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Vegetation Mapping using MSN Analysis in INFORMS

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Vegetation Mapping using MSN Analysis in INFORMS. INFORMS INtegrated FORest Management System MSN Most Similar Neighbor Analysis. Overview. Use MSN to create a current wall to wall vegetation layer utilizing NRIS FSVeg, DEM and Landsat data.

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vegetation mapping using msn analysis in informs

Vegetation Mapping using MSN Analysis in INFORMS


INtegrated FORest Management System


Most Similar Neighbor Analysis

  • Use MSN to create a current wall to wall vegetation layer utilizing NRIS FSVeg, DEM and Landsat data.
  • Utilize the Forest Vegetation Simulator (FVS) to grow stand data to current and future year conditions.
  • Create alternatives and model vegetation treatments (i.e. thinning) for NEPA analysis and impacts evaluation.


A project-level landscape analysis framework.

Most Similar Neighbor (MSN)

A powerful application used to impute available ground-based inventory data to non-inventoried units.


Forest Service Field-Sampled Vegetation database.

Forest Vegetation Simulator (FVS)

An individual-tree, distance-independent growth and yield model.

what is most similar neighbor msn
What is Most Similar Neighbor (MSN)?
  • The MSN application is a powerful tool used to impute available ground-based inventory data to non-inventoried units.
  • The MSN method uses available data from the ground-based sample units and globally available data measured on all sample units to guide the imputation.
  • Examples of global information for all sample units include topographic data and satellite imagery.
  • Landscape of vegetation data is available for analysis based on imputations from the MSN process.
msn calibration
MSN Calibration
  • Most Similar Neighbor analysis command files are prepared and tested for each FVS variant. Calibration (selection of variables) is the most critical part of Most Similar Neighbor analysis.
  • Variables contained in the command files are carefully selected in cooperation with the researchers who developed the Most Similar Neighbor application and methods.
  • Once calibrated, there is a standardized methodology for each FVS variant.
msn calibration variables
MSN Calibration Variables

Calibration is the process of finding the correct combination of global and sampled data for each FVS variant.

Global Data = Data that is available for all polygons (i.e. slope, aspect, Landsat, etc.).

Sampled Data = Data that is available for sampled polygons (i.e. stand exams) or other vegetation sampling (i.e. range data, fuels plots). Examples include Basal Area, Trees per Acre, QMD, Volumes, etc.

msn mapping status by national forest
MSN MappingStatus by National Forest

Region 1

  • Idaho Panhandle

Region 3

  • Lincoln
  • Carson
  • Gila
  • Coconino
  • Kaibab
  • Apache-Sitgreaves2 districts

Forests Completed

Forests In Progress

Region 6

  • Malheur
  • Umatilla
  • Wallowa-Whitman2 districts
  • Deschutes2 districts
  • Siuslaw1 district

Region 1

  • Nez-Perce

Region 2

  • Shoshone

Region 3

  • Santa-Fe
  • Cibola
  • Corrinodo
  • Tonto
data requirements
Data Requirements
  • Populated NRIS FSVeg database.
  • Non-forested survey data (i.e. rangeland data).
  • Local Vegetation coverage which is related to the FSVeg data.
  • DEM derived grids for Slope (in radians), Slope Catchment Area, Insulation and Duration.
  • Landsat grids for reflectance values for bands 1, 2, 3, 4, 5 and 7.
vegetation grouping
Vegetation Grouping
  • Most Similar Neighbor analysis is run separately on Forested and Non-Forested polygons.
  • Vegetation polygons must be divided into three groups by the local GIS shop by adding an attribute into the local stands layer:
    • Forested Vegetation (FV)
    • Non-Forested Vegetation (NF)
    • Non-Vegetated (NV)
preparing global and sampled data in informs
Preparing Global and Sampled Data in INFORMS
  • Global Data Preparation Tool: Summarizes data from the DEM and Landsat Scene into an input format for Most Similar Neighbor analysis.
  • Sampled Data Preparation Tool for Forested Polygons: Grows all stand data forward to the year of the Landsat scene to calibrate stand data to the current condition using FVS.
  • Sampled Data Preparation Tool for Non-Forested Polygons: Data is currently used to impute Fuel Models and other light fuel vegetative data (described in the next series of slides).
non forest data preparation
Non-Forest Data Preparation
  • Fuels data is being loaded into the FSVeg database.
    • Summary cover by lifeform (grass, forbs, shrubs, trees).
    • Non-Forest fuels transects as defined by Texas A&M process (described in the next few slides). (Texas A&M BRASS-G website also utilizes this data.)
  • This data is modeled using the Phygrow growth simulator.
brass g website http brass tamu edu
BRASS-G Website
  • BRASS-G: Burning Risk Advisory Supporting System for Grazinglands.
  • BRASS-G is maintained by Texas A&M University.
  • BRASS-G presents an interactive map interface to non-forested vegetation polygons.
  • Polygons are populated using the Most Similar Neighbor process.
  • Burning conditions are updated daily.
  • Every imputed stand has its own unique vegetation modeled using localized weather using Phygrow.
navigation map for brass g lincoln nf new mexico
Navigation Map for BRASS-G (Lincoln NF – New Mexico)

Polygon shading represents maximum 30-minute burn area predicted for the next week.

By double-clicking on a polygon, current burning condition graphs will be displayed.

brass g low 30 minute burn spread
BRASS-G: Low 30-minute burn spread
  • These graphs represent:
  • 30-minute burn area
  • Spread rate
  • Flame length
  • Fuel Moistures
  • Weather variables
  • The prediction points are graphed in 3-hour increments.
  • The weather is based on 2.5km grids from NOAA.
brass g high 30 minute burn spread
BRASS-G: High 30-minute burn spread

This is based on the actual vegetation grown to this point in time. This is based on weather and soil inputs.

2-3 years of previous daily weather variables are used to grow the plants to their current condition. This is done primarily using soil water budgets.

brass g imputed area photos
BRASS-G: Imputed area photos

This is a photo taken during sampling.

Imputed stands have a photo from the reference stand associated with the record.

Click the photo link to see an sample photo of the area.

running msn
Running MSN
  • MSN is run as a tool in INFORMS once all of the data is prepared.
  • ‘Go/no go’ statistics are presented when MSN is run. This advises the user whether the MSN run should be used for further analysis.
  • Statistics are also produced for specific vegetation attributes resulting from the MSN run. (e.g. basal area, stand height, etc.)
msn results
MSN Results
  • The NRIS FSVeg database contains a table, NRV_MSN_FOR_USE, that stores the MSN results.
  • This table contains a list of links of un-sampled stand polygons pointing them to their ‘most similar neighbor’ with sampled data.
  • This process allows INFORMS tools to use imputed data without loading hypothetical data into the corporate FSVeg stand and tree tables.
msn report for forested vegetation
MSN Report for Forested Vegetation

Produced with each MSN run is the MSN Report. It is a text file summarizing the key elements of the MSN run. These are the attributes in the vegetation map.

msn forest vegetation quality
MSN Forest Vegetation Quality

Gray = Reference (sampled) stands

Green = OK Quality (Imputed)

Red = Poor Quality (Imputed)

Yellow = Non-Veg (rocks, lakes, etc.)

Brown = Non-Forest (grass, shrubs, etc.)

reference stands
Reference Stands

NRV_MSN_FOR_USE Reference Stands

  • Stands with sampled data.
  • Note: FOR_GIS_LINK and USE1_GIS_LINK are the same.
imputed stands
Imputed Stands

NRV_MSN_FOR_USE Imputed Stands

  • Stands that have not been sampled.
  • Note: FOR_GIS_LINK and USE1_GIS_LINK are different.
  • USE1_GIS_LINK is the best match.
imputed msn stands
Imputed MSN Stands

Red = MSN Imputed Stands

Blue = FSVeg Stand Exams

Yellow = No Data

how does msn help you
How does MSN help you?
  • Provides a method to easily maintain and annually update a current vegetation layer.
  • Provides a current wall-to-wall vegetation layer containing base-scale attributes.
  • Allows a site to grow the current vegetation layer forward into the future using FVS for analysis of future conditions. Some examples are:
    • Current and Future Fire Regime Condition Class (FRCC)
    • Current and Future Vegetative Structural Stage (VSS)
    • Current and Future individual stand burning conditions
  • Allows for modeling of treatments to the vegetation layer for NEPA analysis and impacts evaluation.
vegetation layer
Vegetation Layer

The results from FVS and MSN are used to generate current and future vegetation layers for each decade in the simulation.

Fuel Model – Same Year

With MSN

Without MSN

base fvs vegetation layer
Base FVS Vegetation Layer

A wall-to-wall base vegetation layer is built for each decade in the simulation. This layer contains information such as basal area, stand height, qmd, canopy cover and more.

msn accuracy assessment
MSN Accuracy Assessment
  • An accuracy assessment methodology exists for MSN as used in INFORMS. Cooperators were:
    • Natural Resource Information System (NRIS)
    • Rocky Mountain Research Station (RMRS)
    • Remote Sensing Applications Center (RSAC)
  • Plans are to complete an accuracy assessment on the following forests:
    • Carson National Forest (Region 3)
    • Deschutes National Forest (Region 6)
  • After several assessments are complete, this should provide a standard by which to evaluate and improve base vegetation layer maps.
alternative building in informs
Alternative Building in INFORMS
  • Vegetative future conditions are created by defining alternatives and applying vegetative treatment prescriptions.
  • There are three methods for applying prescriptions to a stand or a portion of a stand. A tool is available to split a stand.
  • If MSN analysis is used, prescriptions can be applied to imputed stands (stands which do not have a stand exam in FSVeg).
  • Treatments are applied through FVS keyword files. This changes future condition vegetative values.
basal area before and after treatment same year
Basal Area Before and After Treatment – Same Year

Fuels Reduction Thinning Treatment

No Treatment

  • INFORMS and MSN currently provide a methodology for vegetative treatments and fuels analysis.
  • INFORMS provides the ability to produce multiple alternatives for various treatment scenarios.
  • MSN provides the ability to do landscape-level fuels analysis (i.e. fire spread).
  • Several MSN accuracy assessments are currently being completed to provide ID teams with more defensible results.
for more information
For More Information
  • Steve Williams/Eric Twombly – Project Leads
  • Lynne Bridgford – Developer
  • Jonathan Marston – Developer