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Wildfire &
Wetlands
Mapping with Landsat,
GIS and Statistical
Models
Stephen Chignell
Sky Skach
Colorado State University
...
High Park Fire
• On June 9th, 2012,
lightning ignited Roosevelt
National Forest west of
Fort Collins, Colorado.
• At the t...
• Days later, torrential
downpours caused
major flooding and
erosion in the Poudre
Canyon.
• Large amounts of soil
and ash...
Monitoring effects of fires such as these on sensitive
habitats like wetlands and riparian areas is critical, and there
is...
Cache la Poudre
Watershed
• The Poudre River runs
140 miles from its
headwaters in the
Rockies
• Drops 7,000 feet to
its c...
Community Concerns
• One of the most
important river systems
on the Colorado Front
Range:
– Drinking Water
– Agricultural ...
Importance of Wetlands
• Biogeochemical processes:
• water cycling
• carbon storage
• Ecosystem services:
• water purifica...
Wetland Mapping Status
Percentage of basin mapped:
• Digital NWI Mapping: 61%
• CPW Riparian Mapping: 70%
• Potential Fen ...
Project Objectives
• Provide a current map of wetlands in the Cache la Poudre
watershed for use by local land managers.
• ...
Project Partners
Colorado Natural Heritage Program
Colorado State University

Geospatial Centroid at CSU
Natural Resource ...
Methodology
Landsat 5 TM

Ancillary GIS Data

Statistical Regression
Model

Map of Predicted Wetlands

Existing Wetland
Da...
Landsat 5 Data
Image Acquisition
• Landsat 5 Thematic Mapper
• Path/Row: 34, 32
• Cloudless
• Multiple years and months

A...
Landsat Data Processing
• Atmospheric Correction

Derived Environmental
Variables
• Tasseled Cap: Brightness,
Greenness, W...
Landsat 5 TM

Ancillary GIS Data

Statistical Regression
Model

Map of Predicted Wetlands

Existing Wetland
Data
Existing Wetlands Data
Presence Data Preparation
1. Exclude water bodies

2. Select only palustrine
– Includes all inland, non-tidal,
wetlands wh...
Background Data Preparation
1. Buffer 60 m away
from wetland
polygons
2. Exclude buffered
areas from all
analysis.
3. Gene...
Landsat 5 TM

Ancillary GIS Data

Statistical Regression
Model

Map of Predicted Wetlands

Existing Wetland
Data
USGS Software for Assisted
Habitat Modeling (SAHM)
1. Project, Aggregate,
Resample, and Clip (PARC)

2. Merged Dataset Bui...
3. Covariate
Correlation
Matrix

Removal of
highly
correlated
predictor
variables
Boosted Regression Trees Modeling
Split Wetland Presence Points

BRT Code
within SAHM

20 %
Test

80 % Train

(Figure: Eli...
Landsat 5 TM

Ancillary GIS Data

Statistical Regression
Model

Map of Predicted Wetlands

Existing Wetland
Data
Initial Results
Refinement: Elevation Zones
Three models for three zones:
• Foothills and Plains (< 1800 m)
• Montane (1800 m – 3500 m)
• ...
Results

Source: Esri, DigitalGlobe, GeoEye, i-cubed, USDA, USGS, AEX, Getmapping, Aerogrid, IGN, IGP, swisstopo, and the ...
Plains and Foothills

PCC: 72.5%
AUC: 0.82
Kappa: 0.46

Source: Esri, DigitalGlobe, GeoEye, i-cubed, USDA, USGS, AEX, Getm...
Montane

PCC: 91.3%
AUC: 0.99
Kappa: 0.99

Source: Esri, DigitalGlobe, GeoEye, i-cubed, USDA, USGS, AEX, Getmapping, Aerog...
Alpine

PCC: 86.7%
AUC: 0.97
Kappa: 0.73

Source: Esri, DigitalGlobe, GeoEye, i-cubed, USDA, USGS, AEX, Getmapping, Aerogr...
Validation Statistics
Elev. Zone

Lower

Middle

Upper

Correctly Classified

72.5 %

91.3 %

86.7 %

AUC

0.82

0.99

0.9...
Results and the High Park Fire
Visual assessment of model against current Landsat 8 imagery (June 29, 2013)
Conclusions
• Numerous unmapped wetlands in the CLP watershed,
including the High Park Fire burn area.

• Modeling within ...
Future Work
• Field validation through wetland plant identification
• Refinement of model in developed regions
• Inclusion...
Project Partners
David Merritt, U.S. Forest Service
Jeremy Sueltenfuss, Colorado Natural Heritage Program
The City of Fort...
2013 GISCO Track, Wildfire and Water: Utilizing LANDSAT imagery, GIS, and Statistical Models for Mapping Wetlands in North...
2013 GISCO Track, Wildfire and Water: Utilizing LANDSAT imagery, GIS, and Statistical Models for Mapping Wetlands in North...
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2013 GISCO Track, Wildfire and Water: Utilizing LANDSAT imagery, GIS, and Statistical Models for Mapping Wetlands in Northern Colorado’s Cache la Poudre Watershed in the aftermath of the June 2012 High Park Fire by Stephen Chignell and Sky Skach

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The June 2012 High Park Fire burned over 87,000 acres of forest and 259 homes to the west of Fort Collins, CO. The fire has had dramatic impacts on forest ecosystems. Of particular concern are its effects on the Cache la Poudre watershed, as the Poudre River is one of the most important headwaters of the Colorado Front Range, providing important ecosystem and economic services before flowing into the South Platte, which in turn flows into the Missouri River. Within a week of the fire, the area received several days of torrential rains. This precipitation—in conjunction with steep riverbanks and the loss of vegetation by fire—caused soil and ash runoff to be deposited into the Poudre’s channel, resulting in a river of choking mud and black sludge. Monitoring the effects of this disaster is critical and requires establishing immediate baseline data to assess impacts over time. Utilizing LANDSAT imagery, GIS layers, and boosted regression trees modeling, the NASA DEVELOP team based at the North Central Climate Science Center at Colorado State University conducted an investigation into riparian, wetland and headwaters modeling within the Cache la Poudre watershed. These efforts produced a preliminary model of predicted wetlands across the watershed, which is currently being refined by field data collection and modeling within three elevation-based “life zones.” The ultimate goal of this ongoing project is to provide important spatial data for land managers and create a riparian and wetlands modeling methodology that can be reproduced throughout the intermountain west region.

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Transcript of "2013 GISCO Track, Wildfire and Water: Utilizing LANDSAT imagery, GIS, and Statistical Models for Mapping Wetlands in Northern Colorado’s Cache la Poudre Watershed in the aftermath of the June 2012 High Park Fire by Stephen Chignell and Sky Skach"

  1. 1. Wildfire & Wetlands Mapping with Landsat, GIS and Statistical Models Stephen Chignell Sky Skach Colorado State University A NASA DEVELOP Project
  2. 2. High Park Fire • On June 9th, 2012, lightning ignited Roosevelt National Forest west of Fort Collins, Colorado. • At the time of containment the fire had impacted over 87,000 acres and burned 259 homes.
  3. 3. • Days later, torrential downpours caused major flooding and erosion in the Poudre Canyon. • Large amounts of soil and ash run-off were deposited into the Cache la Poudre River.
  4. 4. Monitoring effects of fires such as these on sensitive habitats like wetlands and riparian areas is critical, and there is urgent need for baseline data to assess change over time.
  5. 5. Cache la Poudre Watershed • The Poudre River runs 140 miles from its headwaters in the Rockies • Drops 7,000 feet to its confluence with the South Platte River, ultimately flowing into the Missouri River • Annual flow of 280,000 acre feet
  6. 6. Community Concerns • One of the most important river systems on the Colorado Front Range: – Drinking Water – Agricultural Water • Vulnerable to a range of environmental and anthropogenic stressors
  7. 7. Importance of Wetlands • Biogeochemical processes: • water cycling • carbon storage • Ecosystem services: • water purification • flood protection • shoreline stabilization • groundwater recharge • stream-flow maintenance • Biodiversity: • home to a diverse array of flora and fauna
  8. 8. Wetland Mapping Status Percentage of basin mapped: • Digital NWI Mapping: 61% • CPW Riparian Mapping: 70% • Potential Fen Mapping: 0% Total area of NWI mapped wetlands: 30,145 acres Percent of total area: 4% Colorado Natural Heritage Program, 2013: http://www.cnhp.colostate.edu/wetlandinventory/
  9. 9. Project Objectives • Provide a current map of wetlands in the Cache la Poudre watershed for use by local land managers. • Create a reproducible methodology for mapping wetlands in other headwaters regions of the Intermountain West.
  10. 10. Project Partners Colorado Natural Heritage Program Colorado State University Geospatial Centroid at CSU Natural Resource Ecology Laboratory at CSU North Central Climate Science Center USDA Forest Service Rocky Mount. Research Station USGS Fort Collins Science Center
  11. 11. Methodology Landsat 5 TM Ancillary GIS Data Statistical Regression Model Map of Predicted Wetlands Existing Wetland Data
  12. 12. Landsat 5 Data Image Acquisition • Landsat 5 Thematic Mapper • Path/Row: 34, 32 • Cloudless • Multiple years and months Available Cloudless LANDSAT Data for Path 34, Row 32 June 2011 March 2010 March 2009 November 2010 January 2010 February 2007 September 2010 August 2009 December 2006 April 2010 May 2009 July 2003
  13. 13. Landsat Data Processing • Atmospheric Correction Derived Environmental Variables • Tasseled Cap: Brightness, Greenness, Wetness • NDVI, NDMI, NDWI, SAVI, Edge Filter Ancillary Data • NED Digital Elevation Model (30 m) • Slope, Aspect, CTI, Curvature Normalized Difference Moisture Index (NDMI)
  14. 14. Landsat 5 TM Ancillary GIS Data Statistical Regression Model Map of Predicted Wetlands Existing Wetland Data
  15. 15. Existing Wetlands Data
  16. 16. Presence Data Preparation 1. Exclude water bodies 2. Select only palustrine – Includes all inland, non-tidal, wetlands which lack flowing water. 3. Exclude all polygons less than one hectare 4. Inverse -30 m buffer 5. Generate 150 random presence points within polygons – 30m distance between points
  17. 17. Background Data Preparation 1. Buffer 60 m away from wetland polygons 2. Exclude buffered areas from all analysis. 3. Generate 150 random absence points from background
  18. 18. Landsat 5 TM Ancillary GIS Data Statistical Regression Model Map of Predicted Wetlands Existing Wetland Data
  19. 19. USGS Software for Assisted Habitat Modeling (SAHM) 1. Project, Aggregate, Resample, and Clip (PARC) 2. Merged Dataset Builder  i.e. “Extract Multi Values to Points” in ArcMap
  20. 20. 3. Covariate Correlation Matrix Removal of highly correlated predictor variables
  21. 21. Boosted Regression Trees Modeling Split Wetland Presence Points BRT Code within SAHM 20 % Test 80 % Train (Figure: Elith et al, 2008) Binary Map
  22. 22. Landsat 5 TM Ancillary GIS Data Statistical Regression Model Map of Predicted Wetlands Existing Wetland Data
  23. 23. Initial Results
  24. 24. Refinement: Elevation Zones Three models for three zones: • Foothills and Plains (< 1800 m) • Montane (1800 m – 3500 m) • Alpine (> 3500 m)
  25. 25. Results Source: Esri, DigitalGlobe, GeoEye, i-cubed, USDA, USGS, AEX, Getmapping, Aerogrid, IGN, IGP, swisstopo, and the GIS User Community
  26. 26. Plains and Foothills PCC: 72.5% AUC: 0.82 Kappa: 0.46 Source: Esri, DigitalGlobe, GeoEye, i-cubed, USDA, USGS, AEX, Getmapping, Aerogrid, IGN, IGP, swisstopo, and the GIS User Community
  27. 27. Montane PCC: 91.3% AUC: 0.99 Kappa: 0.99 Source: Esri, DigitalGlobe, GeoEye, i-cubed, USDA, USGS, AEX, Getmapping, Aerogrid, IGN, IGP, swisstopo, and the GIS User Community
  28. 28. Alpine PCC: 86.7% AUC: 0.97 Kappa: 0.73 Source: Esri, DigitalGlobe, GeoEye, i-cubed, USDA, USGS, AEX, Getmapping, Aerogrid, IGN, IGP, swisstopo, and the GIS User Community
  29. 29. Validation Statistics Elev. Zone Lower Middle Upper Correctly Classified 72.5 % 91.3 % 86.7 % AUC 0.82 0.99 0.97 Kappa 0.46 0.99 0.73 Source: Esri, DigitalGlobe, GeoEye, i-cubed, USDA, USGS, AEX, Getmapping, Aerogrid, IGN, IGP, swisstopo, and the GIS User Community
  30. 30. Results and the High Park Fire Visual assessment of model against current Landsat 8 imagery (June 29, 2013)
  31. 31. Conclusions • Numerous unmapped wetlands in the CLP watershed, including the High Park Fire burn area. • Modeling within distinct elevation zones is a valuable strategy for refining wetland models. • Modeling wetlands in developed areas continues to be a challenge for methodologies relying on moderateresolution remotely sensed data but may be less important than less urbanized areas. • Potential methodology to aid monitoring effects of wildfire and land use change in wetlands.
  32. 32. Future Work • Field validation through wetland plant identification • Refinement of model in developed regions • Inclusion of forthcoming cloudless Landsat 8 imagery in model • Application to other watersheds in the Intermountain West
  33. 33. Project Partners David Merritt, U.S. Forest Service Jeremy Sueltenfuss, Colorado Natural Heritage Program The City of Fort Collins Science Advisors Paul Evangelista, Natural Resource Ecology Lab, CSU Jeff Morisette, USGS, North Central Climate Science Center Melinda Laituri, Ecosystem Science and Sustainability, Geospatial Centroid, CSU Nicholas Young, Natural Resource Ecology Lab, CSU NASA DEVELOP Past Contributors Amy Birtwistle, CSU Brenda Kessenich, CU Boulder Matthew Luizza, CSU Amber Weimer, CSU
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