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Ghana's coastline has been facing erosion and sedimentation phenomena for several decades, resulting in a serious threat to life and property considering that major urban settlements are located on the coast. In this region, there has been a lack of emphasis on comprehensive, large-scale investigations into coastal changes: prior research has predominantly centered on site-specific assessments. These studies have revealed alarming erosion rates, with reports indicating that nearly ten meters are lost annually. The use of high-resolution remotely sensed data can be a consistent support in regions where physical or economic obstacles interfere with collecting in situ information. In particular, the use of continuous all-weather SAR data may facilitate the evaluation of erosion and sedimentation phenomena in coastal areas. In this paper, we apply SAR data over a time period between 2017 and 2021. Sentinel-1 data are pre-processed using the Google Earth Engine platform, and a dedicated algorithm is then applied to identify and quantify erosion and sedimentation processes. Optical images are used as a reference for detecting the location of two areas where consistent sedimentation and erosion phenomena occurred in the considered four years. The results demonstrate that SAR backscattering variations over time offer a reliable method for monitoring coastal changes. This approach enables the identification of the type of phenomena occurring - sedimentation or erosion -, and allows for the quantification of their intensity and dimensions over time. The method can be worldwide applied once the appropriate thresholds are evaluated and help in predictive studies and environmental planning. [ABSTRACT FROM AUTHOR]

Abstract: European Remote Sensing satellites ERS-1 and ERS-2 synthetic aperture radar (SAR) data are used to analyze terrain deformation in the area of Wieliczka, Poland using interferometric techniques. Terrain deformations in Wieliczka are due to (i) salt mining, (ii) catastrophic suffusion caused by water inflows to the mine and (iii) landslides in the southern part of the region. To discriminate between different deformation regimes differential SAR Interferometry (D-InSAR) and persistent scatterers interferometry (PSI) are used. A comparison with published information based on leveling data is performed. It can be concluded that rapid subsidence caused by catastrophic water inflow cannot be identified with InSAR techniques. However, both D-InSAR and PSI retrieve information about slow subsidence due to mine convergence. These data match with subsidence maps constructed from leveling data. A limited amount of coherent scatterers were identified on landslides. Some scatterers can be related to buildings with clear damage caused by landslide movement. [Copyright &y& Elsevier]

Environmental effects and climate change are lately representing an increasing strain on coastal areas, whose topography strongly depends on these conditions. However, the processes by which weather and environmental phenomena influence the highly variable beach morphology are still unknown. Continuous monitoring of the beach environment is necessary to implement protection strategies. This paper presents the results of an innovative study performed on a coastal area using satellite remote sensing data with the aim of understanding how environmental phenomena affect beaches. Two years of synthetic aperture radar (SAR) Sentinel-1 images are used over a test area in Noordwijk, the Netherlands. At the same time as the SAR acquisitions, information on tidal and weather conditions are collected and integrated from nearby meteorological stations. Dedicated codes are implemented in order to understand the relationship between the SAR amplitude and the considered phenomena: wind, precipitation, and tidal conditions. Surface roughness is taken into account. The results indicate a strong correlation between the amplitude and the wind. No particular correlation or trend could be noticed in the relationship with precipitation. The analysis of the amplitude also shows a decreasing trend moving from the dry area of the beach towards the sea and the correlation coefficient between the amplitude and the tide level gets negative with the increase of the water content. [ABSTRACT FROM AUTHOR]

This work presents an automatic procedure to quantify dune dynamics on isolated barchan dunes exploiting Synthetic Aperture RADAR satellite data. We use C-band datasets, allowing the multi-temporal analysis of dune dynamics in two study areas, one located between the Western Sahara and Mauritania and the second one located in the South Rayan dune field in Egypt. Our method uses an adaptive parametric thresholding algorithm and common geospatial operations. A quantitative dune dynamics analysis is also performed. We have measured dune migration rates of 2–6 m/year in the NNW-SSE direction and 11–20 m/year NNE-SSW for the South Rayan and West-Sahara dune fields, respectively. To validate our results, we have manually tracked several dunes per study area using Google Earth imagery. Results from both automatic and manual approaches are consistent. Finally, we discuss the advantages and limitations of the approach presented. [ABSTRACT FROM AUTHOR]

During the last decades, Greater Cairo, Egypt, is increasing in population and in built-up extension. Some of the new buildings are informal, constructed in absence of government planning processes, and threaten the Heritage Cultural Site of the Giza Pyramids. In addition, the fertile land of the Nile floodplain is being urbanized despite the government's building prohibition since the 1990s. Therefore, constant monitoring of construction activity is crucial in the rapidly changing environment of this area. Here, we present a data fusion approach that overcomes the limitations of single medium resolution sensor approaches, and also identifies areas in transition from desert to urban. We use multi-temporal multi-sensor supervised land use classification and include a new land use class for detecting undefined disturbances. Synthetic aperture radar (SAR) data is combined with multi-spectral data for creating the land use land cover (LULC) maps using artificial neural networks (ANN). Specifically, ERS SAR data is combined with Landsat 5TM for 1998 and Envisat ASAR IMS with Landsat 7 ETM+ for 2004 and 2010. With this data fusion approach, it is measured an increase of 73% of Greater Cairo built-up extent from 1998 to 2010. Finally, we show the relationship between the aforementioned disturbances and the new built-up areas, detecting 26% of the total new built-up areas constructed from 1998 to 2010 where undefined disturbances were identified in previous land use maps. [ABSTRACT FROM AUTHOR]

To correctly interpret the estimated displacements in InSAR point clouds, especially in the built environment, these need to be linked to real-world structures. This requires the accurate and precise 3D positioning of each point. Artificial ground control points (GCPs), such as corner reflectors, serve this purpose, but since they require efforts and resources, there is a need for criteria to assess their usefulness. Here we evaluate the value and necessity of using GCPs for different scenarios, concerning the required efforts, and compare this to alternatives such as digital surface models (DSM) and advanced (geo) physical corrections. We consider single-epoch as well as multi-epoch GCP deployment, reflect on the number of GCPs required in relation to the number of SAR data acquisitions, and compare this with digital surface models of different quality levels. Analyzing the geolocation performance using TerraSAR-X and Sentinel-1 data, we evaluate the pros and cons of various deployment options and show that the multi-epoch deployment of a GCP yields optimal geolocalization results in terms of precision, accuracy, and reliability. [ABSTRACT FROM AUTHOR]