the development of a fine resolution, continental scale...
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The Development of a Fine Resolution, Continental Scale Forest Monitoring System using SAR Imagery
Bruce ChapmanJet Propulsion Laboratory
NASA LCLUC meeting Sept 20-22, 2000
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Players and Partners" Processing
� NASDA/Earth Observation Research Center (M. Shimada)" NASDA/Earth Observation Research Center (A. Rosenqvist)
� NASA/JPL (S. Saatchi)� EC/JRC (F. Degrandi)
" Users
� UC Santa Barbara (L. Hess)� Max Planck Institute for Biogeochemistry (R. Zimmermann)� INPE (L. Dutra)� UMD (S. Prince)
" Others...
� USDA - Int. Inst. of Tropical Forestry (E. Helmer)
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Objectives of the Study" Prototype inexpensive SAR processing
With focused science objective,show that inexpensive and timely processing is possible usingCOTS software and an array of inexpensive PC's running linux
DLT
Server
Disk Storage
PC
PC
COTS software
gigabit ethernet
gigabit ethernet
SCSI
III
5 Mb/s
operator
internet
640
Mb/
s
1000 Mb/s
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ALOS
" NASDA mission" L-band polarimetric SAR" Two optical instruments" Launch : 2003" Two data relay satellites " ALOS Research proposal accepted
� Image all of South America every 3 weeks for duration of mission
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Objectives of the StudyComplete L-band Radar image of forested areas in South America (93-96)
Multiple coverage by JERS-1 SAR in most locations
Also, forests in Southern Africa
GRFM
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Objectives of the StudySimple land cover map
ALOS SAR will be better at discriminating some classes than JERS
- forest
- non-forest
- inundated forests
- open water
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Objectives of the StudyFill in gaps in Landsat coverage
ALOS will acquire data over all of South America every three weeks.
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Science Implications" Regional Wetland Mapping
Rosenqvist et al, 1999Jau River, 1995-1996
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Science Implications
JERS-1 radar imagechange detection
Comparison Sept 1995 / May 1996
yellow : 2db brighter
purple : no change
green : 2db darker
Land Cover Change
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Heritage of the Research
" GRFM / JAMMS project
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Methods" Simple land cover classes
� L-band radar is sensitive to forest structure and the resulting scattering mechanism
" diffuse scattering : Forest (-5.5 to -8.5 db)" specular scattering : non-forest/water ( darker than -9 db)" double bounce : flooded forest (brighter than -5 db)
� these scattering mechanisms result in distinct radar backscatter values
" Classification can be performed at time of processing.
" Dual Pol ALOS will be better at distinguishing scattering mechanisms.
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Methods" Raw signal processing
� COTS software� control of processing priority and quality� strip map processing� mosaicking integrated into processing� classification integrated into processing� multiple output products
" projection (geographic, UTM, WRS) , resolution
" processing benchmark for future systems
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Methods
" Experimental ALOS prototype measurements� Change detection� Interferometry processing� Terrain correction� Biomass
" Biomass from derived structure" Measurement confusion
� double bounce (flooded forest)� low vegetation specular scatter (influenced by soil moisture)� moisture in canopy
" Dual pol L-band on ALOS can eliminate some of this confusion
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Data Plan
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Work Schedule" Year 1 (00-01) :
� integrate hardware and software components� test processing
" Year 2 (01-02):� operational processing� testing and validation of derived products
" Year 3 (02-03) :� completion of image processing
" Year 4 : ALOS is launched (June 2003)