1. Zhaoying Wei
GEOG 8350
Comparison of Land use
detection in Niagara Falls using
LIDAR and orthoimagery

2. Outlines
 Goal
 Area of Interest
 Data
 Method and Result
 Conclusion and
Future Work

3. Land use
detection
orthophoto
LIDAR
Goal

4. AOI

5. Data
Data
• point cloud Lidar data
• orthoimagery
Tools
•LAStools
•Lidar Analyst
•ArcGIS 10.0
• ArcGIS 10.0
• Erdas
• ENVI

6. Method (LIDAR)
 Extract Bare earth
• strip the existing classes from the LAS file and
set the coordinate system and projection (noclass.las)
• classify the ground points (ground.las)
• create the only ground points (groundonly.las)
• generate DEM of groundonly .las
• extract bare earth DEM from groundonly DEM

7. Method (LIDAR)
From
From raw LAS
 Extract Bare earth

8. Method (LIDAR)
Extract buildings footprints
• compute the height above the ground
• Classify trees and Buidlings (treeNbuilding.las)
• generate new bare earth for building and trees
extraction

9. Extract building footprints
• point cloud building extraction
Method (LIDAR)

10. Extract building footprints
• edit building
Method (LIDAR)
Before After
Remove building
Add to building
Merge building

11. Before After
Extract building footprints
Method (LIDAR)
Create new building and close holes
Final
footprints

12. Extract tree
• point cloud tree extraction
• visually edit forests and trees
Method (LIDAR)

13. Method (Orthophoto)
Supervised classification
• Create the signature file and AOI for each class
• Combine the signature file of all classes

14. Method (Orthophoto)
Reclassify
• manually digitize AOI
• assign new class value to water

15. Conclusion
 LIDAR:
• vector results consistent with real
terrains
• limited classes
Orthoimage
• numerous classes
• low quality and accuracy, water

16. Future work
Measure accuracy of the classification result
 improve the quality of signature
 better water detection
 object-based classification
Fusion of LIDAR and aerial image