BEN ANDERSON

PROJECT MANAGERUNIVERSITY OF LOUISVILLE

CENTER FOR HAZARDS RESEARCH AND POLICY DEVELOPMENT

BEN.ANDERSON@LOUISVILLE.EDU

Using Dasymetric Mapping to Develop a Population Grid for

Hazard Risk Assessments

Presentation Outline

Census Data Aggregation Levels

Problem Statement

Dasymetric Mapping

Population Grid

Objectives

Introduction to Dasymetric Mapping

Application of Dasymetric Mapping

Underlying need for Standardizing Area

Use in Risk Assessment

Census Data Aggregation Levels

Aggregation Levels Country State County Tract Block Group Block

Tracts, Block Groups, and Blocks are aggregation levels that are designed to be similar in population but not area.

Census Tracts

Census Tracts are a statistical subdivision of a county

Tracts are designed to have between 1,500 and 8,000 persons

Tracts can change from Census to Census as the population changes.

In Kentucky Counties have between 1 tract and 191 tracts in the 2010 Census

Census Block Groups

Census Block Groups are a statistical subdivision of Census Tracts

Block Groups are designed to have between 600 and 3,000 people with an optimum size of 1,500

Block Groups can change from Census to Census

Block Groups are the smallest level which the Census bureau publishes sample data As of the 2010 Census all data excluding population

count, sex, age, race, or ownership status is sample data.

Census Blocks

Census Blocks are a statistical subdivision of Block Groups

Blocks in urban areas are often literally a city block, in rural areas blocks can be much larger In KY Blocks range from 94.22 to less than .001

square kilometers. Blocks are the smallest subdivision that the

Census releases full count data on.

Comparing Risk

Center for Hazards Research has done Hazard Risk Assessments Down to the block level for Kentucky.

CHR’s latest state plan relied on count data within blocks to develop a risk score. CHR’s Risk score is a combination of Exposure and Hazard Risk Using pure count data results in a rural bias for increased risk

Increased exposure• Larger blocks may have a higher population but lower density• Larger blocks may also contain more assets: Roads, Rail, Bridges.

Increased hazard risk • Larger Blocks also have more area exposed to a hazard and may

potentially be affected by more incidents due to the increased area

Dasymetric Mapping

Method of mapping population within an aggregation area using population data and land cover data

http://pubs.usgs.gov/fs/2008/3010/fs2008-3010.pdf

USGS Dasymetric Mapping Tool

A free tool which simplifies the Dasymetric process

Requires Land Cover data to be broken down into 4 Classes User defined breaks Suggests –

High Density Low Density Non-Urban Inhabited Uninhabited

Link: http://geography.wr.usgs.gov/science/dasymetric/Or Google: Dasymetric Mapping USGS

USGS Dasymetric Tool Key functions

Empirical Sampling Empirical sampling is used to determine the fraction of the census

unit's population that should be allocated to each inhabited class for the study area

Areal Weighting The ‘population density fraction’ must be adjusted by the

percentage of the block-group’s total area that each ‘inhabited class’ occupies. A ratio is calculated for each ‘inhabited class’ representing the percentage of area that an ‘inhabited class’ actually occupies within a block group to the expected percentage. The area ratio is used to adjust the ‘population density fraction’ accounting for the variation of both the population density and area for the different ‘inhabited classes’ for each block group.

Source: http://geography.wr.usgs.gov/science/dasymetric/data/ToolDescription.docx

Land Cover Data Issues

Low Resolution In non urban areas, there may not be a differentiation in land

class between a residence and the surroundings Resolution is typically able to differentiate roads from

surroundings in rural areas Assumption is population typically lives near roads

Developed Areas that are uninhabited can show as high density development Use Feature Classes to reclassify raster areas to eliminate

developed areas that are uninhabited Highways Airport

Block level data often finite enough that industrial areas are separated from residential areas and show no population

Military Grid Reference System

MGRS could provide an alternative aggregation level to the Census Block level Each unit is identical in size

Allows better comparisons between units in different parts of the state

Population and demographic data is not calculated at MGRS level Assign proportionally based on area Assign using Dasymetric mapping based on area

Grid Advantages For Population Mapping

Grid will enable a like to like comparison of areas across the state rural or urban Population is compared in an equal area Better and easier to view visuals every polygon is

equal area A group of small highly populated blocks (Downtown

areas) will now be as visible as suburban areas.

Kentucky State Hazard Mitigation Plan Risk Assessment

Hazard Vulnerability Score = Exposure Score X Risk Score

Risk Score = Probability of an event X actual consequences (loss) and the % area of each unit that is probable to be affected by an event. The % area is calculated for hazards that have a

defined and predictable spatial extent. For example; Flooding (DFIRM), Karst (KGS), Land Subsidence (KGS), and Landslide (KGS)

Kentucky State Hazard Mitigation Plan Exposure Score

Exposure Score= Population Rank + Property Rank + Essential Facilities Rank + Utility Rank + Transportation Rank + Government-Owned Facilities Rank + Hazardous Materials Rank

Included raw counts and provided a rank (0-3) for each one and then each was added together and ranked again

Next Steps and Issues

Build state wide risk assessment using dasymetric modeling and an equal area grid

Need Better Land Use Data LIDAR

With Buildings Building Footprint data

Better understanding of where population isBetter comparison of different areas

Takes a Census count of population and creates an estimate