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RSS Remote Sensing Solutions GmbH 2012
Application of multisourceremote sensing data for
estimating and monitoring tropical forests
carbon stocks
Dr. Vanessa Keuck
Prof. Dr. Florian SiegertPeter NavratilSandra EnglhartDr. Jonas FrankeDr. Uwe Ballhorn
RSS Remote Sensing Solutions GmbH
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Forest Inventories, plot sampling
Collection ofdata of
forest type
tree species
dbh
biomass per ha
carbon per ha
geo-location
AGBcalculation
allometricequation formoist tropicalforests (Chaveet al. 2005)
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LiDAR derived products
250
t/ha
250
t/ha
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Photo: F. Siegert
Assessment of carbon stock using SARdata
Field
inventoryLiDAR
Modeling Upscaling(SVM, NN, Regression)
SAR
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Upscaling using SAR
LiDAR is used to up-scaleforest inventories
Dipterocarp - 3
80
90
100
110
120
130
140
830300 830350 830400 830450 830500 830550
X(m)
Z(m)
140forest inventoryplots
3,970LiDAR biomassestimations
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Multifrequency SAR biomass maps
Calibration R=0.79 The model is valid up to
300 t/ha Independent validation using
10% of the LiDAR estimates
(randomly distributed)(R=0.55)Published: Englhart et al. (2011) in RSE
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Photo: F. Siegert
Assessment of carbon stock usingRapidEye data
Fieldinventory LiDAR RapidEye
Stratification
Modeling
Upscaling
Classification
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Land Cover map based on RapidEye imagery
Overall accuracy: 87.8%
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From land cover to carbon stock
Establishment of a reference emission level by the use of the Carbon Calculator: Database contains biomass values from over 200 publications LiDAR based land cover specific AGBs (in progress) Open for integration of in-situ biomass values
Carbon Calculator
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AGB map based on RapidEye imagery
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Forest Disturbance AssessmentChange Detection
22.05.200910.20.201021.06.201029.07.2012
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Forest Disturbance AssessmentSMA Results
Soil Fraction
RGB: 3/5/2
22/05/2009
GV Fraction
NPV Fraction
1000 m
RGB: Soil/NPV/GV
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Forest MonitoringDeforestation and forest degradation mapping
Published: Franke et al. 2012 in JSTAR
validation using video data from flight campaigns:Overall accuracy: 91.5%
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Conclusion
Precise, reliable and consistent forest inventory data are
most important
Combined with LiDAR data estimation of abovegroundbiomass for small areas is possible, also change detection
LiDAR based forest disturbance measurements have a high
potential
Large area up-scaling using multi-frequency SAR data iswith limitations possible (estimation accuracy)
High resolution satellite data, such as RapidEye, allowstimely and accurate detection of deforestation anddegradation
For forest disturbance measurements the crucial point is the
temporal resolution
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Thank you for your attention
www.rssgmbh.de