I. Title Page (1 page maximum)
Title:
Assessment of Fire Hazard/Risk in the Wildland Urban Interface
“WUI” and Stream Environment Zones “SEZs”
Subtheme this proposal is
responding to
Integrating Science
Principal Investigator and
Receiving Institution
David Saah, Ph.D.
Spatial Informatics Group, LLC
3248 Northampton Ct., Pleasanton, CA 94588
Phone: 510 427-3571 Email: dsaah@sig-gis.com
Jason Moghaddas
Spatial Informatics Group, LLC
3248 Northampton Ct., Pleasanton, CA 94588
Phone: (530) 284-7376 Email: jmoghaddas@sig-gis.com
Jarlath O’Neil-Dunne
Research Scientist
Spatial Informatics Group, LLC
3248 Northampton Ct., Pleasanton, CA 94588
Phone: 510 427-3571 Email: jarlath@sig-gis.com
Qi Chen, Ph.D.
Senior Research Scientist
Spatial Informatics Group, LLC
3248 Northampton Ct., Pleasanton, CA 94588
Phone: 510 717-9839 Email: qchen@sig-gis.com
Brandon M. Collins, Ph.D.
Research Scientist
USDA Forest Service
Pacific Southwest Research Station
1731 Research Park Dr., Davis, CA 95618
Phone: (530) 759-1701 Email: bmcollins@fs.fed.us
Emily Moghaddas, Ph.D.
Research Soil Scientist
USDA Forest Service
Pacific Southwest Research Station
PO Box 15, Taylorsville, CA 95983
Phone: (530) 284-7376 Email: emoghaddas@fs.fed.us
Tadashi Moody
Research Scientist
Spatial Informatics Group, LLC
3248 Northampton Ct., Pleasanton, CA 94588
Phone: 510 301-0030 Email: tmoody@sig-gis.com
David Saah, Ph.D.
Spatial Informatics Group, LLC
3248 Northampton Ct., Pleasanton, CA 94588
Phone: 510 427-3571 Email: dsaah@sig-gis.com
Co-Principal Investigator
Co-Principal Investigator
Co-Principal Investigator
Agency Collaborator
Agency Collaborator
Co-Principal Investigator
Grants Contact Person
4a: Understanding current and future resource conditions through
analysis of remote sensing data
Funding requested:
$ 170,105
Total cost share (value of
$ 4,451
financial and in-kind
contributions):
Proposal: Tahoe Research Supported by SNPLMA 2010
II. Proposal Narrative (up to 7 pages, single-spaced)
a. Project abstract (1 paragraph summary for public distribution)
Around Lake Tahoe, sections of the Stream Environment Zone (SEZ), especially those that contain the
terminal portions of streams feeding into the lake, are within the Wildland Urban Interface (WUI) where
potential impacts from wildfire are a key concern. A considerable effort has been underway within the
Lake Tahoe Basin to mitigate these potential impacts. An understanding of how wildfire can impact both
the WUI and SEZ, along with an assessment of mitigation efforts to date, is therefore critical. We propose
a study to characterize conditions in the WUI and assess the current potential for crown fire initiation and
probability of burning for all mapped SEZ and WUI areas in the Lake Tahoe Basin under extreme or
“problem” fire weather conditions. In addition, we will evaluate the effects of all known planned fuels
treatments over the next decade on the crown fire initiation and conditional burn probability in all mapped
SEZ and WUI regions in the Lake Tahoe Basin.
b. Justification statement: explain the relationship between the proposal and the
subtheme(s)
While there have been several published stand-level studies on the effects of fuel treatments on stream
characteristics (Beche et al. 2005; Stephens et al. 2004), we could find no peer-reviewed studies which
have examined effectiveness of fuel treatments on the reduction of landscape-level fire-behavior impacts
on Stream Environment Zones (SEZs) in the Lake Tahoe Basin. The WUI is intermixed with SEZs,
particularly along the lower reaches of these streams; therefore, understanding how wildfire can impact
both the WUI and SEZs, including the interaction between the two, is critical from both an ecological and
public hazard perspective. Without this key body of research, there is little information to guide land
managers in consistently and effectively designing and implementing treatments.
This study addresses Subtheme 4a: Understanding current and future resource conditions through
analysis of remote sensing data. We are specifically targeting components of section 4 within subtheme
4a: develop derivative products to identify catastrophic fire risk, extent and distribution of defensible
space in the urban intermix and Wildland Urban Interface, or hydrologic networks for application to
TMDL project planning, floodplain management, or characterization of stream geomorphology. By
using the recently acquired LiDAR and WorldView-2 data, in conjunction with existing datasets and field
verification, we propose to assess historical patterns of fire severity, as well as the current potential for
crown fire initiation and conditional burn probability in all mapped SEZ and WUI areas in the Lake
Tahoe Basin under extreme fire weather conditions. Additionally, we will examine the potential effects of
all known planned fuels treatments over the next decade on potential crown fire initiation and conditional
burn probability in these areas. Finally, this project will generate ancillary datasets, including LiDAR
based high-resolution wildfire behavior maps and associated vegetation structure modeling input data that
can be utilized for analysis across multiple disciplines. If funded it is our intent to actively make these
products available to all collaborative efforts.
c. Concise background and problem statement
The Wildland Urban Interface (WUI), or region where homes and structures are built within wildland
vegetation (Radeloff et al. 2005), is an area of particular concern for land managers. The WUI not only
introduces potential environmental threats (e.g., future development, exotic species, pollutants from
runoff, wildfire ignitions), it often constrains management decision space (e.g., silvicultural/fuels
activities, wildfire suppression actions) (Collins et al. 2010). In the Lake Tahoe Basin these issues are
intensified, owing to the interactions between a fairly expansive WUI, high concern to protect lake water
quality, and potential damage to human communities and other resources from wildfire. Here, as in many
fire-prone communities, decision makers and the public debate the tradeoffs between environmental
concerns and reducing the risk of severe wildfire (Long 2009).
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Proposal: Tahoe Research Supported by SNPLMA 2010
Recent large fires in the Lake Tahoe Basin, including the Gondola Fire (2002) and the Angora Fire
(2007), and a 2007 wild fire in the Sunnyside area of Lake Tahoe have shown the vulnerability of the SEZ
and the WUI in the basin to the effects of rapid growing, high severity wildfires. Together, these fires
impacted hundreds of homes, cost millions of dollars to suppress, put thousands of lives at risk, and
burned, with high severity, several important SEZs (USDA 2007a; Safford et al. 2009). Lake water
quality and clarity have been identified as a high management objective and understanding the potential
influence of wildfire on water quality is critical to the basin. SEZs are designed to help protect water
quality within the lake by providing filtration, canopy cover (shading), and functional in-stream habitat
for beneficial aquatic species. What happens when the values these SEZs are designed to protect are
severely altered by the effects of high severity fire?
Stream Environment Zones are often excluded from prescribed fires and mechanical fuel treatments due
not only to regulation and policy, but also to the real and perceived risks of soil erosion, sedimentation,
nutrient transport, water quality reduction, loss of shading canopy, or aquatic habitat degradation.
Historical reconstructions of fire occurrence in several SEZs throughout the northern Sierra Nevada
(including Lake Tahoe Basin) found little difference between riparian and upland forests (Van de Water
and North, 2010). However, when left untreated, these SEZs can remain susceptible to the impacts of high
severity fire. This type of fire may pose the same set of risks possible due to fuels treatments, but may
also cause highly magnified impacts due to the timing, intensity and scale of a fire event, and possibly be
subject to a delayed or lengthier recovery period. For the LTB, there is little published literature on fuel
treatments in SEZs and a general lack of knowledge about what constitutes “uncharacteristically severe”
fire in SEZs (Moody et al. 2009). However, there are many examples of untreated stream zones on
National Forest lands embedded within fuel treatments that subsequently burned at high-severity levels.
The 2006 Boulder Fire, which burned the eastern slopes of the Sierras above Antelope Lake on the
Plumas National Forest, is one local example in which dense untreated fuels in near-stream areas helped
to ‘wick’ the fire through the stream corridor and adjacent fuel treatment. In cases such as this, protecting
sensitive areas by excluding fuel treatments can threaten the very qualities for which they are specially
designated. When landscapes are highly dissected by stream channels, a substantial proportion of
proposed and actual fuel treatment areas may fall within SEZs, possibly impacting their efficacy.
To address this issue, a management program that includes fuel treatments intended to reduce fire severity
and protect SEZs has been developed. While the Lake Tahoe Basin has taken several steps to implement
the 2007 “Lake Tahoe Basin Multi-Jurisdictional Fuel Reduction and Wildfire Prevention Strategy”
(Nevada Fire Safe Council 2009; USDA 2007b), the outcomes of this program from an implementation
and fire regime standpoint are still unclear.
d. Goals, objectives, and hypotheses to be tested
Primary Research Goal: What are the effects of the WUI and SEZs on the fire behavior, potential for
crown fire initiation and conditional burn probability in the LTB?
Research Questions:
Question 1: How does current treatment implementation on the ground in the LTB compare to treatments
planned for the next decade?
Question 2: How has fire affected WUI areas and SEZs historically?
Question 3: Given the current status of the WUI, SEZs, and fuel treatment implementation, what is the
current potential for crown fire initiation and conditional burn probability in the WUI and
SEZ areas of the LTB?
Question 4: How would full implementation of planned treatments (next decade) change the potential for
crown fire initiation and conditional burn probability in the WUI and SEZs of the LTB?
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Proposal: Tahoe Research Supported by SNPLMA 2010
Research Objectives:
Objective 1: Examination of fuel treatment compliance and implementation in the LTB
Objective 2: Analysis of severity distributions within WUI areas and SEZs within historical fires in the
LTB.
Objective 3: Fire behavior and probability analysis for the LTB, summarized for all WUI areas and
SEZs.
Objective 4: Fire behavior and probability analysis for the LTB (simulated with future treatments
complete) summarized for all WUI areas and SEZs.
e. Approach, methodology and location of research
This project will encompass all lands within the Lake Tahoe Basin Management Unit. Our general
approach will be to develop new and refine existing GIS data layers for analysis of fire behavior and
probability within the LTB, including using LiDAR and WorldView-2 data to develop inputs for fire
behavior and probability models. Our analysis of the modeling outputs will be focused on SEZs and WUI
areas within the LTB.
Existing conditions vegetation and fuel characteristics including vegetation type, past wildfires and
treatments, canopy cover (CC), height to crown base (HTCB), canopy bulk density (CBD), and fuel
model (FM) will be mapped using a combination of LiDAR data, WorldView-2 data, existing GIS
datasets, and field visits to treated and untreated areas. A detailed stream network will be generated from
the high spatial resolution LiDAR DEM for delineating the SEZs. The LiDAR and Worldview-2 imagery
will be combined to classify vegetation and buildings, based on which WUI zones will be mapped. This
LiDAR derived SEZ and WUI maps will be compared with existing WUI and SEZ delineations.
The Tiffs (Toolbox for LiDAR Data Filtering and Forest Studies) software will be used to filter the raw
point cloud from the LiDAR data to generate Digital Elevation Model (DEM) and Canopy (or
Vegetation) Height Model (CHM) (Chen 2007, Chen et al. 2007a, Chen 2009). Elevation, slope, and
aspect will be directly extracted or derived from the LiDAR DEM. The stand boundaries will be
delineated from LiDAR CHM and multispectral imagery assuming that a stand has similar canopy
structure and spectral signature using image segmentation or clustering algorithms. Canopy cover will be
directly derived by thresholding the CHM and calculating the percentage of pixels above that threshold of
canopy height. An individual tree crown delineation algorithm (Chen et al. 2006; Chen 2007) will be used
to generate basin-wide spatially-explicit individual tree crown map. The individual tree crown canopy
structure metrics derived from LiDAR point cloud or CHM will be combined to the vegetation type
mapped from multispectral imagery to develop a vegetation type dependent foliage biomass model for
estimating crown bulk density. The lidar metrics that are not sensitive to tree crown delineation errors will
be used to estimate foliage biomass (Chen et al. 2007b). Height to live crown will be estimated by
analyzing the vertical distribution of point cloud and calibrated with field mead height will be extracted
by overlaying the stand boundaries and tree height information.
Based on the expertise of local and regional fire managers, LiDAR analysis, field verification,
characteristics observed in the field verification, we will assign initial fuel models to best match surface
fuel structural characteristics described in Scott and Burgan (2005). Values for canopy bulk density
within a particular vegetation class will be scaled to canopy cover using previously published values for
mixed conifer forests (Scott and Reinhardt 2005).
We will utilize the existing FLAMMAP (Finney 2006) and FARSITE (Finney 1998) fire modeling
applications to assess the potential for crown fire risk and probability (conditional) of burning under
current conditions and several scenarios, for the entire LTBMU with an emphasis SEZs and WUI’s. A
landscape file for use in FLAMMAP and FARSITE modeling will be developed and calibrated using
actual fires from the Lake Tahoe Basin (Angora and Gondola) and associated fire weather. Once layers
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Proposal: Tahoe Research Supported by SNPLMA 2010
are calibrated, existing potential for crown fire initiation and conditional burn probability will be assessed
using calculated 97th percentile weather data obtained from local remote access weather stations (RAWS).
This analysis will establish current conditions.
Using the landscape files developed above, a second analysis will be completed using a scenario where all
known fuel treatments planned for implementation over the next decade are assessed for overall
effectiveness at modifying crown fire potential and conditional burn probability for all WUI and SEZ
areas in the Lake Tahoe Basin. An analysis of current condition and potential changes resulting from
implementation will be completed as completed in previous studies (Moghaddas et al. 2010) and
demonstrated in section V, figures 1 and 2.
This project will focus on addressing the identified outstanding questions using systematic, scientifically
sound, previously published methods (Moghaddas et al. 2010; Ager et al. 2007a, b) and providing base
data derived from the LiDAR acquisition to be used in other fire related projects. Specifically, the team
working on this project will complete the following tasks:
Task 1. Pre-Work Conference(s): Meet with the TRPA, LTBMU, CALFIRE, and other local
management agencies to review the proposed Scope of Work as submitted in this proposal within one
week of both parties signing the contract. This meeting will take place either by phone or in person.
Modify Work Plan tasks, deliverables, report formats, and other related logistics based on review.
Produce final Scope of Work and Plan of Work schedule.
Task 2. Project Management: SIG will be the prime contractor and provide project management
services, including monthly and annual progress reports to TRPA and regular communication and
coordination via meetings (including conference calls) with the TRPA.
Task 3. Vegetation Structure Characterization of the SEZ and WUI areas: Use the available highresolution LiDAR data and multispectral imagery to characterize, develop and refine spatially explicit
Stream Environment Zones (SEZs) and wildland-urban interface (WUI) maps.
Task 4. Analysis of Current and Planned Fuel Treatments: Map current on-the-ground and planned
fuel treatments from the “Lake Tahoe Basin Multi-Jurisdictional Fuel Reduction and Wildfire Prevention
Strategy” (USDA 2007). Compare current levels of implementation to overall plan for next decade.
Task 5. Fire Severity Analysis: Conduct a fire severity analysis of historical fires in SEZs and WUI
areas in the Lake Tahoe Basin. This assessment would examine landscape-level trends in burn severity
within SEZs and WUI areas in actual local fires (e.g. Angora and Gondola) using the existing Region 5
Fire History and Severity Geodatabase. The analysis would incorporate past fuel treatments in an attempt
to discern differences in fire severity between treated and untreated SEZs.
Task 6. Development of Fire Behavior Modeling Inputs: Use the available high-resolution LiDAR
data and multispectral imagery along with secondary datasets (including but not limited to LTAB and
MSIM field plots) to develop and refine spatially explicit fuel characteristic maps for use in FARSITE
and FLAMMAP modeling.
Task 7. Baseline Fire Behavior Modeling: Assess fire behavior, potential for crown fire initiation and
probability of burning in the Lake Tahoe Basin under current conditions using an established method for
identifying fuel treatment effectiveness at the landscape level (Moghaddas et al. 2010). This analysis
would be conducted under historical moderate, high and extreme weather conditions as derived from local
Remote Automated Weather Stations (RAWS). Summarize outputs for SEZs and WUI areas (by
neighborhood or community) within the LTB. Sample outputs are shown in Figures 1 and 2; similar
figures would be developed for the entire LTBMU or specific areas of interest within the LTBMU.
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Proposal: Tahoe Research Supported by SNPLMA 2010
Task 8. Treatment Fire Behavior Modeling: Assess the future potential fire behavior, potential for
crown fire initiation, and probability of burning in the LTB under a simulated landscape with full
implementation of all treatments planned for the next decade on public and private lands. This analysis
would be conducted using the same methodology and under the same historical moderate, high and
extreme weather conditions as in Task 6 above. Sample outputs are shown in Figures 1 and 2; similar
figures would be developed for the entire LTBMU or specific areas of interes within the LTBMU. This
task may also assess the effectiveness of new CA Forest Practice Rules on protecting stream zones from
high severity fire.
Task 9. Draft Final Report: Based upon information and findings assimilated in tasks 1 through 8, a
draft final report will be generated. This report will be written so that the target audience (defined by
TRPA) will be able to easily interpret its contents. The report will include a discussion on the effects of
potential fire hazard on erosion, nutrient loading, and possible impacts to lake clarity.
Task 10. Final Report and submission of article for review in peer reviewed scientific publication:
Within 30 days of receiving comments on the draft final report, a final copy will be prepared and
delivered. Report will be formatted for and submitted to a peer reviewed journal.
f. Relationship of the research to previous and current relevant research, monitoring,
and/or environmental improvement efforts
There has been extensive work in the Lake Tahoe Basin to implement fuel treatments both within and
outside the WUI. To date, we could not find publications which assess the effectiveness of this effort in
the peer reviewed literature. While several stand level studies have looked at the impact of wildfire and
prescribed fire on Sierran stream characteristics (Beche et al. 2005; Stephens et al. 2004), we could find
no peer reviewed publications that systematically study the overall effectiveness of existing and planned
fuel treatments on SEZs across the landscape. The proposed study would provide this critical missing
information.
g. Strategy for engaging with managers and obtaining permits
If the proposal is funded, collaborators will work directly with agency fuels, vegetation management, and
contracting personnel to identify and characterize existing and planned fuel treatments on federal lands in
the Lake Tahoe Basin. We have already communicated with Kyle Jacobson, Forest Fuels Specialist and
Susie Kocher, UC Cooperative Extension about this proposal and how to disseminate results. We will
work directly with the Lake Tahoe Basin Fire Safe Council, Nevada Fire Safe Council, California State
Parks, Tahoe Regional Planning Agency, Nevada Department of Conservation & Natural Resources,
University of Nevada Cooperative Extension ,USDA (Lake Tahoe Basin Management Unit), private
landowners, and Home Owner Associations to identify and characterize current and planned fuel
treatments within the Lake Tahoe Basin. Preliminary results will be presented directly to interested
stakeholders through direct meetings, in cooperation with University of California Cooperative Extension,
and via the on-going California Fire Science Collaborative. In addition, final results and reports will be
made available on-line in pdf format to the public.
Project data will be derived using provided LiDAR data, existing GIS databases, and field visual
verification. There will be no treatments specifically implemented for this study, no destructive sampling,
no ground disturbing activity, and no permanent marking of any research plots or points in the field,
greatly limiting or eliminating the need for further CEQA and NEPA analysis or sampling permits.
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Proposal: Tahoe Research Supported by SNPLMA 2010
h. Description of deliverables/products and plan for how data and products will be
reviewed and made available to end users
SIG will create and manage a website (SharePoint site) that will be accessible to the TRPA, all agency
collaborators, and all team members. This site will serve as a distribution point for project documents and
data.
Deliverables

Pre-Work Conference(s): Final Scope of Work and Plan of Work schedule. This will be made
available via the web on the project site.

Project Management: Monthly and annual progress reports to the TRPA. These will be made
available via the web on the project site.

SEZ and WUI Vegetation Structure Characterization: GIS data and maps for refined,
spatially explicit stream environment zone (SEZ) and wildland-urban interface (WUI) data layers
that contain vegetation structure charachterizations.

Analysis of Current and Planned Fuel Treatments: GIS data and maps of all current on-theground fuel treatments, as well as all treatments planned for the next decade.

Fire Severity Analysis: GIS Data, maps, and graphs of wildfire severity patterns and
distributions within historical fires, and within SEZs and WUI areas for these fires.

Fire Behavior Modeling Input Development: GIS data and maps for the following landscape,
vegetation, fuel characteristics: stand boundaries, canopy cover, stand height, crown bulk density,
height to live crown, elevation, slope, aspect, and fuel model.

Baseline Fire Behavior Modeling: GIS data and maps for potential current fire behavior
characteristics in the LTB: Crown Fire Activity, Flame Length and Conditional Burn Probability

Treatment Fire Behavior Modeling: GIS data and maps for potential future fire behavior
characteristics in the LTB: Crown Fire Activity, Flame Length and Conditional Burn Probability.
GIS data and maps demonstrating changes in fire behavior and burn probability under full
implementation treatment scenario.

Cost Sensitivity Analysis: Complete a sensitivity analysis to determine if it is cost effective to
treat additional areas to reduce risk further.

Draft Final Report: Draft report summarizing findings from tasks 3-8.

Final Report and GIS Data: Within 30 days of receiving comments on the draft final report, a
final copy will be prepared and delivered. GIS datasets will be made available for download on
project site.

Scientific Publications: Final report will be formatted for and submitted to a peer reviewed
journal
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Proposal: Tahoe Research Supported by SNPLMA 2010
III. Schedule of Milestones and Deliverables
Milestone/Deliverables
Annual accomplishment
reports
Start Date
September,
2011
End Date
September,
2012
Description
Prepare annual summary of accomplishments in
September.
October,
2011
September,
2012
Submit brief progress report to Tahoe Science Program
coordinator by the 1st of July, October, January, and
April.
Pre-Work Conference(s)
July 2011
August
2011
Meet with TRPA and representatives from local land
management agencies discuss proposal
Project Management
July 2011
October
2012
Spatial Infomatics Group will complete all project
management, including preparation of submission of
progress reports
August
2011
December
2011
Use the available high-resolution LiDAR data and
multispectral imagery to develop and refine spatially
explicit Stream Environment Zones (SEZs) and wildlandurban interface (WUI) maps
October
2011
November
2011
Inventory, map and compare all currently completed fuel
treatments, to all planned fuel treatments for next decade.
Fire Severity Analysis
November
2011
December
2011
GIS Data, maps, and graphs of wildfire severity patterns
and distributions within historical fires, and within SEZs
and WUI areas for these fires.
Develop Fire Behavior
Modeling Inputs
August
2011
December
2011
Use the available high-resolution LiDAR data and
multispectral imagery along with secondary datasets to
develop and refine spatially explicit fuel and vegetation
characteristics
Baseline Fire Behavior
Modeling
January
2012
March
2012
March
2012
April 2012
Modeling the potential fire behavior of the planned
implementation of the “Lake Tahoe Basin MultiJurisdictional Fuel Reduction and Wildfire Prevention
Strategy”
Cost Sensitivity
Analysis:
April 2012
May 2012
Complete a sensitivity analysis to determine if it is cost
effective to treat additional areas to reduce risk further.
Draft Final Report:
May 2012
July 2012
Based upon information and findings assimilated in tasks
3 through 8, a draft final report will be generated.
August
2012
September
2012
Within 30 days of receiving comments on the draft final
report, a final copy will be prepared and delivered. GIS
data will be made available online.
September
2012
October
2012
Progress reports
SEZ and WUI
Identification
Analysis of Current and
Planned Fuel Treatments
Treatment Fire Behavior
Modeling
Final Report and GIS
Data
Scientific Publications
Assess current fire hazard in terms of crown fire
potential, flame length, and conditional burn probability.
Report will be formatted for and submitted to a peer
reviewed journal.
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Proposal: Tahoe Research Supported by SNPLMA 2010
IV. Literature Cited
Ager A.A., McMahan A.J., Barrett J.J., McHugh C.W. 2007a. A simulation study of thinning and fuel
treatments on a wildland-urban interface in eastern Oregon, USA. Landsc. Urban Plan. 80:292-300.
Ager, A.A., Finney, M.A., Kerns, B.K., and Maffei, H. 2007b. Modeling wildfire risk to northern spotted
owl (Strix occidentalis caurina) habitat in Central Oregon, USA. For. Ecol. Manage. 246:45-56.
Beche, L.A., S.L. Stephens, and V.H. Resh. 2005. Prescribed fire effects on a riparian and stream
community in the Sierra Nevada: Dark Canyon Creek, California, USA. Forest Ecology and
Management 218:37-59
Chen, Q., 2009. Improvement of the Edge-based Morphological (EM) method for lidar data filtering,
International Journal of Remote Sensing, 30(4), 1069-1074.
Chen, Q., P. Gong, D.D. Baldocchi, and Y. Tian, 2007b. Estimating basal area and stem volume for
individual trees from LIDAR data, Photogrammetric Engineering and Remote Sensing, 73(12),
1355-1365
Chen, Q., 2007, Airborne lidar data processing and information extraction, Photogrammetric Engineering
and Remote Sensing, 73(2), 109-112 (cover story)
Chen, Q., P. Gong, D.D. Baldocchi, and G. Xie., 2007a, Filtering airborne laser scanning data with
morphological methods, Photogrammetric Engineering and Remote Sensing, 73(2),175-185
Chen, Q., D.D. Baldocchi, P. Gong, and M. Kelly, 2006. Isolating individual trees in a savanna woodland
using small footprint LIDAR data, Photogrammetric Engineering and Remote Sensing, 72(8), 923932
Collins BM, Stephens SL, Moghaddas JJ, Battles J. 2010. Challenges and approaches in planning fuel
treatments across fire-excluded forested landscapes. J For 108: 24-31.
Finney, M.A. 1998. FARSITE: fire area simulator — model development and evaluation. U.S. For. Serv.
Res. Pap. RMRS-RP-4
Finney MA. 2006. An overview of FlamMap modeling capabilities. Pages 213-220 in Fuels management
- how to measure success. U. S. Department of Agriculture, Forest Service, Rocky Mountain
Research Station, Portland, OR. RMRS-P41.
Long, J. W. 2009. Introduction to the effects of fuels management in the Tahoe Basin. Pp. 10-40 In
Effects of Fuel Management in the Tahoe Basin: A Scientific Literature Review. Final Report,
USDA Forest Service, Pacific Southwest Research Station and the Tahoe Science Consortium.
Davis, CA.
Moghaddas, J.J., B.M. Collins, K. Menning, E.E.Y. Moghaddas, and S.L. Stephens. 2010. Fuel treatment
effects on modeled landscape level fire behavior in the northern Sierra Nevada. Canadian Journal of
Forest Research 40: 1751–1765
Moody, T.J., S.L. Stephens and M.A. Moritz. 2009. Effects of fuels management on future wildfires in
the Lake Tahoe Basin. Pp. 83-114 In Effects of Fuel Management in the Tahoe Basin: A Scientific
Literature Review. Final Report, USDA Forest Service, Pacific Southwest Research Station and the
Tahoe Science Consortium. Davis, CA.
Nevada Fire Safe Council. 2009. Tahoe Fire and Fuels Team 2008 Progress Report: SNPLMA Funded
Projects and Other Accomplishments. 20p.
Radeloff, V.C., R. B. Hammer, R.B., S.I. Stewart, J.S. Fried, S.S. Holcomb and J.F. McKeefry. 2005. The
wildland-urban interface in the United States. Ecological Applications. 15(3): 799-805.
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Proposal: Tahoe Research Supported by SNPLMA 2010
Safford, Hugh D. David A. Schmidt, and Chris H. Carlson. 2009. Effects of fuel treatments on fire
severity in an area of wildland–urban interface, Angora Fire, Lake Tahoe Basin, California. Forest
Ecology and Management 258 (2009) 773–787.
Scott, J.H., and Burgan, R.E. 2005. Standard fire behavior fuel models: a comprehensive set for use with
Rothermel’s surface fire spread model. U.S. For. Serv. Gen. Tech. Rep. RMRSGTR- 153.
Scott, J.H., and Reinhardt, E.D. 2005. Stereo photo guide for estimating canopy fuelcharacteristics in
conifer stands. U.S. For. Serv. Gen. Tech. Rep. RMRS-GTR-145.
Stephens, S.L., Meixner, T., Poth, M., McGurk, B, Payne, D. 2004. Prescribed fire, soils, and stream
water chemistry in a watershed in the Lake Tahoe Basin. International Journal of Wildland Fire 13:
27-35
Stratton, Richard D. 2004. Assessing the Effectiveness of Landscape Fuel Treatments on Fire Growth and
Behavior. Journal of Forestry, Oct./Nov., vol. 102, no. 7, pp. 32-40
United States Department of Agriculture (USDA). 2007a. An Assessment of Fuel Treatment Effects on
FireBehavior, Suppression Effectiveness, and Structure Ignition on the Angora Fire. R5-TP-025.
38p
United States Department of Agriculture (USDA). 2007b. Lake Tahoe Basin Multi-Jurisdictional Fuel
Reduction and Wildfire Prevention Strategy. United States Department of Agriculture, Forest
Service, Tahoe Regional Planning Agency, Nevada Tahoe Resource Team, Nevada Division of
Forestry, Nevada Division of State Lands, Nevada Fire Safe Councils, California Department of
Forestry and Fire Protection, California Tahoe Conservancy, California StateParks, North Tahoe
Fire Protection District, North Lake Tahoe Fire Protection District, Tahoe-Douglas Fire Protection
District, Lake Valley Fire, Protection District, Meeks Bay Fire, Protection District, South Lake
Tahoe, Fire Department, Fallen Leaf Fire Department. 80p
Van de Water K.M. and North M. 2010. Fire history of coniferous riparian forests in the Sierra Nevada.
Forest Ecology and Management 2260: 384-395.
IV-2
Proposal:: Tahoe Researrch Supportedd by SNPLMA 2010
V. Figu
ures
Figure 1. Sample outpu
ut (Moghaddas et al. 2010) showing
s
changge in potentiall fire size on tthe Plumas Naational
Forest und
der existing co
onditions (left panel) and with planned fueel treatments ccompleted (rigght panel) undeer 97th
percentile weather
w
condittions. Prevailin
ng wind is from
m the southwesst. Study area sshown is 45,000 acres.
3
Proposal:: Tahoe Researrch Supportedd by SNPLMA 2010
Figure 2. Sample outpu
ut (Moghaddass et al. 2010) showing channge conditionaal burn probabbility on the P
Plumas
National Forest
F
with plaanned fuel treeatments comp
pleted (right ppanel) under 997th percentile weather condditions.
Prevailing wind is from the southwestt. Areas of darrker green indiicate a reductiion in conditioonal burn probability
under mod
deled condition
ns. Study area shown
s
is 45,000 acres.
4