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Detection of Decadal Change in Alaskan Wetlands
Using PALSARand JERS SAR Data
Detection of Decadal Change in Alaskan Wetlands
Using PALSARand JERS SAR Data
Jane Whitcomb and Mahta Moghaddam, University of MichiganKyle McDonald and Erika Podest, Jet Propulsion Laboratory
Acknowledging Bruce Chapman, JPL
Jane Whitcomb and Mahta Moghaddam, University of MichiganKyle McDonald and Erika Podest, Jet Propulsion Laboratory
Acknowledging Bruce Chapman, JPLALOS PI Meeting
November 6, 2008Rhodes, Greece
ALOS PI MeetingNovember 6, 2008
Rhodes, Greece
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IntroductionIntroductionEffects of global warming may be most widely and strongly felt in the northern ecosystems
Wetlands, in particular, are susceptible to significant change, subject to drying or changing vegetation cover, and switching between carbon sinks and sources
JERS acquired 2 seasons data over global boreal forests in 1997
Through NASA support, our team has used these data and developed a map of wetlands of Alaska
AK wetlands map has been validated extensively
We are using the same methodology to produce the 2007-era maps over AK and Canada
Ultimate goal is to integrate this product with carbon models and investigate scaling-up possibilities for assessing boreal carbon balance
Effects of global warming may be most widely and strongly felt in the northern ecosystems
Wetlands, in particular, are susceptible to significant change, subject to drying or changing vegetation cover, and switching between carbon sinks and sources
JERS acquired 2 seasons data over global boreal forests in 1997
Through NASA support, our team has used these data and developed a map of wetlands of Alaska
AK wetlands map has been validated extensively
We are using the same methodology to produce the 2007-era maps over AK and Canada
Ultimate goal is to integrate this product with carbon models and investigate scaling-up possibilities for assessing boreal carbon balance
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Background:Imagery from JERS-1
Boreal Mapping Mission
Background:Imagery from JERS-1
Boreal Mapping Mission
Summer WinterPass-to-Pass striping is prominent, pointing to possible calibration
drifts and/or temporal scene variationsPass-to-Pass striping is prominent, pointing to possible calibration
drifts and/or temporal scene variations
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Wetlands Classification ApproachWetlands Classification Approach
Standard methods such as maximum likelihoodestimators, iso-data classifiers, and even scattering-based approaches do not work, due to pass-to-passvariations and calibration inconsistencies
The method used here uses a diversity of decision tree classifiers, whereby not just a single decision tree, but a decision “forest” is used: “Random Forests” technique
The data layers used include ground reference data, DEM, slope, open water, latitude, acquisition date, and image texture
Standard methods such as maximum likelihoodestimators, iso-data classifiers, and even scattering-based approaches do not work, due to pass-to-passvariations and calibration inconsistencies
The method used here uses a diversity of decision tree classifiers, whereby not just a single decision tree, but a decision “forest” is used: “Random Forests” technique
The data layers used include ground reference data, DEM, slope, open water, latitude, acquisition date, and image texture
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Wetlands Classification ApproachWetlands Classification ApproachThe JERS Alaska radar mosaic was divided into 9 tiles, and each tile classified separately, with enough overlap to ensure consistency of class definitions100m resolutionExample data layers for a tile:
The JERS Alaska radar mosaic was divided into 9 tiles, and each tile classified separately, with enough overlap to ensure consistency of class definitions100m resolutionExample data layers for a tile:
Tile A5 DEM Tile A5 open water Tile A5 texture Tile A5 acquisition date
A1 A2 A3
A4 A5 A6 A7
A8 A9
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Wetlands Classification ApproachWetlands Classification Approach
Ground reference data set primarily from NWI
NWI uses Cowardin’s classification system (1979) for the US
Nonwetlands classes from AGDC
Ground reference data set primarily from NWI
NWI uses Cowardin’s classification system (1979) for the US
Nonwetlands classes from AGDC
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Wetlands Classification ApproachWetlands Classification Approach
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Completed Wetlands Map of Alaska, 1997-era
Completed Wetlands Map of Alaska, 1997-era
Note: some of the smaller classes are not visible at the resolution of this figure
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Classification AccuracyClassification Accuracy
Referring to the image tiles identified on previous pages, the following table shows the classification error rate. The resulting accuracy is better than 88%.
Referring to the image tiles identified on previous pages, the following table shows the classification error rate. The resulting accuracy is better than 88%.
Tile Number Training Pixels Error Rate (%) A1 387059 3.72 A2 2120222 11.22 A3 124669 11.13
West A4 1835839 3.61 Mid A4/A5 1184311 20.16
East A5 822863 19.09 A6 440813 13.69
A7/A9 67612 13.20 A8 70160 30.56
Overall Aggregated Error Rate 11.61
Ref.: J. Whitcomb, M. Moghaddam, K. McDonald, J. Kellndorfer, and E. Podest, “Mapping Wetlands of Alaska Using L-Band Radar Satellite Imagery,” C. J. Remote Sensing, in press.
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Alaska Wetlands Tally, 1997-eraAlaska Wetlands Tally, 1997-era
Following results are based on pixel counts in classified imageFollowing results are based on pixel counts in classified image
Approx. 26.3% of Alaska is vegetated wetlandsApprox. 3.7% of Alaska is open waterTotal estimate of ~30% wetlands updates the 1980s figure (40-45%) derived through possibly less rigorous means
Approx. 26.3% of Alaska is vegetated wetlandsApprox. 3.7% of Alaska is open waterTotal estimate of ~30% wetlands updates the 1980s figure (40-45%) derived through possibly less rigorous means
Wetland Type Fraction of Total Wetlands (%) Fraction of Total Area of AK (%)
Emergent, Palustrine 46.4 12.2
Scrub/Shrub, Palustrine 44.3 11.6
Forested, Palustrine 8.56 2.25
Emergent, Estuarine 0.78 0.21
All Other vegetated 0.02 0.00
Open water 3.7
Total (all wetlands) 100.0 29.9
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PALSAR Map of Alaska2007-era
PALSAR Map of Alaska2007-era
Data acquired in 2007; partially processedWe have just begun receiving processed data for wetlands mappingSo far only small areas have been classified for wetlandsGround reference data same as those used for JERS
Data acquired in 2007; partially processedWe have just begun receiving processed data for wetlands mappingSo far only small areas have been classified for wetlandsGround reference data same as those used for JERS
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PALSAR Input Image Layers PALSAR Input Image Layers
Generate static wetlands map to startThe images have been projected into SRTM-like tiles1o X 1o
61N 61WHH+HV<50m resolution
Generate static wetlands map to startThe images have been projected into SRTM-like tiles1o X 1o
61N 61WHH+HV<50m resolution
HH Image HH Texture
HV TextureHV Image
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Ancillary data Layers Ancillary data Layers
DEM
Proximity to Water
Slope
Open Water
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Initial ResultsInitial Results
Same ground reference data as JERS-eramap (from NWI and AGDC)HH-only JERS, 100mHH+HV PALSAR, <50m resolution
Same ground reference data as JERS-eramap (from NWI and AGDC)HH-only JERS, 100mHH+HV PALSAR, <50m resolution
JERS Classification PALSAR Classification
Ground Reference Data for target tile
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Decadal ChangeDecadal Change
Green: no change in vegetated wetland typeBlue: conversion from herbaceous to scrub/shrub wetland in 10 yearsBlack: nonvegetated or nonwetland for bothPossible interpretation: Woody vegetation is encroaching northCaveat: ground reference data are not updated for PALSAR-era
Green: no change in vegetated wetland typeBlue: conversion from herbaceous to scrub/shrub wetland in 10 yearsBlack: nonvegetated or nonwetland for bothPossible interpretation: Woody vegetation is encroaching northCaveat: ground reference data are not updated for PALSAR-era
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Upcoming Products (1):2007-era Static Wetlands Map of Canada
and Alaska
Upcoming Products (1):2007-era Static Wetlands Map of Canada
and Alaska
Blue outline shows the ALOS/PALSAR coverage areaThese are regions of Alaska and Canada for which ALOS PALSAR repeat acquisitions in ScanSAR HH-polarization mode (descending node) have been acquired. The area was also covered by standard beam dual-pol (HH+HV) mode at least once, in summer 2007.Standard beam dual-pol data is being used for the static mapWill assess change w/r to the 1990s-era map
Blue outline shows the ALOS/PALSAR coverage areaThese are regions of Alaska and Canada for which ALOS PALSAR repeat acquisitions in ScanSAR HH-polarization mode (descending node) have been acquired. The area was also covered by standard beam dual-pol (HH+HV) mode at least once, in summer 2007.Standard beam dual-pol data is being used for the static mapWill assess change w/r to the 1990s-era map
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Upcoming Products (2):2007-era Time-series Wetlands Map of
Selected Sites
Upcoming Products (2):2007-era Time-series Wetlands Map of
Selected Sites
Within the targeted PALSAR coverage area, will use a handful of focused study sites for time-series analysisSoil wetness regimes proposed as a new product from this data setSpecial focus on permafrost
Within the targeted PALSAR coverage area, will use a handful of focused study sites for time-series analysisSoil wetness regimes proposed as a new product from this data setSpecial focus on permafrost
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Tentative locations of ground reference data for Canada
Tentative locations of ground reference data for Canada
Need to assemble ground reference data with help from collaboratorsWill have access to IPY surveys from CiCAT projectCan use as many more as possible!
Need to assemble ground reference data with help from collaboratorsWill have access to IPY surveys from CiCAT projectCan use as many more as possible!
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SummarySummaryMachinery for boreal wetlands classification developed and validated: Alaska wetlands map of the 1990s-eraMethod is based on using a diversity of regression treesHave started to produce the 2007-era Alaska static wetlands mapResults so far show increase of scrub-shrub vegetated wetlands, encroaching into emergent vegetationWill be followed by Canada 2007 static map, and time-series for selected sitesWill investigate integrating remote-sensing derived wetlands maps into Carbon model (“wetland-DNDC”)Will investigate a new product: wetlands soil wetness regime
Machinery for boreal wetlands classification developed and validated: Alaska wetlands map of the 1990s-eraMethod is based on using a diversity of regression treesHave started to produce the 2007-era Alaska static wetlands mapResults so far show increase of scrub-shrub vegetated wetlands, encroaching into emergent vegetationWill be followed by Canada 2007 static map, and time-series for selected sitesWill investigate integrating remote-sensing derived wetlands maps into Carbon model (“wetland-DNDC”)Will investigate a new product: wetlands soil wetness regime