Integrated use of GIS and remote sensing for monitoring landslides in transportation pavements: the case study of Paphos area in Cyprus

This study considers the impact of landslides on transportation pavements in rural road network of Cyprus using remote sensing and geographical information system (GIS) techniques. Landslides are considered to be one of the most extreme natural hazards worldwide, causing both human losses and severe damages to the transportation network. Risk assessment for monitoring a road network is based on the combination of the probability of landslides occurrence and the extent and severity of the resultant consequences should the disasters (landslides) occur. Factors that can trigger landslide episodes include proximity to active faults, geological formations, fracture zones, degree and high curvature of slopes, water conditions, etc. In this study, the reliability and vulnerability of a rural network are examined. Initially, landslide locations were identified from the interpretation of satellite images. Different geomorphological factors such as aspect, slope, distance from the watershed, lithology, distance from lineaments, topographic curvature, land use and vegetation regime derived from satellite images were selected and incorporated in GIS environment in order to develop a decision support and continuous landslide monitoring system of the area. These parameters were then used in the final landslide hazard assessment model based on the analytic hierarchy process method. The results indicated good correlation between classified high-hazard areas and field-confirmed slope failures. The CA Markov model was also used to predict the landslide hazard zonation map for 2020 and the possible future hazards for transportation pavements. The proposed methodology can be used for areas with similar physiographic conditions all over the Eastern Mediterranean region.     

Risk provision using field spectroscopy to identify spectral regions for the detection of defects in flexible pavements

Natural and physical hazards accelerate the deterioration of asphalted surfaces. Climatic factors are unavoidable and can affect the properties of asphalt mixtures, making them weaker and less durable. Thus, continuous monitoring of bituminous surfaces is something that can reduce the risks of public health. Remote sensing techniques have become an effective, noninvasive method for early detection of damaged asphalt pavements. This paper outlines a range of different remote sensing methodologies that can be used to monitor asphalt road pavements. This is complemented by the use of field spectroscopy for the examination of asphalt pavements of varying age and conditions. The results of the study found spectral differences regarding asphalt defects, such as physical cracking, patched cracking and polishing. These spectral changes were examined through “in-band” simulation analysis of the Landsat 7 ETM+ sensor, using appropriate relative spectral response filters, concluding that the ratio band 5/band 1 can be used to distinguish asphalt pavements of different date of construction and condition.