overview and update on remote sensing technology for redd...remote sensing • unique technique of...
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Overview and update on remote sensing technology
for REDD
Yasumasa HirataForestry and Forest Products Research Institute
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Forest monitoring using remote sensing
• Unique technique of forest monitoring widely and retrospectively.
• Essential tool for identify deforestation and forest degradation in developing countries
Satellite imagery in Manaus, Amazon
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Gap between remote sensing and definitions of forest degradation and deforestation
ForestForest
Non ForestNon Forest
- Degradation
- Deforestation
Threshold
+/- Conservation
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Observation Techniques toward REDD
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Satellite data
Wall-to-wall
Pixel-based classification
Object-oriented classification
Interpretation
Sampling
Pixel-based classification
Object-oriented classification
Interpretation
Monitoring of forests by remote sensing
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Satellite data
Wall-to-wall
Sampling
Forest monitoring using satellite remote sensing
No leakage in the area.Coat is large.Difficulty of acquiring cloud-free data.Applicability for local policy is large.
Accuracy for sampling rate.Coat is effective.Acquiring cloud-free data is relatively easy.Applicability for local policy ?
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Object-oriented classification
• The object-oriented approach is effective in segmenting an area that consists of various land cover types into objects with extensions of similar properties (Lamonaca et al. 2008).
• Classification results that is similar to human interpretation
• Advantage of handling by object (segment)
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The challenges of forest monitoring
Deforestation (Area)
Deforestation (Carbon stock)
Degradation Incremental change
Forest vs. Non-forest
Classification of forest types
Crown extraction by high resolution satellite
More challenging !
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Two types of forest monitoring required for REDD
Year
Carb
on s
tock
present
Retrospective monitoring Forward-looking monitoring
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Monitoring of deforestation
ó Extracting changes of land use category
ó Using properties of reflectance of each category
ó Comparing multi-temporal
ó Available to identify forest type change
Deforestation in MalaysiaLandsat imageryUpper 1989 yr, lower 2001 yr
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Monitoring of forest degradation
• Various causes of degradation
• Selective (illegal) logging
• Forest fire
• Intensive shifting cultivation
• development
• Development of method as to each cause of degradation is required
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Detection of illegal deforestation using ALOS-PALSAR
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Monitoring of sifting cultivation by ASTER images(provided Mr. Naoyuki Furuya, JIRCAS)
2002/2/9
2003/3/16
2005/2/1
2006/3/8
Object-oriented classification
Image pre-processing
6 years - shifting cultivation distribution map
Monitoring of sifting cultivation for six years
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Monitoring of forest degradation
Technology already exists and many countries have beenusing such technologies to develop forest carbon inventories(for example, remote sensing technologies).
There is a need to expand these technologies for monitoringforest degradation and associated GHG emissions andchanges in carbon stocks.
Although some gaps exist, waiting for replacement by anotherpromising technology will be a time-consuming process.
Chair’s Summary of Key Messages from the Informal Meeting ofExperts on Methodological Issues relating to Reducing Emissionsfrom Forest Degradation in Developing Countries
20 - 21 October 2008, Bonn, Germany
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Which one do you select?
Conventional RS
Field survey
LiDARSAR
VHR satellite
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Kee
Keeping sharp eyes out for the Earth
QuickBird - 0.61m10. 2001
IKONOS – 0.82m9. 1999
SPOT-5 – 2.5m5. 2002
ALOS PRISM – 2.5m1. 2006
KOMPSAT– 1.0m7. 2006
WorldView– 0.5m9. 2007
THEOS – 2.5m10. 2008
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2. Estimating carbon stock from interpretation of QuickBird data
1.Mapping of illegal logging using multi-temporal 2.5 m-resolution satellite images
Mapping of illegal logging
PRISM2006/11/27 PRISM2008/3/1
Comparison of CD between ground and satellite measurements
0
5
10
15
20
25
30
0 5 10 15 20 25 30
衛星
計測
(m)
地上計測(m)
QuickBirdSPOT
Forest degradation using high resolution satellite data(provided Mr. Naoyuki Furuya, JIRCAS)
Ground measurement
Sate
llite
mea
sure
men
t
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木木
Intensity
First Pulse
Last pulse
One shot of laser
GPSGPS
IMUIMU
TimeTime
Tim
e
A part of the laser beam reflects on canopy .The rest goes through canopy and reflects on the ground.
0
200
400
600
800
1000
1200
0 200 400 600 800 1000 1200
DCMから得られた林分材積(m )3
現地
調査
によ
る林
分材
積(m
)3
Source: Hirata et al (2008) Journal of Forest Planning 14 Stand volume from LiDAR
Measurement of ground and canopy surface
R = 0.93
3-D forest measurement with LiDAR as alternative of ground-based survey
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Combination of several factors• Data availability
– Acquisition (spatial, temporal), seasonality
• Data property– Ground resolution, optical vs. radar (vs. dimension)
• Monitoring cost– High resolution < very high resolution ?
• Cause of forest degradation
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Thank you for your attention!