Logging & Remote Sensing
Sebastian Schnobrich
GPHY 426 Remote Sensing
Fall 2014
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Landsat 7 ETM+ imagery of logging segments in the eastern
Brazilian Amazon.
Importance of Remote Sensing In Logging and Forest Management
~ The ability to monitor large areas of forest with remote sensing is
unparalleled.
~ Precise monitoring of our forests is increasingly important, as much
illegal logging is still taking place.
~ Our forests, particularly our rainforests, play immense roles in the
carbon and water cycles.
Impacts of logging on the canopy and the consequences for
forest management in French Guiana
This study used medium-resolution satellite imagery (SPOT 4&5) over 15 blocks of
forest and over 3300 hectares (81.55 acres) in two forests, to correlate canopy
openings with logging intensity from 2008 to 2010.
Location map of the studied forests
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Canopy openness and unit areas per
logged tree were calculated with
logging statistics and GPS mapping. A
20% canopy opening for a logging
intensity of 3.5 trees ha-1 was found,
along with the average canopy
opening per harvested tree being 601
m2.
A general linear model was created to
evaluate the relationship between
logging intensity, canopy damage and relief at multiple scales.
At a larger scale, such as the management-unit level, no notable effect from the
variables was found. At a local scale however, a more significant correlation was
found.
Conclusion
With a local harvesting intensity of 8 trees per hectare on flatter terrain, such as a
plateau, an opening of 33% or less is possible (at 85% probability). On terrain
with more relief a similar canopy openness threshold can only be obtained when
harvesting 5 or less trees per
hectare.
Remote sensing of selective logging impact for tropical forest
management
This study investigated the possibility of creating a system to monitor and detect
selective logging activities in tropical forests. It’s based in a semi-deciduous,
100,000 hectare (247,105.38 acre) forest in the southwest Central African
Republic. This forest has protected areas and also areas dedicated to logging.
A multitude of images
were used for this study:
six multispectral SPOT
images and two thematic
mapper images, along
with field information.
The two TM images were
taken five years apart,
allowing for the study of
forest regeneration. The
SPOT images were used to
assess the impact of the season, geometry of acquisition and spatial resolution.
While it was basically impossible to tell if a single tree fall was due to logging, it
was easy enough to identify logging activity specifically by the concentrated large
gaps in tree canopy and the semi-linear clearings of skid trails.
Surprisingly, seasonal and atmospheric effects did not greatly affect the
detectability of the logging areas. The sensor viewing and sun illumination angles
played a much larger role, as more that 40% of the logging areas could be missed
when these conditions (known a geometry of acquisition) were not desirable.
Conclusion
More than 50% of the logging trail network was still visible five years after last
activity, even with rapid canopy closure.
Logging trail length according to TM images, 1 and 5 years after logging As more time
passed, the image’s spatial resolution became critical, as the visible contrast
between the trails and
forest vanished
quickly. On an image captured immediately after logging more than 95% of the
trails were visible
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but after
five years only 34% of the trails were visible.
Effects of geometry of acquisition on SPOT images of logging trails in the study area.
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Remote sensing of selective
logging in Amazonia
This study combined Landsat 7 enhanced
thematic mapper plus (ETM+) reflectance
data and texture analysis with detailed
field study of forest canopy damage, in
order to determine the sensitivity of
remote sensing to selective logging in
Amazonia. The field study measured
ground damage and canopy gap
fractions. It was found that the logging
method used (conventional or reduced
impact) had a great effect on canopy
damage and regrowth rates.
GIS coverages of conventional and
Log decks were the most obviously
damaged areas on the ground and in
satellite
imagery but they only represented
1-2% of the total harvested area. Other features such as
Reduced impact logging treatments.
tree-fall gaps, roads and skid trails
were difficult to recognize with
textural analysis or
reflectance data and could only be
resolved in intensively logged areas within 0.5 years after
harvest.
When the canopy gap fraction
was less than 50% forest damage largely couldn’t be resolved
at all. It was determined that the
Landsat ETM+ imagery didn’t have the necessary resolution
for quantitative studies of logging
damage, at least in this environment.
Conclusion
Landsat imagery may be useful for broadly determining logged forests but more
detailed studies will likely require more detailed remote sensing data. Impacts of
this land usage on a continental scale remain poorly understood.
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Area
integrated forest canopy
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fractions.
Conclusion
gap
~ Terrain with more variation, or with more relief, cannot be logged as intensively
as flatter terrain while still maintaining the same amount of canopy opening.
~ As time passes after the logging activity has ceased, spatial resolution is critical
in discerning logging trails from forest.
~ Landsat imagery is primarily useful in separating logged areas from non-logged
areas. More detailed data is required for more specific research.
References
Asner, Gregory P., Michael Keller, Rodrigo Pereira Jr., and Johan C. Zweede. "Remote Sensing of
Selective Logging in Amazonia: Assessing Limitations Based on Detailed Field Observations, Landsat ETM,
and Textural Analysis." Remote Sensing of Environment 80.3 (2002): 483-96. Print.
Guitet, Stéphane, Sophie Pithon, Olivier Brunaux, Guillaume Jubelin, and Valéry Gond. "Impacts
of Logging on the Canopy and the Consequences for Forest Management in French Guiana."
Forest Ecology and Management 277 (2012): 124-31. Print.
Wasseige, Carlos De, and Pierre Defourny. "Remote Sensing of Selective Logging Impact for Tropical
Forest Management." Forest Ecology and Management 188 (2004): 161-73. Print.