Monitoring asphalt pavement damages using remote sensing techniques

Christodoulos Mettas; Kyriacos Themistocleous; Kyriacos Neocleous; Andreas Christofe; Kypros Pilakoutas; Diofantos Hadjimitsis

doi:10.1117/12.2195702

19 June 2015 Monitoring asphalt pavement damages using remote sensing techniques

Christodoulos Mettas, Kyriacos Themistocleous, Kyriacos Neocleous, Andreas Christofe, Kypros Pilakoutas, Diofantos Hadjimitsis

Author Affiliations +

Proceedings Volume 9535, Third International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2015); 95350S (2015) https://doi.org/10.1117/12.2195702
Event: Third International Conference on Remote Sensing and Geoinformation of the Environment, 2015, Paphos, Cyprus

Abstract

One of the main issues in the maintenance plans of road agencies or governmental organizations is the early detection of damaged asphalt pavements. The development of a smart and non-destructive systematic technique for monitoring damaged asphalt pavements is considered a main priority to fill this gap. During the 1970’s, remote sensing was used to map road surface distress, while during the last decade, remote sensing became more advanced, thereby assisting in the evolution of the identification and mapping of roads. Various techniques were used in order to explore condition, age, weaknesses and imperfections of asphalted pavements. These methods were fairly successful in the classification of asphalted surfaces and in the detection of some of their characteristics. This paper explores the state of the art of using remote sensing techniques for monitoring damaged pavements and some typical spectral profiles of various asphalt pavements in Cyprus area acquired using the SVC1024 field spectroradiometer.

Citation Download Citation

Christodoulos Mettas, Kyriacos Themistocleous, Kyriacos Neocleous, Andreas Christofe, Kypros Pilakoutas, and Diofantos Hadjimitsis "Monitoring asphalt pavement damages using remote sensing techniques", Proc. SPIE 9535, Third International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2015), 95350S (19 June 2015); https://doi.org/10.1117/12.2195702

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