Condition Evaluation and Classification Using Geospatial Tools

Pradeep Kumar

ISBN 10: 620292358X / ISBN 13: 9786202923583

Published by LAP LAMBERT Academic Publishing Okt 2020, 2020

About this Item

Neuware -Maintenance of pavements is an important aspect for the road authorities all over the world. The first step towards maintenance is pavement evaluation. Pavement could be evaluated through different types of distress experienced, such as cracking, disintegration and surface deformation. Pavement surface distresses, such as cracks and pothole are visible imperfections on the surface of the pavements. At present, there are various methods for conducting distress surveys, recording and analysing distress survey data. Traditionally, pavement condition data are gathered by human inspectors who walk or drive along the road to assess the distresses and subsequently produce reports, but it is costly and time-consuming, and endangers the safety of the personnel involved. Also, the large differences exist between the actual condition and evaluation results because of the subjectivity of the evaluation process. This work proposed methodologies for automatic assessment of pavement surface distresses using geospatial tools and soft computing techniques.Books on Demand GmbH, Überseering 33, 22297 Hamburg 112 pp. Englisch.

Seller Inventory # 9786202923583

Bibliographic Details

• Title: Condition Evaluation and Classification Using Geospatial Tools
• Publisher: LAP LAMBERT Academic Publishing Okt 2020
• Publication Date: 2020
• Language: English
• ISBN 10: 620292358X
• ISBN 13: 9786202923583
• Binding: Taschenbuch
• Condition: Neu

About this title

Synopsis

Maintenance of pavements is an important aspect for the road authorities all over the world. The first step towards maintenance is pavement evaluation. Pavement could be evaluated through different types of distress experienced, such as cracking, disintegration and surface deformation. Pavement surface distresses, such as cracks and pothole are visible imperfections on the surface of the pavements. At present, there are various methods for conducting distress surveys, recording and analysing distress survey data. Traditionally, pavement condition data are gathered by human inspectors who walk or drive along the road to assess the distresses and subsequently produce reports, but it is costly and time-consuming, and endangers the safety of the personnel involved. Also, the large differences exist between the actual condition and evaluation results because of the subjectivity of the evaluation process. This work proposed methodologies for automatic assessment of pavement surface distresses using geospatial tools and soft computing techniques.