This document discusses using geospatial technologies like GIS and remote sensing to evaluate road quality by detecting pavement defects. It presents two case studies: one using unsupervised methods and image processing to detect potholes with 81% accuracy, and another using 3D line laser scanning from vehicles up to 100kph to automatically measure rut depth on roads with 5mm accuracy. These innovative techniques can effectively identify road deterioration like potholes and rutting to help transportation agencies better plan maintenance and rehabilitation.

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(A Reliable, Cost-effective Performance Measurement
Technology)
Introduction:-
Condition of pavement detection is one of the
important tasks for the proper planning of repairs and
rehabilitation of the asphalt-surfaced pavements.
It is necessary in those situations where
unconditioned pavement compromise safety and
pavement ride-ability.
ANALYSIS ON QUALITY OF ROADS
USING GEOINFORMATICS

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In this,we present a new and rapidly increasing
technology GIS & RS , which does not require
much work in field and produce good results.
This method deploys image processing and
spectral clustering for identification and estimation
of potholes .
And also rutting and fatigue cracks on pavement
can be identified with 3D scanning.

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What are problems in asphalt-pavements ?
 Potholes.
 Rutting.
 Fatigue cracking.
 Raveling.
 Bleeding.
 Longitudinal cracking.
 Edge cracking.

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Why require timely maintenance ?

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Problems In Conventional Methods
 Manually gather all data for analysis.
 Time consuming.
 Human errors.
 More effort is required.
 Labour expensive.
 Less accuracy of data.
 Additional effort is required for analysis.

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Innovative Methods
 In the present ,swiftly emergent technology is
GIS & RS.
 In this we have the methods like
3D line laser image technology
and
Unsupervised method.
 By using these two methods we can identify the
defects in pavements.

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Potholes
Methods to detect potholes
Supervised methods
3D reconstruction
Vibration
Vision analysis

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Mobile imaging vehicle

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Case Study(Pot holes)
This study done by EMIR BUZA, SAMIR OMANOVIC,
ALVIN HUSEINOVIC from
University of sarajevu in Bosnia.

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Unsupervised Method
 The goal of unsupervised method is to
automatically segregate pixels of a remote
sensing image into groups of similar spectral
character.
 Classification is done using "clustering" where
classes of pixels are created based on their shared
spectral signatures

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Flowchart

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Results of pothole estimation

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Conclusions
 In this case study ,the proposed method was
tested on 50 different pothole images and the
detection accuracy has been calculated manually.
 On a given set of data, our method identified all
potholes and the surface estimation was 81%
accurate.
 Thus , it is suitable for rough estimation of
potholes, and it is cost effective because it uses
in-expensive equipment.

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3D line laser image technology
 A 3D scanner is a device that analyses a real-world object or
environment to collect data on its shape and possibly its
appearance. The collected data can then be used to construct
digital three-dimensional models.

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Principle
The laser line is directed to the surface at an
oblique angle. It incised on the surfaces and
creates a visible line. In areas where the object is
lower, the beam is slightly shifted. By means of a
camera this displacement of the bright laser lines
can be determined in the image.
Triangulation

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Working
In driver direction it measures up to
5mm accuracy with vehicle runs with
100kmph

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Evaluation of rut depth

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Case Study (rutting)
 This study done by Mr.Feng Li from Georgia
Institute of Technology in Atlanta.

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In field

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Limitations
Missing Points
The object surface gets out of the measurement
range.
Occlusion.
Dim laser point.
Unseemly Points
Effect of Loose Rocks.
Effect of Selected Road Surface Characteristics.
Reflective Surface Test.

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Other Errors

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Conclusions
 Pavement rutting is one of the major asphalt pavement
surface distresses affecting.
 Conventional rutting measurement method is still used
by many state Departments of Transportation
however, it is time-consuming, labour-intensive, and
dangerous.
 With the advance of sensing technology, emerging 3D
line laser imaging technology is capable of collecting
high-resolution 3D range data at highway speed (e.g.,
100 km/h).

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Using this advanced sensing technology to
1) process 3D range data.
2) automatically extract 1D rut depth measurements
and 2D/3D rutting characteristics.
3) assess the accuracy and repeatability of rutting
measurements
4) explore more detailed information to support
current and future pavement management decisions,
e.g., network-level condition

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References
 Emir Buza, Samir Omanovic, Alvin Huseinovic
given there study on “Pothole Detection with
Image Processing and Spectral Clustering”
 Feng li given his study on “A methodology for
characterizing pavement rutting condition using
emerging 3d line laser imaging technology”
 Yao, M., Yao, X., Yu, W., and Xu, B. (2009). “A
Real-time 3D Scanning System for Pavement
Rutting and Pothole Detections.” Proceedings of
SPIE: Video metrics, Range Imaging, and
Applications X, 74470B-74479.

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