal bands. Atmospheric properties and their effects on imagery can be precisely
modelled using the thermal channels to estimate columnar water vapour and the visible
and middle-infrared channels to estimate aerosol concentration (Justice et al. 1998). The
Multi-Angle Imaging Spectroradiometer (MISR), also to be onboard EOS-1, is expected to
improve on inputs to aerosol optical models by estimating particle size distribution and
discriminating spherical from non-spherical particles (Diner et al. 1988).
These corrections apply not only to MODIS and MISR imagery, but the estimated
atmospheric water vapour and aerosols can also be used to correct higher resolution
images from alternative sensors. Advanced Spaceborne Thermal Emission and
Reflection Radiometer (ASTER), also on EOS-1, will provide 15 to 30 m resolution
imagery in the visible and near-infrared bands (Yamaguchi et al. 1998). Landsat-7 will
have the same spectral channel configuration as Landsat-5, although is planned to follow
the same orbit as EOS-1 within a half-hour (Goward and Williams 1997). Thus, in most
instances the correction of a Landsat-7 image based on atmospheric properties estimated
from virtually synchronous image data from EOS-1 will be possible.
Many research questions continue to drive us to produce better regional estimates of
tropical secondary forest distribution andbiomass. Observations of high resolution optical
imagery to date have demonstrated consistent patterns of change in canopy spectra with
tropical regrowth age, with the exception of the Bolivian results in this study. The results
of this study suggest that the potential for use of optical satellite data for above-ground
biomass estimation of tropical secondary forests is similar to that for age estimation. With
data from EOS-1, isolation of atmospheric effects from estimates of canopy reflectance
will greatly increase the potential for extrapolations of spectral relationships over large
areas or over multiple dates. This will require a better understanding of the possible
variability of canopy structure for similarly aged patches of tropical regrowth.
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