scholarly journals Testing Sentinel-1 SAR Interferometry Data for Airport Runway Monitoring: A Geostatistical Analysis

Sensors ◽  
2021 ◽  
Vol 21 (17) ◽  
pp. 5769 ◽  
Author(s):  
Valerio Gagliardi ◽  
Luca Bianchini Ciampoli ◽  
Sebastiano Trevisani ◽  
Fabrizio D’Amico ◽  
Amir M. Alani ◽  
...  
Keyword(s):  
Spatial Data ◽  
Leonardo Da Vinci ◽  
Geostatistical Analysis ◽  
Sar Interferometry ◽  
Spatial Data Analysis ◽  
Maintenance Strategies ◽  
Spatial Continuity ◽  
Persistent Scatterers ◽  
Sar Data

Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) techniques are gaining momentum in the assessment and health monitoring of infrastructure assets. Amongst others, the Persistent Scatterers Interferometry (PSI) technique has proven to be viable for the long-term evaluation of ground scatterers. However, its effectiveness as a routine tool for certain critical application areas, such as the assessment of millimetre-scale differential displacements in airport runways, is still debated. This research aims to demonstrate the viability of using medium-resolution Copernicus ESA Sentinel-1A (C-Band) SAR products and their contribution to improve current maintenance strategies in case of localised foundation settlements in airport runways. To this purpose, “Runway n.3” of the “Leonardo Da Vinci International Airport” in Fiumicino, Rome, Italy was investigated as an explanatory case study, in view of historical geotechnical settlements affecting the runway area. In this context, a geostatistical study is developed for the exploratory spatial data analysis and the interpolation of the Sentinel-1A SAR data. The geostatistical analysis provided ample information on the spatial continuity of the Sentinel 1 data in comparison with the high-resolution COSMO-SkyMed data and the ground-based topographic levelling data. Furthermore, a comparison between the PSI outcomes from the Sentinel-1A SAR data—interpolated through Ordinary Kriging—and the ground-truth topographic levelling data demonstrated the high accuracy of the Sentinel 1 data. This is proven by the high values of the correlation coefficient (r = 0.94), the multiple R-squared coefficient (R2 = 0.88) and the Slope value (0.96). The results of this study clearly support the effectiveness of using Sentinel-1A SAR data as a continuous and long-term routine monitoring tool for millimetre-scale displacements in airport runways, paving the way for the development of more efficient and sustainable maintenance strategies for inclusion in next generation Airport Pavement Management Systems (APMSs).

scholarly journals Long-Term Remote Monitoring of Ground Deformation Using Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR): Applications and Insights into Geotechnical Engineering Practices

2020 ◽  
Vol 10 (21) ◽  
pp. 7447
Author(s):  
Ryan Ramirez ◽  
Seung-Rae Lee ◽  
Tae-Hyuk Kwon
Keyword(s):  
Synthetic Aperture Radar ◽  
Ground Deformation ◽  
Geotechnical Engineering ◽  
Sar Interferometry ◽  
Synthetic Aperture ◽  
Successful Implementation ◽  
Persistent Scatterers ◽  
Sar Data ◽  
Aperture Radar

Development of synthetic aperture radar (SAR) technology and the dedicated suite of processing tools have aided the evolution of remote sensing techniques for various Earth Observation (EO) applications. Interferometric SAR (InSAR) is a relatively new geodetic technique which provides high-speed and reliable geographic, geologic, and hazards information allowing the prognosis of future environmental and urban planning. In this study, we explored the applicability of two differential interferometry techniques, conventional and advanced differential InSAR (A-DInSAR), for topographic mapping and long-term geotechnical monitoring by exploiting satellite data, particularly Sentinel-1 SAR data, which is publicly shared. We specifically used the open-source tools of SeNtinel Application Platform (SNAP) and Stanford Method for Persistent Scatterers (StaMPS) for interferometric data processing to implement A-DInSAR. This study presents various applications, which include generation of a digital elevation model (DEM), mapping of seismically induced displacement and associated damages, and detection and long-term monitoring of tunneling-induced ground deformation and rainfall-induced landslide. Geometric and temporal decorrelations posed challenges and limitations in the successful implementation of Sentinel-1 SAR interferometry specifically in vegetated areas. The presented results proved the validity and reliability of the exploited SAR data and InSAR techniques for addressing geotechnical engineering related problems.

scholarly journals Long-Term Spatial Associations and Regional Convergence of Rural Literacy Rate in India

2021 ◽  
Vol 04 (03) ◽  
Author(s):  
Hazem Mohamed ◽  
Keyword(s):  
Spatial Data ◽  
Careful Analysis ◽  
Spatial Data Analysis ◽  
Literacy Rate ◽  
Rural Districts ◽  
Spatial Associations ◽  
Nonparametric Approach ◽  
And Gender ◽  
Convergence Model

Although there are claims that inequality in India has stagnated or even increased in the post-liberalization period, careful analysis of data shows that these views are mostly unsubstantiate. The main aspects of social inequality can be structured, to a large extent, along urban-rural and gender lines. In this paper, we explore a nonparametric approach to highlight the form of the long-term spatial associations of the georeferenced units. Relying on the method of Markov chains, we develop a stationary form for the Moran scatter plot, one of the techniques of the exploratory spatial data analysis. As an illustration, we highlight the forms of spatial autocorrelation and heterogeneity of long-term literacy rates in rural districts in India observed by the two censuses of 1991 and 2001. We use the same data to estimate a spatial β-convergence model. It appears that the growth of literacy rate is higher in rural districts with the lowest literacy and proceeds by spatial diffusion. Beyond his correspondence with the β-convergence model, the proposed nonparametric approach has the advantage of identifying the location of spatial associations

scholarly journals Displacement Monitoring in Airport Runways by Persistent Scatterers SAR Interferometry

2020 ◽  
Vol 12 (21) ◽  
pp. 3564 ◽  
Author(s):  
Luca Bianchini Ciampoli ◽  
Valerio Gagliardi ◽  
Chiara Ferrante ◽  
Alessandro Calvi ◽  
Fabrizio D’Amico ◽  
...  
Keyword(s):  
Time Series ◽  
Leonardo Da Vinci ◽  
Sar Interferometry ◽  
Subgrade Soils ◽  
Ground Deformations ◽  
Persistent Scatterers ◽  
Deformation Velocity ◽  
Open Issue ◽  
Remote Sensing Techniques ◽  
Surrounding Areas

Deformations monitoring in airport runways and the surrounding areas is crucial, especially in cases of low-bearing capacity subgrades, such as the clayey subgrade soils. An effective monitoring of the infrastructure asset allows to secure the highest necessary standards in terms of the operational and safety requirements. Amongst the emerging remote sensing techniques for transport infrastructures monitoring, the Persistent Scatterers Interferometry (PSI) technique has proven effective for the evaluation of the ground deformations. However, its use for certain demanding applications, such as the assessment of millimetric differential deformations in airport runways, is still considered as an open issue for future developments. In this study, a time-series analysis of COSMO–SkyMed satellite images acquired from January 2015 to April 2019 is carried out by employing the PSI technique. The aim is to retrieve the mean deformation velocity and time series of the surface deformations occurring in airport runways. The technique is applied to Runway 3 at the “Leonardo da Vinci” International Airport in Rome, Italy. The proposed PSI technique is then validated by way of comparison with the deformation outcomes obtained on the runway by traditional topographic levelling over the same time span. The results of this study clearly demonstrate the efficiency and the accuracy of the applied PSI technique for the assessment of deformations in airport runways.

scholarly journals Long-term monitoring of a deep-seated, slow-moving landslide by mean of C-band and X-band advanced interferometric products: the Corvara in Badia case study (Dolomites, Italy)

2015 ◽  
Vol XL-7/W3 ◽  
pp. 827-829 ◽  
Author(s):  
M. Mulas ◽  
M. Petitta ◽  
A. Corsini ◽  
S. Schneiderbauer ◽  
F. V. Mair ◽  
...  
Keyword(s):  
Time Series ◽  
Test Case ◽  
Persistent Scatterers ◽  
X Band ◽  
Slow Moving ◽  
Sar Data ◽  
Slope Displacement ◽  
Term Monitoring

The availability of data from various Synthetic Aperture Radar (SAR) operating in X-Band and C-Band acquired in the last decades enables to monitor slopes affected by landslides. The ASI-founded project ‘LAWINA’ (2010 – 2012) aimed at the improvement of SAR – based monitoring techniques as well as at the integration of SAR data with data stemming from other sensors. Test case area of LAWINA has been a slow-moving landslide located up-stream of Corvara in Badia village in the Dolomites, Italy. Within the scope of the project different time-series obtained through 35 Envisat2, 40 Radarsat-1 and 46 Cosmo-SkyMed covering this test area have been processed in order to explore the potentials to analyse historical and near real time landslide dynamics. The SAR data are characterized by various geometric and temporal resolutions having been acquired by 3 sensors operating at different bands in different periods between 2003 and 2011. TeleRilevamento Europa (TRE) exploited these data in order to retrive displacement timeseries applying its proprietary SqueeSAR algorithm. After re-projecting Envisat-2 and Radarsat datasets according to the CSK Line Of Sight a comparison of displacements recorded by each sensor has been possible. For this purpose, we have selected areas characterized by the presence of Persistent Scatterers or Diffused Scatterers from at least two datasets. This multi-sensor approach allowed determining the slope displacement tracking during 8 years. Even though the different time series are not formally integrated each other, the result is accurate enough to allow the evaluation of the landslide’s behaviour and trend over several years.

scholarly journals The support of multidimensional approaches in integrate monitoring for SEA: a case of study

2013 ◽  
Vol 4 (1) ◽  
pp. 51-61 ◽  
Author(s):  
C. M. Torre ◽  
M. Selicato
Keyword(s):  
Spatial Data ◽  
Carrying Capacity ◽  
Coastal Waters ◽  
Spatial Data Analysis ◽  
Human Pressure ◽  
Short Term ◽  
Urban Settlements ◽  
The Subject ◽  
Definition Of

Abstract. During the centuries, the seaside has represented a crucial pole for future human development and civilization. The use of the sea for transport and trade and the overwhelming availability of food derived from coastal waters have encouraged and strengthened the growth of urban settlements. In the same time, the human pressure menaces to destroy coastal habitats and consequently their carrying capacity that allows for many essential functions. Low-impact activities are often replaced, on the surface, by new intensive ones that are attractive in the short term, but that in the long term undermine by reducing the resilience of the coast. It is clear that, in a perspective of sustainable development, economically efficient and socially equitable use of coastal areas need to be supported inside strategies to correct these weaknesses. The definition of such strategies and their implementation in the Strategic Environmental Assessment (SEA) is an essential tool for supporting decisions and of monitoring. The issues of monitoring, more in particular, have been the subject of study and modelling by the use of Dynamic Spatial Data Analysis (DSDA), in the case of the SEA of the Coastal Plan of the Italian Apulia Region, as an information instrument for regulating the anthropogenic changes; a possibility to implement the analysis of environmental sensitivity and propensity to Coastal erosion has been explored, in order to control the level of human pressure on land. The monitoring system should provide an automatic "alert" when the dimension and the velocity of the change of land use overpass some threshold of environmental pressure.

scholarly journals Long-Term Deflection Monitoring for Bridges Using X and C-Band Time-Series SAR Interferometry

2019 ◽  
Vol 11 (11) ◽  
pp. 1258 ◽  
Author(s):  
Jungkyo Jung ◽  
Duk-jin Kim ◽  
Suresh Krishnan Palanisamy Vadivel ◽  
Sang-Ho Yun
Keyword(s):  
Time Series ◽  
Orientation Angle ◽  
Sar Interferometry ◽  
Interferometric Synthetic Aperture Radar ◽  
Vertical Deflection ◽  
Vertical Displacements ◽  
Multi Temporal ◽  
Sar Data ◽  
Thermal Dilation

This study aims to monitor the deformation of bridges, namely in the form of long-term deflection and thermal dilation, using multi-temporal interferometric synthetic aperture radar (InSAR) observations. To precisely estimate the vertical and longitudinal displacements, we used the InSAR time-series technique with multi-track stacks of Sentinel-1 SAR dataset and a single-track stack of COSMO-SkyMed SAR data over two extradosed bridge cases; Kimdaejung and Muyoung bridges between 2013 and 2017. The vertical and longitudinal displacements are estimated using multi-track Sentinel-1 SAR data and orientation angle of bridges, and we converted the displacements into thermal dilation and long-term vertical deflection. From COSMO-SkyMed data, we calculated the horizontal thermal dilation and long-term vertical deflection assuming that they dominantly contribute to the horizontal and vertical displacements, respectively. This assumption appeared reasonable based on the comparison with calculations from Sentinel-1 data. The deflection patterns exhibit downward movements at the mid-spans between towers. The results reveal that both bridges have been suffering long-term deflection over the observation period. Thus, this study verifies the potential to monitor the long-term deflection and implies that the bridges need to be monitored periodically.

scholarly journals Cropland Abandonment in Slovakia: Analysis and Comparison of Different Data Sources

Land ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 334
Author(s):  
Juraj Lieskovský ◽  
Dana Lieskovská
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Spatial Data ◽  
Data Sources ◽  
Communist Regime ◽  
Corine Land Cover ◽  
Cropland Area ◽  
Cropland Abandonment ◽  
Multi Temporal

This study compares different nationwide multi-temporal spatial data sources and analyzes the cropland area, cropland abandonment rates and transformation of cropland to other land cover/land use categories in Slovakia. Four multi-temporal land cover/land use data sources were used: The Historic Land Dynamics Assessment (HILDA), the Carpathian Historical Land Use Dataset (CHLUD), CORINE Land Cover (CLC) data and Landsat images classification. We hypothesized that because of the different spatial, temporal and thematic resolution of the datasets, there would be differences in the resulting cropland abandonment rates. We validated the datasets, compared the differences, interpreted the results and combined the information from the different datasets to form an overall picture of long-term cropland abandonment in Slovakia. The cropland area increased until the Second World War, but then decreased after transition to the communist regime and sharply declined following the 1989 transition to an open market economy. A total of 49% of cropland area has been transformed to grassland, 34% to forest and 15% to urban areas. The Historical Carpathian dataset is the more reliable long-term dataset, and it records 19.65 km2/year average cropland abandonment for 1836–1937, 154.44 km2/year for 1938–1955 and 140.21 km2/year for 1956–2012. In comparison, the Landsat, as a recent data source, records 142.02 km2/year abandonment for 1985–2000 and 89.42 km2/year for 2000–2010. These rates, however, would be higher if the dataset contained urbanisation data and more precise information on afforestation. The CORINE Land Cover reflects changes larger than 5 ha, and therefore the reported cropland abandonment rates are lower.

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