Download iGETT Cohort 2, June 2008

iGETT Cohort 2, June 2008
Learning Unit Proposal
Landslides_Johnson_PR_June2008
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Name: Ann Johnson
Institution:
ESRI
Email: [email protected]
Phone: 775 553-9914
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Title of Learning Unit: Landslide Susceptibility and Vegetation Recovery After a Fire
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Keyword used for Title: Landslide, Fire, Vegetation, Regrowth, ArcGIS, ENVI
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Focus Topic (Agriculture, Disasters, Environmental Management): Disasters
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Problem statement (Justification – needs, causes, how RS/GIS and possibly GPS can be
used) – about 4 to 8 sentences – more “industry” need to solve a problem
The combined effects of a dry climate and mountainous topography in Southern
California (less than 30 cm of precipitation per year) result in a high potential for
large scale landslides. This problem can be further exacerbated by infrequent heaving
rains concentrated along mountain fronts, the lack of vegetation on south facing
slopes and the very dry vegetation during late summer and fall. Wildfires can further
reduce the vegetation or create hydrophobic soils leading to even higher susceptibility
for landslides. This Learning Module will use GIS to determine the most likely
locations for landslides using slope, aspect and burn severity after the Old Fire in
October 2003 in San Bernardino. Three Remote Sensing images (July 2003,
December 2003, and May 2004) will be used to suggest the amount of vegetation on
slopes before the Old Fire, the burn severity during the Old Fire and the amount of
vegetation recovery within 6 months after the fire. This data will be used to identify
possible recovery rates for burned areas and how this may affect the extent and
location of regions with a higher susceptibility for landslides.
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Short description (paragraph of why, how, where, importance for student activity)
This Learning Unit will help students understand how GIS can be used to determine the
topographic relief of an area. They will then combine the steepness of a slope, the affect of
sun and dry climate on the different slope directions (aspect of a slope) and the after affects of
a fire on the susceptibility of the region to landslides. Remote sensing will be used to
evaluate the pre and post fire vegetation of the region as well as to determine the burn area,
burn severity and the regrowth of vegetation after the fire and its possible relationship to
landslide susceptibility. This LU is focused on the San Bernardino Mountains of Southern
California. It includes building a “ModelBuilder” Model to automate the process. The
student will then use 3D animation to better visualize the region
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Student Outcomes (preliminary list of what you want the student to know/do)
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Develop map-reading skills, including recognizing latitude, longitude and
other coordinate systems currently employed in mapping
Develop critical thinking skills by determining, accessing and
downloading required data and other background information
Execute spatial analysis on acquired data and build a Model
Demonstrate skills in manipulating GIS software (specifically ArcGIS
Spatial Analyst)
Demonstrate skills in manipulating spatial data using image processing
software
Prepare and present a report on analysis findings
Optional: GPS data acquisition, processing, and inclusion in final map
analysis as part of ground-truthing
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Preliminary list of data sets needed for topic
– DEM of region
– DLQ of region
– Streets
– Streams
– Geology
– Historic Landslides
– Burn Severity from 2003 Old Fire
– LandSat Images (3) prior to, shortly after and one year later
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Brief description of the methods (field work, data access, analysis, etc.)
Students will use ArcGIS to define the slope, aspect and burn severity of the region.
The data will then be reclassified for values that are important to landslides
(steepness, south facing aspect and burn severity). These values will be combined
using tool by tool map algebra to find the locations with highest susceptibility to
landslides. The same data will be used to create a ModelBuilder Model of the
analysis process to show how to automate the process. The LandSat images will then
be used in ENVI to determine the burn extent, loss of and recovery of vegetation.
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Brief description of possible evaluation or assessment methods
Students will create a cartographically accurate visualization of the region showing the
pre and post fire areas and highlighting those locations that they have determined to have
the highest susceptibility to lands slides. A brief written report on their methods and
results will also be graded. Students will then do an oral presentation using images from
their project to support their conclusions.
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List of possible resources
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www.esri.com
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http://seamless.usgs.gov/
www.landsat.org
http://iitvis.com/tutorials/index.asp (ENVI tutorials)
http://ledaps.nascom.nasa.gov/ledaps/ledaps_NorthAmerica.html
http://glcf.umiacs.umd.edu (Global Land Cover Facility)
http://glovis.usgs.gov (Glovis)
http://lpdaac.usgs.gov/datapool/datapool.asp (Data Pool)
http://edcimswww.cr.usgs.gov/pub/imswelcome/ (EOS Data Gateway)
http://map.sdsu.edu/fireweb
http://map.sdsu.edu
http://www.geog.umd.edu
www.iste.org
http://www.californiachaparral.com/chaparralfacts.html