2013 GISCO Track, Wildfire and Water: Utilizing LANDSAT imagery, GIS, and Statistical Models for...
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Wildfire & Wetlands Mapping with Landsat, GIS and Statistical Models Stephen Chignell Sky Skach Colorado State University A NASA DEVELOP Project
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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.
Transcript of 2013 GISCO Track, Wildfire and Water: Utilizing LANDSAT imagery, GIS, and Statistical Models for...
Wildfire &
Wetlands
Mapping with Landsat,
GIS and Statistical
Models
Stephen Chignell Sky Skach
Colorado State University
A NASA DEVELOP Project
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.
• 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.
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.
• 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
Cache la Poudre
Watershed
• 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
Community Concerns
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
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/
• 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.
Project Objectives
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
Project Partners
Map of Predicted Wetlands
Existing Wetland Data
Landsat 5 TM Ancillary GIS Data
Statistical Regression Model
Methodology
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
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)
Map of Predicted Wetlands
Existing Wetland Data
Landsat 5 TM Ancillary GIS Data
Statistical Regression Model
Existing Wetlands Data
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
Presence 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
Background Data Preparation
Map of Predicted Wetlands
Existing Wetland Data
Landsat 5 TM Ancillary GIS Data
Statistical Regression Model
2. Merged Dataset Builder i.e. “Extract Multi Values
to Points” in ArcMap
USGS Software for Assisted
Habitat Modeling (SAHM)
1. Project, Aggregate, Resample, and Clip (PARC)
3. Covariate Correlation Matrix
Removal of highly
correlated predictor variables
Boosted Regression Trees Modeling
Split Wetland Presence Points
80 % Train
20 % Test
(Figure: Elith et al, 2008)
BRT Code within SAHM
Binary Map
Map of Predicted Wetlands
Existing Wetland Data
Landsat 5 TM Ancillary GIS Data
Statistical Regression Model
Initial Results
Refinement: Elevation Zones
Three models for three zones:
• Foothills and Plains (< 1800 m)
• Montane (1800 m – 3500 m)
• Alpine (> 3500 m)
Results
Source: Esri, DigitalGlobe, GeoEye, i-cubed, USDA, USGS, AEX, Getmapping, Aerogrid, IGN, IGP, swisstopo, and the GIS User Community
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
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
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
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
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 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 moderate-resolution 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.
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
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
