Infrastructure is operational under normal circumstances and is designed to cope with common natural disruptions such as rainfall and snow. Natural hazards can lead to severe problems at the areas where such phenomena occur, but also at neighboring regions as they can make parts of a road network virtually impassable. Landslides are one of the most devastating natural hazards worldwide, triggered by various factors that can be monitored via ground-based and/or satellite-based techniques. Cyprus is in an area of high susceptibility to such phenomena. Currently, extensive field campaigns including geotechnical drilling investigations and geophysical excavations are conducted to monitor land movements, and, at the same time, determine the geological suitability of areas. Active satellite remote sensors, namely Synthetic Aperture Radar (SAR), have been widely used for detecting and monitoring landslides and other ground deformation phenomena using Earth Observation based techniques. This paper aims to demonstrate how the use of Copernicus open-access and freely distributed datasets along with the exploitation of the open-source processing software SNAP (Sentinel’s Application Platform), provided by the European Space Agency, can be used for landslide detection, as in the case study near Pissouri, where a landslide was triggered by heavy rainfall on 15 February 2019, which caused a major disturbance to everyday commuters since the motorway connecting the cities of Limassol and Paphos remained closed for more than a month. The Coherent Change Detection (CCD) methodology was applied successfully by detecting the phenomenon under study accurately, using two indicators (the coherence difference and the normalized coherence difference). Receiver Operating Characteristic (ROC) analysis was carried out to measure their performance with the coherence difference having an overall accuracy of 93% and the normalized coherence difference having an overall accuracy of 94.8% for detecting the landslide and non-landslide areas. The probability of landslide detection was 63.2% in the case of the coherence difference and increased to 73.7% for the normalized coherence difference, whereas the probability of false alarm for both indicators was approximately 1%.

Active satellite remote sensors have emerged in the last years in the field of archaeology, providing new tools for monitoring extensive cultural heritage landscapes and areas. These active sensors, namely synthetic aperture radar (SAR) satellites, provide systematic datasets for mapping land movements triggered from earthquakes, landslides, and so on. Copernicus, the European program for monitoring the environment, provides continuous radar datasets through the Sentinel-1 mission with an almost worldwide coverage. This paper aims to demonstrate how the use of open-access and freely distributed datasets such as those under the Copernicus umbrella, along with the exploitation of open-source radar processing software, namely the sentinel applications platform (SNAP) and SNAPHU tools, provided respectively by the European Space Agency (ESA) and the University of Stanford, can be used to extract an SAR interferogram in the wider area of Paphos, located in the western part of Cyprus. The city includes various heritage sites and monuments, some of them already included in the UNESCO World Heritage list. The interferogram was prepared to study the effects of an earthquake to the buildings and sites of the area. The earthquake of a 5.6 magnitude on the Richter scale was triggered on 15 April 2015 and was strongly felt throughout the whole island. The interferogram results were based on Differential Synthetic Aperture Radar Interferometry (D-InSAR) methodology, finding a maximum uplift of 74 mm and a maximum subsidence of 31 mm. The overall process and methodology are presented in this paper.

This study aims to investigate how alternations of the land surface temperature (LST) affects the normalized difference vegetation index (NDVI) in Paphos forest, Cyprus, using Landsat-5 and Landsat-8 imagery for the time periods 1993–2000 and 2013–2018, respectively. A total of 262 Landsat images were processed to compute the mean monthly NDVI and LST values and create a time series. Using the Cook’s distance, the effect of missing values in the analysis of the time series were examined. Results from the cross-correlation and cross-variograms, decomposition model, and the BFAST algorithm were compared to produce reliable conclusions on forest changes and satellite, meteorological, and environmental data were combined to interpret the changes that occurred inside the forest. The decomposition analysis showed a decrease of 2.7% in the LST for the period 1993–2000 and an increase of 4.6% in the LST during the period 2013–2018. The NDVI trend is negatively correlated to the LST trend for both time periods. An increase in the LST trend was identified in November 1998 as well as in the NDVI trend in October 1994 and May 2014 that was caused by favorable climatic conditions. An increase in the NDVI trend from May 2014 to December 2015 may be related to reduced pityocampa attacks. An abrupt decrease was detected in December 2015 that was probably caused by the locust invasion that occurred in the island earlier that year. A positive correlation appears for LST and NDVI variables for time lags 4, 5, 6, 7, and 8 months. Overall, it was shown that LST and NDVI analysis is very promising for identifying potential forest decline.

Cyprus, being located on the Mediterranean fault zone, exhibits a unique geodynamic regime since its tectonic evolution is driven by the interaction of the Eurasian and African plate. Besides its seismological interest, many active landslides and slope instabilities in areas of steep topography occur in Cyprus, having substantial impact on the built environment, by posing an imminent threat for entire settlements and critical infrastructure. Moreover, extreme meteorological events occur rarely, like severe rainfall and thunderstorms, that combined with the geological properties in some areas and the seismically stressed ground, can lead to landslides, causing severe damages to critical infrastructure. In the present study, the DInSAR methodology is applied for the detection of two individual landslide events that were triggered by heavy rainfall in Limassol and Paphos Districts in February 2019. Six co-event interferometric Synthetic Aperture Radar (SAR) pairs were used to produce displacement maps in vertical and east-west directions to study the resulting slope deformations. The above are carried out using Sentinel-1 imagery that are freely provided under the Copernicus umbrella. The limitations that arise from the speed and complexity of the deformations under study and the adverse residing meteorological conditions that caused these phenomena are investigated, as found in literature. Indeed, the sparse vegetation at the slopes affected by the landslides, the residing meteorological conditions, the heavy rainfall that triggered the two landslides, and the temporal phase aliasing effect due to the speed of the ground deformation were found to be the main limitations for the application of DInSAR methodology, resulting in the underestimation of the ground deformation that occurred.

PNT stands for Positioning, Navigation, and Timing. Space-based PNT refers to the capabilities enabled by GNSS, and enhanced by Ground and Space-based Augmentation Systems (GBAS and SBAS), which provide position, velocity, and timing information to an unlimited number of users around the world, allowing every user to operate in the same reference system and timing standard. Such information has become increasingly critical to the security, safety, prosperity, and overall qualityof-life of many citizens. As a result, space-based PNT is now widely recognized as an essential element of the global information infrastructure. This paper discusses the importance of the availability and continuity of PNT information, whose application, scope and significance have exploded in the past 10–15 years. A paradigm shift in the navigation solution has been observed in recent years. It has been manifested by an evolution from traditional single sensor-based solutions, to multiple sensor-based solutions and ultimately to collaborative navigation and layered sensing, using non-traditional sensors and techniques – so called signals of opportunity. A joint working group under the auspices of the International Federation of Surveyors (FIG) and the International Association of Geodesy (IAG), entitled ‘Ubiquitous Positioning Systems’ investigated the use of Collaborative Positioning (CP) through several field trials over the past four years. In this paper, the concept of CP is discussed in detail and selected results of these experiments are presented. It is demonstrated here, that CP is a viable solution if a ‘network’ or ‘neighbourhood’ of users is to be positioned / navigated together, as it increases the accuracy, integrity, availability, and continuity of the PNT information for all users

Nowadays, assessing geo-hazards in cultural heritage sites in most cases takes place after the hazard has occurred. Monitoring structural and ground deformation resulting from geo-hazards facilitates the early recognition of potential risks and encourages effective conservation planning. This paper presents an integrated ground deformation monitoring approach based on the combined use of satellite SAR data, campaign-based GPS/GNSS observations, and aerial images from UAVs within the Choirokoitia UNESCO World Heritage Site in Cyprus. The Neolithic settlement of Choirokoitia is one of the most important prehistoric sites in the Eastern Mediterranean. The site is located on a steep hill, which makes it vulnerable to rock falls and landslides. As part of the PROTHEGO project, a series of field measurements were collected at the Choirokoitia site and compared against satellite SAR data to verify kinematic behavior of the broader area and to assist in monitoring potential geo-hazards over time. The results obtained indicate displacement rates of the order of 0.03 m/year. These results indicate that ground deformation should be monitored in the area surrounding the Choirokoitia using long-term, low-impact monitoring systems such as SAR images and UAV-based and geodetic techniques. The combination of such monitoring technologies can be compared to monitor and assess potential geo-hazards on archeological sites with increased accuracy.