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21/4/2015 Dr. Ahmad Yousef
The Use of GIS for 3D Urban ModelsReconstruction Based on Aerial Lidar Data
Dr. Ahmad Yousef
21/4/2015 Dr. Ahmad Yousef
• Overview
• Objectives & Goals
• Digital Terrain Model Extraction
• 3D Building Model Reconstruction
• Conclusion & Final Thoughts
AGENDA
21/4/2015 Dr. Ahmad Yousef
Pollution, CairoVisualization, Dubai
Pollution, Moscow
Flood, Pakistan
Visualization, Los Angeles
City Planning, Stuttgart
Flood, Mexico
• GIS has traditionally been 2D technology.
• New product and technology make us reconsider the role of 3D.
• It is widely recognized that 3D models are necessary.
OverviewWhy 3D GIS …
21/4/2015 Dr. Ahmad Yousef
Year : 2050
66%
Year : 2014
54%
Urban Population
World
Source: UN DESA’s Population Division
of Global Population
o The overall growth of theworld’s population could addanother 2.5 billion people tourban populations by 2050
o 90 percent of the increaseconcentrated in Asia andAfrica
OverviewWhy urban area …
21/4/2015 Dr. Ahmad Yousef
OverviewWhy lidar data …
Waldkirch, Germany
21/4/2015 Dr. Ahmad Yousef
OverviewWorkshop Objectives & Goals
21/4/2015 Dr. Ahmad Yousef
OverviewWorkshop Objectives & Goals
21/4/2015 Dr. Ahmad Yousef
OverviewWorkshop Objectives & Goals
1. Introduce a fast and simple integrated Digital Terrain Model (DTM) extraction framework in a GIS environment.
21/4/2015 Dr. Ahmad Yousef
OverviewWorkshop Objectives & Goals
1. Introduce a fast and simple integrated Digital Terrain Model (DTM) extraction framework in a GIS environment.
2. Introduce a developed GIS approach for reconstructing of the 3D building models from lidar point clouds.
21/4/2015 Dr. Ahmad Yousef
Digital Terrain Model Extraction
How to classify lidar data into terrain and off-terrain points?
21/4/2015 Dr. Ahmad Yousef
• Filtering means classification of points into terrain and off-terrain.
• Bare earth is assumed to be continuous surface.
• Filtering In/Out data:
– Point list
– Grid
– Triangulated Irregular Network - TIN
DTM ExtractionFiltering lidar data
21/4/2015 Dr. Ahmad Yousef
DTM ExtractionEsri Terrain Dataset
Surface geometry at different resolution (TINs)
– TIN is acronym for triangulated irregular network.
Level of Detail-Pyramid
LoD x
Pyramid Type:I. WINDOWSIZEII. ZTOLERANCE
parameter:I. ZMINII. ZMAXIII. ZMEANIV. ZMINMAX
21/4/2015 Dr. Ahmad Yousef
DTM ExtractionEsri Terrain Dataset
21/4/2015 Dr. Ahmad Yousef
DTM ExtractionEsri Terrain Dataset
21/4/2015 Dr. Ahmad Yousef
DTM ExtractionEsri Terrain Dataset
21/4/2015 Dr. Ahmad Yousef
DTM ExtractionEsri Terrain Dataset
21/4/2015 Dr. Ahmad Yousef
DTM ExtractionMinimum Block Classification - MBC
Window Block
Bare Earth Surface
Input Points Dataset [Geodatabase], Input Window Size, Cell Size (≈ Points Average Distance)
Output Ground Points, DTM
Window Block
21/4/2015 Dr. Ahmad Yousef
DTM ExtractionMinimum Block Classification - MBC
Input Points Dataset [Geodatabase], Input Window Size, Cell Size (≈ Points Average Distance)
Output Ground Points, DTM
1
2
3
5
Window Size Z-threshold
32 3.2
16 1.6
8 0.8
4 0.4
2 0.2
4
21/4/2015 Dr. Ahmad Yousef
DTM ExtractionMinimum Block Classification - MBC
Input Points Dataset [Geodatabase], Input Window Size, Cell Size (≈ Points Average Distance)
Output Ground Points, DTM
Convert Terrain to TIN
Smoothing
Umbrella Filter
21/4/2015 Dr. Ahmad Yousef
DTM ExtractionDigital Surface Model
21/4/2015 Dr. Ahmad Yousef
DTM ExtractionDigital Terrain Model
21/4/2015 Dr. Ahmad Yousef
Digital Surface Model Shaded Relief
DTM ExtractionForest Dataset …
Digital Terrain Model Shaded Relief
21/4/2015 Dr. Ahmad Yousef
45m x 35m
DTM ExtractionUrban Dataset …
5 750 000 Points
21/4/2015 Dr. Ahmad Yousef
DTM ExtractionUrban Dataset …
21/4/2015 Dr. Ahmad Yousef
3D Building Models Reconstruction
How to fulfill the gap between lidar data and building models ?How to minimize the number of points that represent a building ?
21/4/2015 Dr. Ahmad Yousef
3D Building ModelBuildings Shapes …
Redlands, USA. Source : Google maps
21/4/2015 Dr. Ahmad Yousef
3D Building ModelNo Comments …
Venezuela. Barrio Petare, Caracas.Source: A sustainable approach to problems in urban squatter developments
21/4/2015 Dr. Ahmad Yousef
3D Building ModelLevel of Details LoD
• Building model is the representation used for describing the form of building.
• The complexity of a 3D building model is known as the level of details (LoDs).
Source: : Open Geospatial Consortium CityGML Implementation Specification 1.0,20.8 2008
Level of Details
Data Processing
LoD 1 : Flat Roofs
LoD 2 : Roof Type
LoD 3 : Real Roof Shape
LoD 4 : Interior
21/4/2015 Dr. Ahmad Yousef
Model Structure Based – Model Derive
3D Building ModelModeling Approaches
• Model Database.
• The final roof shape is always topologically correct.
• Complex roof shapes cannot be reconstructed.
3D Building Models Database
Flat Desk Gable Hipped Mansard PyramidGambrel
21/4/2015 Dr. Ahmad Yousef
3D Building ModelModeling Approaches
Source: International Summer School “Digital Recording and 3D Modeling”.
3D Building Models Database
Flat Desk Gable Hipped Mansard PyramidGambrel
21/4/2015 Dr. Ahmad Yousef
Data Structure Based – Data Derive
3D Building ModelModeling Approaches
• Roof described by planar faces.
• Partitioning the given ground plan and find the most appropriate plane segment to each partition.
Source: International Summer School “Digital Recording and 3D Modeling”.
21/4/2015 Dr. Ahmad Yousef
Input for Data Derive Model
3D Building ModelModeling Approaches
I. Points based
– Points may belong to several planes.
II. Raster based
– Information content is decreased due to interpolation.
III. TIN based
– To avoid loss of information due to interpolation, all operations are performed on the Delaunay triangulation of the original height points.
– Requires more analysis.
21/4/2015 Dr. Ahmad Yousef
3D Building ModelBuilding Model Elements
Planar Patches
Wall
Footprint
Planar Face
TIN Triangles
Lidar
Roof Boundary
21/4/2015 Dr. Ahmad Yousef
5 Processing Steps :-
3D Building ModelFramework …
1. Generate Triangle Irregular Network - TIN
2. Extract Roof Planar Patches
i. Normal Vector Estimation
ii. Segmentation & Region Growing
3. Detection of Planar Roof Faces
i. Least Square Plane Fitting
ii. Merging Planar Patches
4. Intersection of Roof Planes
5. 3D Model Reconstruction
21/4/2015 Dr. Ahmad Yousef
21/4/2015 Dr. Ahmad Yousef
3D Building Model1 - Triangle Irregular Network
21/4/2015 Dr. Ahmad Yousef
3D Building Model1 - Triangle Irregular Network
21/4/2015 Dr. Ahmad Yousef
3D Building Model2 - Extract Roof Planar Patches
A.X + B.Y + C.Z + D = 0N=(A,B,C)
21/4/2015 Dr. Ahmad Yousef
3D Building Model2 - Extract Roof Planar Patches
Normal Vector Estimation
1 Ring Neighborhood 2 Rings Neighborhood
21/4/2015 Dr. Ahmad Yousef
3D Building Model2 - Extract Roof Planar Patches
Normal Vector Estimation
21/4/2015 Dr. Ahmad Yousef
3D Building Model2 - Extract Roof Planar Patches
Normal Vector Estimation
21/4/2015 Dr. Ahmad Yousef
1 Ring Neighborhood
3D Building Model2 - Extract Roof Planar Patches
Normal Vector Estimation
21/4/2015 Dr. Ahmad Yousef
3D Building Model2 - Extract Roof Planar Patches
Normal Vector Estimation
2 Rings Neighborhood
21/4/2015 Dr. Ahmad Yousef
2 Rings Neighborhood
3D Building Model2 - Extract Roof Planar Patches
Normal Vector Estimation
21/4/2015 Dr. Ahmad Yousef
3D Building Model2 - Extract Roof Planar Patches
Segmentation & Region Growing
Apply region growing to find roof patches
21/4/2015 Dr. Ahmad Yousef
3D Building Model2 - Extract Roof Planar Patches
Segmentation & Region Growing
21/4/2015 Dr. Ahmad Yousef
3D Building Model2 - Extract Roof Planar Patches
Segmentation & Region Growing
21/4/2015 Dr. Ahmad Yousef
3D Building Model2 - Extract Roof Planar Patches
Segmentation & Region Growing
21/4/2015 Dr. Ahmad Yousef
3D Building Model3 - Detection of Planar Roof Faces
21/4/2015 Dr. Ahmad Yousef
3D Building Model3 - Detection of Planar Roof Faces
Vertical Triangles
All triangles with slope greater than 60 are considered as vertical patches
21/4/2015 Dr. Ahmad Yousef
3D Building Model3 - Detection of Planar Roof Faces
Least Square Plane Fitting
A * X + B * Y + C * Z = D
The Plane Normal is given by : N = (A,B,C)
21/4/2015 Dr. Ahmad Yousef
3D Building Model3 - Detection of Planar Roof Faces
Intersection of adjacent patches
A * X + B * Y + C * Z = D
21/4/2015 Dr. Ahmad Yousef
3D Building Model3 - Detection of Planar Roof Faces
Merging Planar Patches
21/4/2015 Dr. Ahmad Yousef
3D Building Model4 - Intersection of Roof Planes
Patch 1 2 3 4 5 6 7
1 YES YES YES YES
2 YES YES YES
3 YES YES
4 YES YES
5 YES YES
6 YES YES YES
7 YES
Plane Adjacency Matrix
21/4/2015 Dr. Ahmad Yousef
3D Building Model4 - Intersection of Roof Planes
21/4/2015 Dr. Ahmad Yousef
3D Building Model4 - Intersection of Roof Planes
21/4/2015 Dr. Ahmad Yousef
3D Building Model5 - 3D Model Reconstruction
21/4/2015 Dr. Ahmad Yousef
3D Building Model5 - 3D Model Reconstruction
21/4/2015 Dr. Ahmad Yousef
3D Building Model5 - 3D Model Reconstruction
21/4/2015 Dr. Ahmad Yousef
3D Building Model5 - 3D Model Reconstruction
21/4/2015 Dr. Ahmad Yousef
3D Building Model5 - 3D Model Reconstruction
21/4/2015 Dr. Ahmad Yousef
3D Building Model5 - 3D Model Reconstruction
21/4/2015 Dr. Ahmad Yousef
3D Building ModelExample 1
21/4/2015 Dr. Ahmad Yousef
3D Building ModelExample 1
21/4/2015 Dr. Ahmad Yousef
3D Building ModelExample 1
21/4/2015 Dr. Ahmad Yousef
3D Building ModelExample 2
Minimum area threshold = 5 m2
Minimum area threshold = 3 m2
21/4/2015 Dr. Ahmad Yousef
3D Building ModelExample 3
21/4/2015 Dr. Ahmad Yousef
3D Building ModelTest Area
21/4/2015 Dr. Ahmad Yousef
3D Building ModelError Sources
21/4/2015 Dr. Ahmad Yousef
SummaryConclusion & Final Thoughts...
• Minimum Block Classification (MBC) Model was successfully implemented in GIS environment.
• Advantages of MBC Model includes :
– Fixed number of processing loops.
– Capable of capturing and removing the major terrain features.
– Although building size and shape present a challenge for many other filtering
algorithms, they do not significantly hinder the MBC algorithm when using the
proper window size and threshold.
21/4/2015 Dr. Ahmad Yousef
SummaryConclusion & Final Thoughts...
o Minimum Block Classification (MBC) Model was successfully implementedin GIS environment.
o 3D building reconstruction models from lidar data was developed fromconstructing a roof surface geometry.
o 3D building reconstruction models result affected by
Minimum area threshold
Points distribution
Shape complexity
o The processing time varies and is dependent on the shape of the building,start from 5 seconds for simple buildings to 30 seconds for complexbuildings.
21/4/2015 Dr. Ahmad Yousef
Thank YouShare What You Can To Benefit The OthersAhmad Yousef ([email protected])