thomas j. cova department of geography, university of utah paul c. sutton
DESCRIPTION
Light My Fire Proneness: Residential Change Detection in The Urban-Wildland Interface with Nighttime Satellite Imagery. Thomas J. Cova Department of Geography, University of Utah Paul C. Sutton Department of Geography, University of Denver David M. Theobald - PowerPoint PPT PresentationTRANSCRIPT
![Page 1: Thomas J. Cova Department of Geography, University of Utah Paul C. Sutton](https://reader035.vdocuments.mx/reader035/viewer/2022062314/568145db550346895db2de43/html5/thumbnails/1.jpg)
Light My Fire Proneness: Residential Change Detection in The
Urban-Wildland Interface with Nighttime Satellite Imagery
Thomas J. CovaDepartment of Geography, University of Utah
Paul C. SuttonDepartment of Geography, University of Denver
David M. TheobaldDepartment of Natural Resource Recreation & Tourism and
The Natural Resource Ecology Lab (NREL), CSU
April 2004
![Page 2: Thomas J. Cova Department of Geography, University of Utah Paul C. Sutton](https://reader035.vdocuments.mx/reader035/viewer/2022062314/568145db550346895db2de43/html5/thumbnails/2.jpg)
The Urban-Wildland Interface
![Page 3: Thomas J. Cova Department of Geography, University of Utah Paul C. Sutton](https://reader035.vdocuments.mx/reader035/viewer/2022062314/568145db550346895db2de43/html5/thumbnails/3.jpg)
Tracking Interface Development
• Where is interface development occurring and at what densities?
• How many people live in the interface?• What is the historic rate of development?• Are emergency services keeping pace with
the change?• Where might development occur in the
future?
![Page 4: Thomas J. Cova Department of Geography, University of Utah Paul C. Sutton](https://reader035.vdocuments.mx/reader035/viewer/2022062314/568145db550346895db2de43/html5/thumbnails/4.jpg)
Existing Change-Detection Approaches
• The Census? – Really big tracts in exurban areas.– Updated once every 10 years on the ’00.
• Existing RS Change Detection Methods?– Expensive for large, forested areas.
• City, County or State Agencies?– Difficult to acquire and tile for large areas and
regions that cross jurisdictions.
![Page 5: Thomas J. Cova Department of Geography, University of Utah Paul C. Sutton](https://reader035.vdocuments.mx/reader035/viewer/2022062314/568145db550346895db2de43/html5/thumbnails/5.jpg)
Wildlands? or Residential?
![Page 6: Thomas J. Cova Department of Geography, University of Utah Paul C. Sutton](https://reader035.vdocuments.mx/reader035/viewer/2022062314/568145db550346895db2de43/html5/thumbnails/6.jpg)
DMSP-OLS Data (1 km)
![Page 7: Thomas J. Cova Department of Geography, University of Utah Paul C. Sutton](https://reader035.vdocuments.mx/reader035/viewer/2022062314/568145db550346895db2de43/html5/thumbnails/7.jpg)
Exploring DMSP Nighttime
Lights Data
1) 30m National Land Cover Data (NLCD) classified areas as ‘forest’ that Ikonos revealed had many homes.
2) DMSP saw low levels of light in the same areas.
![Page 8: Thomas J. Cova Department of Geography, University of Utah Paul C. Sutton](https://reader035.vdocuments.mx/reader035/viewer/2022062314/568145db550346895db2de43/html5/thumbnails/8.jpg)
Classifying DMSP Change (’92-’00)
• 6-bit data (64 values)
• 0 – “no light” (NL)
• 1-62 – “low light” (LL)
• 63 – “saturated” (S)
1
2 3
4
NL LL S
NL
LL
S
![Page 9: Thomas J. Cova Department of Geography, University of Utah Paul C. Sutton](https://reader035.vdocuments.mx/reader035/viewer/2022062314/568145db550346895db2de43/html5/thumbnails/9.jpg)
DMSP Change Map for Colorado
![Page 10: Thomas J. Cova Department of Geography, University of Utah Paul C. Sutton](https://reader035.vdocuments.mx/reader035/viewer/2022062314/568145db550346895db2de43/html5/thumbnails/10.jpg)
“Extreme” Fire Risk Mapping Method
• Composite score based on fire frequency and fire severity of seven forest types found in Colorado: Lower montane, montane, and upper montane, mixed conifer, aspen, pinyon-juniper, and shrubland.
• Fire frequency: (normalized 1-10) based on the inverse of historical frequency and mapped using species level NLCD data set.
• Fire severity: (normalized 1-10) relies on DEM to distinguish moist north-facing from dry south-facing slopes and very dry ridges.
• Multiply the two together and average with a ¼ mile filter.
![Page 11: Thomas J. Cova Department of Geography, University of Utah Paul C. Sutton](https://reader035.vdocuments.mx/reader035/viewer/2022062314/568145db550346895db2de43/html5/thumbnails/11.jpg)
![Page 12: Thomas J. Cova Department of Geography, University of Utah Paul C. Sutton](https://reader035.vdocuments.mx/reader035/viewer/2022062314/568145db550346895db2de43/html5/thumbnails/12.jpg)
Light on
Fire Risk
For
2000
![Page 13: Thomas J. Cova Department of Geography, University of Utah Paul C. Sutton](https://reader035.vdocuments.mx/reader035/viewer/2022062314/568145db550346895db2de43/html5/thumbnails/13.jpg)
![Page 14: Thomas J. Cova Department of Geography, University of Utah Paul C. Sutton](https://reader035.vdocuments.mx/reader035/viewer/2022062314/568145db550346895db2de43/html5/thumbnails/14.jpg)
Results Highlights (’92-’00)
• Grand County had the greatest absolute increase in ambient sprawl into fire-prone areas (215 km2).
• Teller County had the greatest percentage increase (7.3%).
• In 2000, La Plata County had the most ambient development in fire-prone areas (909 km2)
• In 2000, Jefferson County had the greatest percentage (42%) of ambient development in fire-prone areas.
![Page 15: Thomas J. Cova Department of Geography, University of Utah Paul C. Sutton](https://reader035.vdocuments.mx/reader035/viewer/2022062314/568145db550346895db2de43/html5/thumbnails/15.jpg)
Conclusions
• DMSP with Fire Mapping shows promise for detecting residential change in fire prone areas.
• It can get into problems with snow reflectance, changes in vegetation, ephemeral light, etc.
• New processing of DMSP data will improve this method (low gain images available from ‘98).
![Page 16: Thomas J. Cova Department of Geography, University of Utah Paul C. Sutton](https://reader035.vdocuments.mx/reader035/viewer/2022062314/568145db550346895db2de43/html5/thumbnails/16.jpg)
Paper / Questions?
Cova, T.J., Sutton, P.C., and Theobald, D.M. (2004) Exurban change detection in fire-prone areas with nighttime satellite imagery, Photogrammetric Engineering and Remote Sensing, in press.
http://www.geog.utah.edu