larry stanislawski , michael howard

Larry Stanislawski, Michael HowardCenter of Excellence for Geospatial Information Science (CEGIS), United States Geological Survey, Rolla MO

Marc-Olivier Briat, Edith PuntEsri, Inc., Redlands CA

Cynthia Brewer Department of Geography, Pennsylvania State University, Unversity Park PA

Barbara ButtenfieldDepartment of Geography, University of Colorado-Boulder, Boulder CO

Density-Stratified Thinning to Support Automated Generalization of

Transportation

15th ICA Generalisation Workshop, Istanbul, Turkey, September 13-14, 2012

Outline

• Esri Thin Road Network Tool

• Density-stratified Thinning

• Results of Stratified Thinning

• Summary Statements and Future Work


Cartography Geoprocessing Toolbox

• ArcGIS 10 introduced contextual generalization tools that consider relationships between features from multiple layers- Maintain representative patterns,

density, and character- Resolve conflicts between

symbolized features

Esri Thin Road Network tool

• Maintain pattern and density while retaining connectivity• Keep significant roads only

- Balanced by road classification- Retain specific features by locking

• Visibility controlled by attribute, easy to modify

Esri Thin Road Network Tool


Inputs:1. Road network features,2. Minimum length,3. Invisibility field, and4. Hierarchy field

Marks features for elimination to create a simplified pattern of roads that maintains connectivity, representative pattern, and density

Limitations of Thin Road Network Tool• Preprocessing• A single minimum length can homogenize local density

variations (more than expected)• Difficult to set tolerance values for tool

Preprocessing for Thin Network Tool


• Road network featureso Projected coordinate systemo Remove coincident featureso Transfer names to retained featureso Multi-part features to single-part featureso Ensure features are split at intersections

• Hierarchy fieldo Compute importance values based on

road class (and names where class is missing)

Test Data: Four Subbasins in Rural Iowa and Part of Atlanta Metropolitan Area

Part of Atlanta MSA• ~10,000 sq km• Dense urban area• Atlanta MSA pop. ~5.4M• Over 393,000 road features• Nearly 49,000 km of roads


Four subbasins in Iowa:• ~24,000 sq km• Rural midwest agricultural area • Des Moines ~580,000 persons• Over 109,000 road features• Nearly 36,000 km of roads

Road data from transportation layer of USGS Best Practices (BP)database

Test Methods1. Subdivide data into density classes

• Iowa: < 1.50 and > 1.50 km / sq km, min. polygon area = 45 sq km• Atlanta: < 2.50, 2.50 to 4.50, and > 4.50 km / sq km, min. polygon area = 45 sq km.

2. Determine 100K target density estimate for each class using Radical Law3. Run thin network tool multiple times to find which minimum length comes closest to

the 100K target density for each density class4. Extract visible lines for each class using the invisibility field5. Compare resulting 100K extracted lines with 100K DLG lines by subtracting the raster

road-density thinned Best Practices (BP) data from the 100K DLG roads (300m grids).


IowaResults


BP and 100K DLG RoadsStudy area in Iowa


DLGs compiled 1981 to 1985Compiled

2011

Tom Tom and 100K DLG RoadsStudy area in Iowa


Tom Tom Roads and Density Strata(class breaks: < 1.5 and more than 1.5 km per sq km)


Thinning Tom Tom to 100K Radical LawThinning entire data set Urban Rural Partitions

Density Class Rural Urban

Density (km/sq km)

Percent from Radical Law

Density (km/sq km)


Density Class Breakless than 1.50

more than 1.50

Average Density of class at 1:24,000 1.24 3.47Radical Law Density Estimate for 1:100,000 0.61 1.70Minimum Length 1 km 1.14 87.90 2.50 46.98Minimum Length 2 km 1.10 81.67 2.12 24.44Minimum Length 4 km 1.06 74.86 1.80 5.65Minimum Length 10 km 0.63 4.35 1.19 -29.98


Tom Tom Roads Thinned to Radical Law 100K


AtlantaResults


TomTom Roads and Density Strata(class breaks: < 2.5, 2.5 to 4.5, and more than 4.5 km per sq km)


Thinning Tom Tom to 100K Radical LawThinning entire data set Urban Rural Partitions


Density Partition Density (km/sq km)

Density Class Rural Suburban Urban

Density (km/sq km)


Density (km/sq km)


Density (km/sq km)


Density Class Breakless than 2.50

less than 4.50

more than 4.50

Average Density at 1:24,000 1.65 3.35 7.20Radical Law Density Estimate for 1:100,000 0.81 1.64 3.53Minimum Length 500 m 1.53 88.83 2.54 54.88 5.03 42.59Minimum Length 1000 m 1.32 63.04 1.94 18.06 3.74 5.89Minimum Length 1500 m 1.20 47.59 1.67 1.37 3.18 -9.71Minimum Length 2000 m 1.13 39.59 1.54 -6.26 2.88 -18.34Minimum Length 2500 m 1.09 34.49 1.47 -10.38 2.69 -23.85

Tom Tom Roads Thinned to Radical Law 100K


Left: All Atlanta TomTom Roads

Middle: TomTom Roads thinned using 2 km minimum length

Right: TomTom Roads thinned in three density-strata

10 km

• Density-stratification is a flexible approach to use Thin Network Tool that preserves local density variation better than using a single minimum length

• Future work:o Select formal density class breaks for stratifying the countryo Identify thinning requirements for 100K and smaller scaleso Automate selection of minimum length for each density classo Ensure feature connectivity at density-class boundarieso Test a complete work flow of the Esri transportation

generalization tools (include merge divided highway tool, remove road conflicts tool, etc.) [is this necessary to include…]

o Test and implement parallel processing to improve performance

o Test network navigation capabilities before and after thinning


Summary and Future Work

larry stanislawski , michael howard

Documents