Fusion of LiDAR and OrthoFusion of LiDAR and Ortho--ImageryImageryTo Determine Impervious SurfacesTo Determine Impervious SurfacesTo Determine Impervious SurfacesTo Determine Impervious Surfaces

Joe Cantz, CP,Project Manager

Woolpert, Inc.

Presentation AgendaPresentation Agendagg• Case Study - City of Columbus Service Area• History• History

• Traditional Techniques• Semi-Automated Feature Extraction• Why a Semi Automated Process?• Why a Semi-Automated Process?

• Process• LiDAR and Ortho-Imagery (color and color infrared)

I i S f D li ti• Impervious Surface Delineation• Pilot Project

• Eastland MallR lt• Results

• Lessons Learned• Project Status• Beyond Impervious Surface Delineation (Other Uses)

City of ColumbusCity of ColumbusService AreaService AreaService AreaService Area

S i A 600• Service Area: ~600 Square Miles in Size

• Covers the entire land area of Franklin County, plus portions of Delaware, Fairfield, , ,Licking and Union Counties

City of ColumbusCity of ColumbusTraditional TechniquesTraditional Techniques--Current ProcessCurrent ProcessTraditional TechniquesTraditional Techniques Current ProcessCurrent Process

Current process for impervious areas:p p1- Proposed jobs are submitted in AutoCad format2- Items that pertain to impervious areas such as parking lots,

sidewalks and buildings are extracted from the AutoCad drawingsidewalks and buildings are extracted from the AutoCad drawing.3- Items are traced by hand to make an impervious polygon4- Polygon areas are calculated utilizing a proprietary tool5 C l l t d i i ll t d i t F P d5- Calculated impervious areas are manually entered into FoxPro and

Microsoft Access.6- The City does not receive as-built plans therefore billing for the

i i b ti h th t bill f th t limpervious areas become active when the water bill for that parcel becomes active or when a field check performed.

City of ColumbusCity of ColumbusTraditional TechniquesTraditional Techniques--Current ProcessCurrent ProcessTraditional TechniquesTraditional Techniques Current ProcessCurrent Process

Traditional approach to the delineation of impervious surfaces:

Utilize traditional photogrammetric techniques(3D)Time consumingC b hibi i Si f ?Can be cost prohibitive-Size of area?Higher accuracy than heads-up digitizing from orthos

Radial displacement above ground featuresRadial displacement above ground featuresHuman error

Utilize ortho-photography for heads-up digitizing (2D)Time consumingTime consumingLess cost prohibitive than traditional photogrammetric techniquesLess accuracy than photogrammetric techniquesy p g q

Radial displacementHuman error

City of ColumbusCity of ColumbusExisting Impervious DataExisting Impervious DataExisting Impervious DataExisting Impervious Data

Comprised of photogrammetrically derivedphotogrammetrically derived line-work

Updated using heads upUpdated using heads-up digitizing on ortho-photography

Files provided in AutoCADFiles provided in AutoCAD Format

City of ColumbusCity of ColumbusSolution: SemiSolution: Semi--Automated Feature ExtractionAutomated Feature ExtractionSolution: SemiSolution: Semi Automated Feature ExtractionAutomated Feature Extraction

City of ColumbusCity of ColumbusWhy SemiWhy Semi--Automated Process ?Automated Process ?

Provides a higher accuracy

Why SemiWhy Semi Automated Process ?Automated Process ?

Delineates and identifies smaller areas more accurately

Large reduction in potential human errorOff i d f i hOffers a more consistent and fair approach

Provides a more cost effective approachTraditional heads-up digitizing = substantially higher

costcostProvides opportunity to perform delineation on a

yearly basisProvides a shorter completion timeframeProvides a shorter completion timeframe

Traditional heads-up digitizing = much longer timeframe

Provides opportunity to perform delineation on a pp y pyearly basis

City of ColumbusCity of ColumbusImplementationImplementation

How is the automated impervious surface delineation implemented?

ImplementationImplementation

delineation implemented?• Utilize digital orthophotography dataset

• Color 1”=100’ scale RGB & CIR orthos with 0.5-foot pixelresolution

• Utilize Existing OSIP LiDAR dataset• 2-meter point density over the entire service area

El ti d l i t it & tt i• Elevation model, intensity, & patterningUtilize existing parcel dataset

• Use existing commercial parcel datasets in the service areaUtilize existing impervious surface areas as quality assurance• Utilize existing impervious surface areas as quality assurance

• Utilize ESRI software to incorporate datasets• Using all datasets above provides the impervious delineation• Impervious surfaces are compatible with the City’s existing• Impervious surfaces are compatible with the City s existing

software

City of ColumbusCity of ColumbusProcessProcess

Process – Semi-Automated Feature Extraction

ProcessProcess

• Remote Sensing Techniques and Software• Utilize 1”=100’ Scale Ortho-Imagery

• Color Ortho-Imagery (0.5-foot pixel l ti )resolution)

• Color Infra-red Ortho-Imagery (0.5-foot pixel resolution)

C l O th A l i C l I f d O th A l iColor Ortho Analysis Color Infra-red Ortho Analysis

City of ColumbusCity of ColumbusProcessProcess

Process – Semi-Automated Feature Extraction

Elevation

• Remote Sensing Techniques and Software• Utilize LiDAR – OSIP 2-meter Data

• Elevation Data • Intensity Data

LiDAR Point Cloud

ll f h d l fLiDAR allows for the delineation of impervious surfaces obscured by foliage (tree canopy), areas of shadow (around buildings) and buildings/structures (elevation and intensity)

LiDAR Intensity(elevation and intensity).

City of ColumbusCity of ColumbusAnalysisAnalysis

Impervious Surface Analysis

AnalysisAnalysis

1) Combine Ortho and LiDAR Data

2) Perform S t tiSegmentation

3) Develop Rule sets4) Perform Analysis5) Adjust Rule sets if5) Adjust Rule sets if

needed

City of ColumbusCity of ColumbusPilotPilot

Pilot Project

PilotPilot

Pilot Project

Eastland MallBilli A-Billing Areas

-Process

Results

City of ColumbusCity of ColumbusBilling AreasBilling AreasBilling AreasBilling Areas

EM Columbus LLC

Largest Property Owner

Existing ImperviousSurface1 607 934 square feet1,607,934 square feet

City of ColumbusCity of ColumbusBilling AreasBilling AreasBilling AreasBilling Areas

Sears

2nd Largest Property Owner

Existing ImperviousSurface740 172 square feet740,172 square feet

City of ColumbusCity of ColumbusBilling AreasBilling AreasBilling AreasBilling Areas

Lazarus Inc.

3rd Largest Property Owner

Existing ImperviousSurface688 290 square feet688,290 square feet

City of ColumbusCity of ColumbusProcessProcessProcessProcess

Pilot Process

-0.5 foot Color RGB (0-255 values)( )

-0.5 foot CIR(0-255 values)

-2.0 Meter average point spacing LiDAR

N I t it d-No Intensity used

City of ColumbusCity of ColumbusSegmentation ProcessSegmentation ProcessSegmentation ProcessSegmentation Process

S t tiSegmentation

Polygons developed b d l fbased on values of pixels

Often outside of whatOften outside of what the human eye can discern

City of ColumbusCity of ColumbusResulting DataResulting DataResulting DataResulting Data

EM Columbus LLC

Original AutoCAD filesExisting Impervious Surface

N I iNew Impervious Surface Delineation

City of ColumbusCity of ColumbusResulting DataResulting DataResulting DataResulting Data

EM Columbus LLC

Original AutoCAD filesExisting Impervious Surface

N I iNew Impervious Surface Delineation

City of ColumbusCity of ColumbusResulting DataResulting DataResulting DataResulting Data

EM Columbus LLC

Original AutoCAD filesExisting Impervious Surface

N I iNew Impervious Surface Delineation

City of ColumbusCity of ColumbusResulting DataResulting DataResulting DataResulting Data

CIR Imagery will impervious surfaceoverlaid

City of ColumbusCity of ColumbusResulting DataResulting DataResulting DataResulting Data

Color Imagery will impervious surface overlaid

City of ColumbusCity of ColumbusResulting DataResulting DataResulting DataResulting Data

Resulting Impervious Surface

City of ColumbusCity of ColumbusResulting DataResulting DataResulting DataResulting Data

Original AutoCAD Data

New Automated Impervious SurfaceSurface

City of ColumbusCity of ColumbusNumbersNumbers

Differences Between Current Data and using LiDAR/Ortho Data

NumbersNumbers

Owner# of ERUs

Stormwater Charges

Clean River Charges Total Charges

Sears 370 $1,335.70 $865.80 $2,201.50376 $1,353.60 $879.84 $2,233.44

Difference 6 $17.90 $14.04 $31.94Lazarus

Inc 344 $1,283.12 $749.92 $2,033.04351 $1,305.72 $765.11 $2,070.83

Difference 7 $22.60 $15.19 $37.79EMColumbusLLC 804 $2,894.40 $1,881.36 $4,775.76

805 $2,898.00 $1,883.70 $4,781.70Difference 1 $3.60 $2.34 $5.94

City of ColumbusCity of ColumbusNumbersNumbers

Estimated Dollars Comparing LiDAR Data with Current DataEstimated Dollars Comparing LiDAR Data with Current Data

OwnerTotal

Charges CommentAnnual Income

Sears and 30 Day BillingSears and Roebuck $31.94

30 Day Billing Cycle $383.28

Lazarus Inc $37.7931 Day Billing

Cycle $453.48Lazarus Inc $37.79 Cycle $453.48EM Columbus LLC $5.94

30 Day Billing Cycle $71.28

Total EstimatedTotal Estimated Annual Income $908.04

City of ColumbusCity of ColumbusLessons LearnedLessons Learned

Lessons Learned• Shadows are an issue

City of ColumbusCity of ColumbusLessons LearnedLessons Learned

Lessons Learned• Vegetation (trees) covering impervious areas are an issue

City of ColumbusCity of ColumbusLessons LearnedLessons Learned

Lessons Learned• Some surface areas identified as impervious, may not be

City of ColumbusCity of ColumbusImproving the ProcessImproving the Process

1-meter vs. 2-meter LiDAR

2-meter Post Spacing1-meter Post Spacing VS.

City of ColumbusCity of ColumbusProject StatusProject Status

PROJECT STATUS

• All input data (orthos/LiDAR) completed• All input data (orthos/LiDAR) completed• Project area segmentation completed• Project area impervious surface completed• Extraction of impervious surfaces for commercial parcelsExtraction of impervious surfaces for commercial parcels

completed• QC of commercial parcel impervious surfaces is completed• Final Deliverable made to Columbus

City of ColumbusCity of ColumbusFinal DataFinal Data

Sample Final DatasetsImpervious Surfaces Shown in Blue/Gray

City of ColumbusCity of ColumbusFinal DataFinal Data

Sample Final DatasetsImpervious Surface Shown in Blue/Gray

Building Classification Shown in Light BlueBuilding Classification Shown in Light Blue

City of ColumbusCity of ColumbusSample DataSample Data

Sample Final DatasetsImpervious Surfaces Shown in Blue/Gray

City of ColumbusCity of ColumbusBenefitsBenefits

Benefits:• Release technicians to perform other tasks• Release technicians to perform other tasks• Opportunity to maintain a more up-to-date and accurate

databaseOpportunity to offer a more fair assessment of impervious• Opportunity to offer a more fair assessment of impervious surfaces

• Greatly reduced time frame of maintaining impervious surface databasesurface database

• Greatly reduced costs associated with maintaining an impervious surface database (using traditional methods)

( f• Reduce human error (using computer software and geo-spatial datasets)

• Track growth through change detection of impervious f ( h i l i h i ?)surfaces (where is population growth occurring?)

City of ColumbusCity of ColumbusBeyond Impervious SurfaceBeyond Impervious Surface

Beyond Impervious Surface Delineation (Other Uses)Vegetation Analysis

City of ColumbusCity of ColumbusRoad ExtractionRoad Extraction--DOTDOT

Questions??Questions??