fusion of lidar and orthofusion of lidar and ortho...
TRANSCRIPT
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??