Overview and Example 

Application of the 

Landscape Treatment 

Designer

Alan A. Ager, Nicole M. Vaillant, David E. Owens, 

Stuart Brittain, and Jeff Hamann

United States 

Department of 

Agriculture

Forest Service

Pacific Northwest 

Research Station

General Technical Report 

PNW-GTR-859

February 2012

DEPAR TMENT OF AGRICULT URE
Authors

Alan A. Ager is an operations research analyst, and Nicole M. Vaillant is a fire 

ecologist, Western Wildland Environmental Threat Center, 3160 E 3rd Street, 

Prineville, OR 97754; David E. Owens is a fuel planner, Central Oregon Fire 

Management Service, Bureau of Land Management, 3050 NE 3rd Street, Prineville, 

OR 97754; Stuart Brittain is a senior programmer, Systems for Environmental 

Management, 1280 S 3rd Street W 2, Missoula, MT 59801; and Jeff Hamann is 

president of Forest Informatics, Inc., P.O. Box 1421, Corvallis, OR 97339.

Cover photograph by Frank Vanni.

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multiple use management of the Nation’s forest resources for sustained yields of wood, 

water, forage, wildlife, and recreation. Through forestry research, cooperation with the 

States and private forest owners, and management of the National Forests and National 

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Abstract

Ager, Alan A.; Vaillant, Nicole M.; Owens, David E.; Brittain, Stuart; 

Hamann, Jeff. 2012. Overview and example application of the Landscape Treatment Designer. Gen. Tech. Rep. PNW-GTR-859. Portland, OR: U.S. Department 

of Agriculture, Forest Service, Pacific Northwest Research Station. 11 p.

The Landscape Treatment Designer (LTD) is a multicriteria spatial prioritization and 

optimization system to help design and explore landscape fuel treatment scenarios. The 

program fills a gap between fire model programs such as FlamMap, and planning systems 

such as ArcFuels, in the fuel treatment planning process. The LTD uses inputs on spatial 

treatment objectives, activity constraints, and treatment thresholds, and then identifies 

optimal fuel treatment locations with respect to the input parameters. The input data 

represent polygons that are attributed with information about expected fire behavior and 

the polygon’s overall contribution to one or more landscape management objectives. The 

program can be used in a number of different ways to explore treatment priority and decision rules that manifest themselves on large (1 million ha) landscapes as spatially explicit 

treatment strategies. This report describes the LTD program and an example application 

on the Ochoco National Forest. Further information including program download and a 

tutorial can be found at http://www.fs.fed.us/wwetac/ltd.

Keywords: Fuel treatment, spatial optimization, forest planning, forest restoration.
Contents

1 Introduction

3 The LTD Program

3 Input

3 Types of Scenarios

5 Outputs

5 Example Application

7 Additional Options in LTD

10 Downloads and Other Documentation Information

10 Acknowledgments

10 English Equivalents

11 References
1

Overview and Example Application of the Landscape Treatment Designer

Introduction

The Landscape Treatment Designer (LTD) is a multicriteria spatial prioritization and optimization system to help design and explore landscape fuel treatment 

scenarios. The program fills a void between fire model programs such as FlamMap 

(Finney 2006) and planning systems like ArcFuels (Ager et al. 2011), in the fuel 

treatment planning process. The LTD uses inputs on spatial treatment objectives, 

activity constraints, and treatment thresholds, and then identifies optimal fuel 

treatment locations with respect to the input parameters. The input data represent 

polygons that are attributed with information about expected fire behavior and the 

polygon’s overall contribution to one or more landscape management objectives. 

These can include nonspatial attributes such as stand conditions, or spatial attributes such as the distance to fire-susceptible landscape features like critical habitat 

or residential structures. The user supplies an activity constraint (e.g., area treated) 

that represents the maximum area that can be treated based on fuel treatment budget allocations or other constraints (fig. 1). The program can be used in a number of 

ways to explore treatment priority and decision rules as they manifest themselves 

on large (1 million ha) landscapes as spatially explicit treatment strategies. In a 

simple application, the program operates the same as sorting polygons based on 

fields of interest, and then selecting polygons from the sorted list until some total 

area limit is met. However, LTD automates the process and allows for combining 

several attributes in weighted combinations so that treatment alternatives can be 

quickly generated and mapped. The LTD also has an aggregation constraint option 

for coordinating treatments to build low-hazard fire containers (e.g., contiguous 

areas) that can serve as wildland-fire-use areas or large-scale prescribed fire treatment areas. The aggregation constraint forces the program to build patches within 

which threshold conditions at the stand level are not exceeded using the decision 

framework in figure 2. Stands that exceed fire behavior thresholds are treated until 

the treatment constraint is reached. For instance, to restore natural fire, treatments 

can be spatially allocated such that a large patch is created within which fire 

behavior thresholds are not exceeded, and the total area treated does not exceed 

a predetermined threshold. A nonadjacency problem would allocate treatments 

based on objective values regardless of their location relative to each other. Another 

implementation might use distance and azimuth objectives to allocate treatments 

around features of interest, such as a wildland-urban interface (WUI) or critical 

habitat for threatened and endangered species. Up to five objective values can be 

blended with weighting factors to build hybrid scenarios that allocate investments 

to multiple values of interest. For instance, a 50 percent weight could be put on 

treatments near the WUI and a 50 percent weight on treatments for restoration 

objectives. Because attribute values can include distance measures, scenarios with 
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GENERAL TECHNICAL REPORT PNW-GTR-859

Start at first

polygon

Find nearest polygon

not in current project

Move to next

polygon

and start new

search

Write patch

outputs

Increment

activity constraint

Add polygon to

project and increment

objectives

Record patch

location and 

objective

Is treatment

threshold

exceeded?

All polygons

tested as

project

centroids

Is activity

constraint

exceded? No Yes

Yes

No Yes

No

Figure 2—Flow chart of program control for the Landscape Treatment Designer program showing 

the decision framework for simulations that use the aggregation option. 

Polygon Shapefile

Fire behavior

treatment threshold(s)

Objective

function(s)

X Y Area

Activity

constraint(s)

LTD

program

Figure 1—Diagram showing the input data and outputs of the Landscape Treatment Designer (LTD) 

program. Each record of the polygon shapefile contains data on (1) polygon XY centroid, (2) polygon 

area, (3) objectives, and (4) constraints. The latter two variables can be integer or real values. The 

outputs include a polygon shapefile that identifies the objective value for each polygon, and a code 

that specifies whether it was selected to be in a patch, and whether it was also selected for treatment.
3

Overview and Example Application of the Landscape Treatment Designer

spatial fidelity to particular landscape features (roads, WUI, etc.) can be used to 

drive treatment locations (e.g., Ager et al. 2010). 

This paper describes the LTD program, including an example application on the 

Ochoco National Forest. Further information including program download and a 

tutorial can be found by following the links at http://www.fs.fed.us/wwetac/ltd/.

The LTD Program

Input

The LTD program uses an ArcGIS®1 polygon shapefile containing forest stand 

boundaries and an attribute table with fields describing each stand’s characteristics 

with respect to (1) treatment threshold (e.g., flame length, stand density index); 

(2) ecological, financial, or other objectives and respective weighting factors that 

are used for the objective function; and (3) investment or activity constraint (e.g., 

area or financial value required for treatment). The input data can be derived from 

Landfire (Rollins 2009), FlamMap (Finney 2006), the Forest Vegetation Simulator, 

and corporate spatial data. The stand value attribute can be represented by both 

relative spatial (e.g., distance to fire-susceptible landscape features like critical 

habitat or residential structures) and nonspatial attributes (e.g., stand density, crown 

fire potential). Attribute fields must include the polygon coordinates (centroid 

XY) and the area (fig. 3). The activity constraint entered by the user represents the 

total possible investment in the management activities based on budgets or other 

constraints. The treatment threshold is a constant that when exceeded by the value 

in a particular polygon, a treatment is triggered. Objective Direction can either be 

maximized (1) or minimized (0). The Check Availability option allows the user to 

only permit treatments in stands that are available for treatments. When checked, 

the program reads a user-specified field that indicates whether stands are available 

for treatments. The field is coded with 1 to indicate a stand is available for treatment, and a 0 otherwise. 

Types of Scenarios

Several types of scenarios can be performed with a given set of input data. Options 

include (1) aggregation, (2) iterate until all treated, and (3) sensitivity runs. When 

the first option is invoked, LTD builds a contiguous patch that maximizes the objective function while not exceeding the investment constraint. Stands that exceed the 

established treatment threshold count against the investment constraint. Without the 

aggregation option, LTD simply locates the polygons that maximize the objective 

1 The use of trade or firm names in this publication is for reader information and does not 

imply endorsement by the U.S. Department of Agriculture of any product or service.
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GENERAL TECHNICAL REPORT PNW-GTR-859

function within the activity constraints, irrespective of their spatial relationships. 

The iteration option repeats the process of maximizing the objective function to 

create multiple planning areas, until all stands in the landscape have been either 

treated or included in a patch. With the aggregation option enabled, this process 

creates multiple patches (i.e., planning areas) of decreasing treatment priority. The 

sensitivity option allows the user to specify floor, ceiling, and an interval for input 

parameters that LTD will use to simulate multiple runs to see how changing input 

parameters affect the outputs. 

Figure 3—Screen capture of the Landscape Treatment Designer program showing the run parameters for example run No. 1 described 

in the text. The input parameters call for maximizing indices that describe stand size class, and structure, and fuel hazard (table 2, 

OS_SUM, VI_SUM, FH_SUM) while treating polygons that have a predicted flame length that exceeds 2 m. The activity constraint is 

set at 9000 ha, meaning each patch can include a maximum of 9000 ha that exceed the treatment threshold.
5

Overview and Example Application of the Landscape Treatment Designer

Outputs

Three types of output files are generated with each run: (1) a text file with all the 

input data with treatment locations indicated, (2) a summary text file of input 

parameters and output results, and (3) a shapefile with an attribute table that identifies patch locations and stands selected for treatments. 

Example Application

The example application was derived from the Ochoco National Forest where a 

vegetation action plan2 identified vegetation management priorities for the forest. It 

represents a typical approach used by national forests to prioritize vegetation management activities and develop strategic plans for restoration and fuel management. 

The priority schema was based on forest stand structure, overstocking, and fuel 

hazard (tables 1, 2). The above three indices were then combined into an objective 

function with equal weights. The stand structure index identified multilayer stands 

with large trees and overstocked conditions according to the stand density index 

(table 2). Fire hazard rating was developed from a combination of flame length and 

crown fire activity derived from FlamMap runs (table 1). Overstocked condition 

was measured by comparing the current stand density with the maximum as specified by the stand density index (table 2). The stand structure and density indices 

were calculated by processing gradient nearest neighbor data (Ohmann and Gregory 

2002) through the Forest Vegetation Simulator. 

To trigger a treatment, we identified a treatment threshold as the average flame 

length for the stand as determined from a FlamMap (Finney 2006) simulation. We 

then set a treatment threshold at 2 m, which represented minimum conditions where 

2 Owens, D. 2011. Unpublished report. On file with: Ochoco National Forest Supervisors 

Office, 3050 NE Third St., Prineville, OR 97754. 

Table 1—Definition of fuel hazard used for the Ochoco 

National Forest examplea

Crown fire potential 

Flame length Surface Passive Active

Feet (meters)

0–2 (0–0.6) Low Low Low

2–4 (0.6–1.2) Low Low Medium

5 (1.5) Low Medium Medium

6 (1.8) Medium Medium Medium

6–8 (1.8–2.4) Medium High High

8–11 (2.4–3.4) High High High

11–20 (3.4–6.1) High High High

20+ (6.1+) High High High

a See Finney 2006 for crown fire definitions.
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GENERAL TECHNICAL REPORT PNW-GTR-859

fire behavior would likely result in a significant loss of ecological and economic 

value in the stand. The total area assigned for management activity, the activity 

constraint, was set at a minimum of 6000 ha and a maximum of 9000 ha. Although 

this level of activity is relatively high for a typical fuel treatment project, we chose 

the higher value for illustration purposes as described below. 

We performed two simulations to demonstrate LTD. The first run (figs. 3 and 4) 

maximized the objective function with aggregation, meaning that the LTD program 

identified a contiguous patch on the landscape that contained the largest objective 

function value (maximizing area of stands that are overstocked and have high fuel 

hazard), treating those polygons that exceeded the flame length threshold (>2 m, 

fig. 2). Note that polygons that did not exceed the treatment threshold were also 

included in the patch. The run also used the iteration feature (Enable Iteration), such 

that successive patches were created that each maximized the objective given that 

the previous patches were not available for consideration. The resulting output (fig. 

4) identified 16 patches in order of decreasing priority. These represent potential 

project areas that best meet the intent of the forest restoration and 

treatment objectives. 

The second run (figs. 5 and 6) maximized the same objective function without 

the aggregation constraints. The result was the identification of stands that maximized the objective function and had flame lengths >2 m (exceeded the treatment 

threshold). For clarity, only the first four sets of stands identified in the run are 

shown in figure 6. The solution shows the location of the stands that best satisfy the 

objectives under the treatment threshold and constraints. 

Table 2—Vegetation scoring system to determine treatment and restoration priorities 

for the Ochoco National Forest examplea

Variable Specification Objective score

Stocking Overstocked stands 3+ in (8 cm) dbh 1

at or above lower stand density index 

management zone

Overstocked stand 8 to 20.9 in (20 to 53 cm) 2

dbh at or above the lower stand density 

index management zone

Structure size class Grass/forbs/shrubs 0

Seed/saplings 0

Poles (4 to 8.9 in [10 to 23 cm] dbh) 1

Small (9 to 20.9 in [23 to 53 cm] dbh) 2

Med/large (21+ [53+ in [53+ cm] dbh) 1

Fuel hazard Low 0

Medium 1

High 3

a Fuel hazard is defined in table 1. Dbh is diameter at breast height.
7

Overview and Example Application of the Landscape Treatment Designer

Additional Options in LTD

Many other options are available in LTD to experiment with treatment strategies. 

The reader is referred to the tutorial for more detailed examples. Selected options 

are described below.

Enable iteration—

Step treatments and constraints—This option allows the user to perform a batch 

run where the activity constraint and treatment threshold is incremented by fixed 

amounts. The option can only be used for runs where a single threshold and constraint is specified. 

Figure 4—Map of outputs from example run No. 1 for the Ochoco National Forest as described in figure 3. Increasing 

patch numbers represent decreasing treatment priority based on the objective function value. For example, patch No. 1 (red) 

contained a set of contiguous stands that collectively maximized the objective function with the specified treatment area 

constraint. The black lines represent major roads on the forest.
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GENERAL TECHNICAL REPORT PNW-GTR-859

Disable shapefile outputs—

Disabling the point shapefile outputs is used for batch runs to reduce the volume of 

output files.

Conditional objective—

Increase only on treat—This option is intended for runs that use the aggregation 

option where the objective is not incremented for stands that are added to a patch 

unless they exceed the treatment threshold. Thus the objective is not realized unless 

a treatment is allocated to the stand.

Figure 5—Screen capture of the Landscape Treatment Designer program showing the run parameters for the example run No. 2 

described in the text. The input parameters call for maximizing indices that describe stand size class, and structure, and fuel hazard 

(table 2, OS_SUM, VI_SUM, FH_SUM) while treating polygons that have a predicted flame length that exceeds 2 m. The activity 

constraint is set at 9000 ha, meaning that sets of stands that maximize the objectives are identified until the constraint is met, and the 

process repeated until less than 8000 ha (minimum value) of stands needing treatment are remaining. 
9

Overview and Example Application of the Landscape Treatment Designer

Check availability—

This option is available for landscapes where treatments are not allowed on specific 

land allocations like wilderness and conservation reserves. A user-defined integer 

field (0/1) allows users to specify which stands can be treated.

Objective direction—

Allows the user to minimize or maximize the objective function. 

Treatment efficiency—

The treatment efficiency option was added to allow the creation of patches with 

variable fire severity. A specified percentage of stands are not treated, despite the 

fact that they exceed the fire behavior threshold. The stands are chosen at random. 

This option was added to address research aimed at creating landscapes that retain 

a mix of potential fire behaviors. 

Figure 6—Map of outputs from example run No. 2 for the Ochoco National Forest showing stand treatment priority without the 

use of the aggregation feature. The colors identify groups of stands of decreasing treatment priority based on the objective function. The run parameters are shown in figure 5. 
10

GENERAL TECHNICAL REPORT PNW-GTR-859

Downloads and Other Documentation Information

To obtain the LTD program, go to http://www.fs.fed.us/wwetac/ltd/. Demonstration 

data are available to download for LTD at the Web site and tutorial (Vaillant and 

Ager 2011).

Acknowledgments

We thank Ayn Shisky and Miles Hemstrom for many useful comments to an earlier 

draft. We also thank Leo Yanez of the Deschutes National Forest for the example 

data sets and development of the treatment objective variables. We also thank 

Michele Buonopane for editorial assistance. This project was funded by the USDA 

Forest Service, Pacific Northwest Research Station, Western Wildland Environmental Threat Assessment Center.

English Equivalents

When you know: Multiply by: To find:

Centimeters (cm) 0.394 Inches

Meters (m) 3.28 Feet

Kilometers (km) 0.621 Miles

Hectares (ha) 2.47 Acres
11

Overview and Example Application of the Landscape Treatment Designer

References

Ager, A.A.; Vaillant, N.M.; Finney, M.A. 2011. Application of fire behavior 

models and geographic information systems for wildfire risk assessment and 

fuel management programs. Journal of Combustion. Vol. 2011, Article ID 

572452. 19 p.

Ager, A.A.; Vaillant, N.M.; Finney, M.A. 2010. A comparison of landscape fuel 

treatment strategies to mitigate wildland fire risk in the urban interface and 

preserve old forest structure. Forest Ecology and Management. 259: 1556–1570.

Finney, M.A. 2006. An overview of FlamMap fire modeling capabilities. In: Fuels 

management—how to measure success. Proceedings, RMRS-P-41. Fort Collins, 

CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research 

Station: 213–220.

Ohmann, J.L.; Gregory, M.J. 2002. Predictive mapping of forest composition and 

structure with direct gradient analysis and nearest-neighbor imputation in coastal 

Oregon, USA. Canadian Journal of Forest Research. 32: 725–741.

Rollins, M.G. 2009. LANDFIRE: a nationally consistent vegetation, wildland fire, 

and fuel assessment. International Journal of Wildland Fire. 18: 235–249.

Vaillant, N.M.; Ager, A.A. 2011. Tutorial for the Landscape Treatment Designer. 

Unpublished paper. http://www.arcfuels.org/ltd/download.shtml. 

(October 1,2011).

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