Search

Three-Dimensional Ground Penetrating Radar (3D GPR) detects subsurface targets non-destructively, rapidly, and continuously. The complex environment around urban roads affects the positioning accuracy of 3D GPR. The positioning accuracy directly affects the data quality, as inaccurate positioning can lead to distortion and misalignment of 3D GPR data. This paper proposed a multi-level robust positioning method to improve the positioning accuracy of 3D GPR in dense urban areas in order to obtain more accurate underground data. In environments with good GNSS signals, fast and high-precision positioning can be achieved based on GNSS data using differential GNSS technology; in scenes with weak GNSS signals, high-precision positioning of subsurface data can be achieved by using GNSS and IMU as well as using GNSS/INS tightly coupled solution technology; in scenes with no GNSS signals, SLAM technology is used for positioning based on INS data and 3D point cloud data. In summary, this method ensures a positioning accuracy of 3D GPR better than 10 cm and high-quality 3D images of underground urban roads in any environment. This provides data support for urban road underground structure surveys and has broad application prospects in underground disease detection and prevention. [ABSTRACT FROM AUTHOR]

Mini–unmanned aerial vehicles (mini-UAVs) are emerging as a promising platform for through-wall radar to sense the enclosed space in cities, especially high-rise buildings, due to their excellent maneuverability. However, due to unavoidable environmental interference such as airflow, mini-UAVs are prone to trajectory deviation thus degrading their sensing accuracy. Most of the existing approaches model the impact of trajectory deviation into a polynomial phase error on the received signal, which cannot fit the space-variant motion error well. Moreover, the large trajectory deviations of UAVs introduce the unavoidable envelope error. This article proposes an autofocusing algorithm based on the back projection (BP) image, which directly estimates the trajectory deviations between the actual and measured track. Thus, the problem of the 2D space variability of the motion error can be circumvented. The proposed method mainly consists of two steps. First, we estimate the trajectory deviation in the line-of-sight (LOS) direction by exploring the underlying linear property of the wall embedded in the BP imaging result. Then, the estimated trajectory deviation in the LOS direction is compensated for to obtain an updated BP image, followed by a Particle Swarm Optimization (PSO) approach to estimate the trajectory deviation along the track through focusing targets behind the wall. Simulations and practical experiments show that the proposed algorithm can accurately estimate the serious trajectory deviations larger than the range resolution, improving the sensing robustness of UAV-borne through-wall radar greatly. [ABSTRACT FROM AUTHOR]

The country of Libya, situated on the Mediterranean fault zone, has a distinctive geodynamic regime due to the interplay between the Eurasian and African plates, which governs its tectonic evolution. In addition to its seismological significance, Libya is characterized by numerous subsidence and slope instabilities in regions with steep terrain. These geological phenomena have significant consequences for the built environment, as they pose an immediate danger to entire towns and essential infrastructure. Furthermore, infrequent weather phenomena, such as intense precipitation and thunderstorms, when coupled with the geological characteristics of some regions and the presence of seismically active terrain, have the potential to trigger landslide and land subsidence, resulting in significant harm to vital infrastructure. The current study utilizes the DInSAR technology to identify distinct subsidence occurrences that were induced by intense precipitation in coastal regions of Libya, specifically in Derna. These areas experienced significant flooding resulting in collapses during September 2023. A total of six pairs of co-event Interferometric Synthetic Aperture Radar (SAR) were utilized to generate displacement maps in the vertical, north-east, and north-west directions for the purpose of analysing the deformations. The aforementioned activities are conducted via Sentinel-1A images, which is freely accessible through the Copernicus program. Additionally, flood-prone zones were defined using Sentinel-1 GRD imagery. The Interferometric processing revealed multiple areas of subsidence. Subsidence rates of up to −14 cm were found in Derna city's urban cores after flood. The findings suggest that subsidence may have an effect on the flood-proneness of the region of Derna City as Ground subsidence also occurred in the period immediately before the earthquake, at a rate of −14 cm. [ABSTRACT FROM AUTHOR]

This study focuses on analyzing and monitoring urban subsidence, particularly in the city of Palermo, Italy. Land subsidence, induced by natural and human factors, poses threats to infrastructure and urban safety. Remote sensing (RS), specifically synthetic-aperture radar interferometry (In-SAR), is employed due to its ability to detect ground displacements over large areas with great precision. The persistent scatterer InSAR (PS-InSAR) technique is utilized to identify stable targets and track millimeter-level surface deformations. This research spans from October 2014 to October 2021, using Sentinel-1 satellite data to capture ground deformation from various angles. The findings are integrated into an accessible web app (ArcGIS) for local authorities that could be used aiding in urban planning and enhancing safety measures. This study's results offer updated deformation maps, serving as an operational tool to support decision-making and community resilience, emphasizing risk awareness and responsible practices. This study highlights that the exponential expansion of urban areas, which does not take into account historical information, can gravely jeopardize both the integrity of urban infrastructure and the well-being of its inhabitants. In this context, remote sensing technologies emerge as an invaluable ally, used in monitoring and safeguarding the urban landscape. [ABSTRACT FROM AUTHOR]

Mining activities represent one of the main causes leading to subsidence in the natural and urban environment. Sustainable urban planning and detection of potential hazards in mining areas involve the use of adequate instruments such as the continuous monitoring of land subsidence. The complexity of urban environment demands the utilization of new methods for monitoring and quantifying the effects of the mining processes. In the last decades, considering the technological developments from the remote sensing domain, the Synthetic Aperture Radar Interferometry (InSAR) techniques offer the opportunity for early detection and continuous monitoring of subsidence in mining areas, including urban centers. Considering various parameters of mining subsidence monitoring, a review of several tens of studies realized in different mining sites, based on InSAR techniques, is presented. As mining subsidence in urban areas has a direct impact on the quality of life, the review is completed with demographic indicators assessment, followed by a study case on the dynamics of the population in an urban mining area from Romania, Ocnele Mari. [ABSTRACT FROM AUTHOR]

Downhill thunderstorms frequently occur in Beijing during the rainy seasons, leading to substantial precipitation. The accurate intensity prediction of these events remains a challenge, partly attributed to insufficient observational studies that unveil the thermodynamic and dynamic structures along the vertical direction. This study provides a comprehensive methodology for identifying both enhanced and dissipated downhill thunderstorms. In addition, a radar wind profiler (RWP) mesonet has been built in Beijing to characterize the pre-storm environment downstream to the thunderstorms at the mountain foot. This involves deriving vertical distributions of high-resolution horizontal divergence and vertical motion from the horizontal wind profiles measured by the RWP mesonet. A case of enhanced downhill thunderstorm on 28 September 2018 is carried out, which support the idea that the enhanced southerly flow and corresponding convergence detected by the RWP mesonet could favorably support the development of thunderstorms in the afternoon. The results also indicate that low-level convergence is an effective signal in accounting for convective maintenance. Statistical analysis based on radar reflectivity from April to September 2018–2021 have shown that a total of 63 thunderstorm events tend to be enhanced after moving into downhill and urban areas, accounting for about 66 % of the total number of downhill thunderstorm events. A critical region for intensified thunderstorms lies on the downslope side of the mountains west to Beijing. The evolution of the downhill storm is associated with the dynamic conditions over the plain compared to its initial morphology. The lifting induced by stronger westerly winds and vertical shear in the low and midlevel troposphere exerts a critical influence on the enhancement of convection. The findings underscore the significant role of RWP network in elucidating the evolution of downhill storm. [ABSTRACT FROM AUTHOR]

Observations of the vertical wind profile in Chongqing, a typical mountainous city in China, are important, but they are sparse and have low resolution. To obtain more wind profile data, this study matched the Aeolus track with ground-based wind observation sites in Chongqing in 2021. Based on the obtained results, verification and quality control studies were conducted on the wind observations of a wind profile radar (WPR) with radiosonde (RS) data, and a comparison of the Aeolus Mie-cloudy and Rayleigh-clear wind products (Aeolus winds measured in cloudy and aerosol-rich atmospheric conditions from Mie-channel-collected data and winds measured in clear-air conditions from Rayleigh-collected data) with WPR data was then performed. The conclusions can be summarized as follows: (1) a clear correlation between the wind observations of WPR and RS was found, with a correlation coefficient (R) of 0.71. Their root mean square deviation increased with height but decreased at heights between 3 and 4 km. (2) After quality control using Gaussian filtering (GF) and empirical orthogonal function construction (EOFc; G=87.23 %) of the WPR data, the R between the WPR and RS reached 0.83 and 0.95, respectively. The vertical distribution showed that GF could better retain the characteristics of WPR wind observations but with limited improvement in decreasing deviations, whereas EOFc performed better in decreasing deviations but considerably modified the original characteristics of the wind field, especially regarding intensive vertical wind shear in strong convective weather processes. (3) In terms of the differences between the Aeolus and WPR data, 56.0 % and 67.8 % deviations were observed within ±5 m s -1 for Rayleigh-clear and Mie-cloudy winds (Aeolus winds measured in cloudy and aerosol-rich atmospheric conditions from Mie-channel-collected data and winds measured in clear-air conditions from Rayleigh-collected data) vs WPR winds, respectively. Vertically, large mean differences of both Rayleigh-clean and Mie-cloudy winds versus WPR winds appeared below 1.5 km, which is attributed to the prevailing quiet and small winds within the boundary layer in Chongqing; in this case the movement of molecules and aerosols is mostly affected by irregular turbulence. Additionally, large mean differences at a height range between 4 and 8 km for Mie-cloudy versus WPR winds may be related to the high content of cloud liquid water in the middle troposphere of Chongqing. (4) The differences in both Rayleigh-clear and Mie-cloudy versus WPR winds had changed. Deviations of 58.9 % and 59.6 % were concentrated within ±5 m s -1 for Rayleigh-clear versus WPR winds with GF and EOFc quality control, respectively. In contrast, 69.1 % and 70.2 % of deviations appeared within ±5 m s -1 for Rayleigh-clear versus WPR and EOFc WPR winds, respectively. These results shed light on the comprehensive applications of multi-source wind profile data in mountainous cities or areas with sparse ground-based wind observations. [ABSTRACT FROM AUTHOR]

This paper presents the results of a study to determine the potential of radar imaging to detect classes of built-up areas defined in the Urban Atlas (UA) spatial database. The classes are distinguished by function and building density. In addition to the reflectance value itself, characteristics such as building density or spatial layout can improve the identification of these classes. In order to increase the classification possibilities and better exploit the potential of radar imagery, a grey-level co-occurrence matrix (GLCM) was generated to analyse the texture of built-up classes. Two types of synthetic-aperture radar (SAR) images from different sensors were used as test data: Sentinel-1 and ICEYE, which were selected for their different setup configurations and parameters. Classification was carried out using the Random Forests (RF) and Minimum Distance (MD) methods. The use of the MD classifier resulted in an overall accuracy of 64% and 51% for Sentinel-1 and ICEYE, respectively. In ICEYE, individual objects (e.g. buildings) are better recognised than classes defined by their function or density, as in UA classes. Sentinel-1 performed better than ICEYE, with its texture images better complementing the features of urban area classes. This remains a significant challenge due to the complexity of urban areas in defining and characterising urban area classes. Automatic acquisition of training fields directly from UA is problematic and it is therefore advisable to independently obtain reference data for built-up area categories. [ABSTRACT FROM AUTHOR]

Radar rainfall nowcasting has mostly been applied to relatively large (often rural) domains (e.g., river basins), although rainfall nowcasting in small urban areas is expected to be more challenging. Here, we selected 80 events with high rainfall intensities (at least one 1-km2 grid cell experiences precipitation >15 mm h−1 for 1-h events or 30 mm day−1 for 24-h events) in five urban areas (Maastricht, Eindhoven, The Hague, Amsterdam, and Groningen) in the Netherlands. We evaluated the performance of 9060 probabilistic nowcasts with 20 ensemble members by applying the short-term ensemble prediction system (STEPS) from Pysteps to every 10-min issue time for the selected events. We found that nowcast errors increased with decreasing (urban) areas especially when below 100 km2. In addition, at 30-min lead time, the underestimation of nowcasts was 38% larger and the discrimination ability was 11% lower for 1-h events than for 24-h events. A set of gridded correction factors for the Netherlands, CARROTS (Climatology-based Adjustments for Radar Rainfall in an Operational Setting) could adjust the bias in real-time QPE and nowcasts by 70%. Yet, nowcasts were still found to underestimate rainfall more than 50% above 40-min lead time relative to the reference, which indicates that this error originates from the nowcasting model itself. Also, CARROTS did not adjust the rainfall spatial distribution in urban areas much. In summary, radar-based nowcasting for urban areas (between 67 and 213 km2) in the Netherlands exhibits a short skillful lead time of about 20 min, which can only be used for last-minute warning and preparation. [ABSTRACT FROM AUTHOR]

Observations of vertical wind in Chongqing, a typical mountainous city in China, are important, but sparse and have low resolution. To obtain more wind profile data, this study matched the Aeolus track with ground-based wind observation sites in Chongqing in 2021. Based on the obtained results, verification and quality control studies were conducted on the wind observations of a wind profile radar (WPR) with radiosonde (RS) data, and a comparison of the Aeolus Mie-cloudy and Rayleigh-clear wind products with WPR data was then performed. The conclusions can be summarized as follows: (1) A clear correlation between the wind observations of WPR and RS was found, with a correlation coefficient (R) of 69.92%. Their root-mean-square deviation increased with height but decreased by 3 - 4 km. (2) After quality control of Gaussian filtering (GF) and empirical orthogonal function construction (EOFc, G = 87.23%) of the WPR data, the R between the WPR and RS reached 76.00% and 95.44%, respectively. The vertical distribution showed that GF could better retain the characteristics of WPR wind observations, but with limited improvement in decreasing deviations, whereas EOFc performed better in decreasing deviations, but considerably modified the original characteristics of the wind field, especially regarding intensive vertical wind shear in strong convective weather processes. (3) In terms of the differences between the Aeolus and WPR data, 56.0% and 67.8% deviations were observed between ± 5 m/s for Rayleigh-clear and Mie-cloudy winds vs. WPR winds, respectively. Vertically, the mean differences of both Rayleigh-clean and Mie-cloudy winds versus WPR winds appeared below 1.5 km, which is attributed to the prevailing quiet and small winds within the boundary layer in Chongqing, such that the movement of molecules and aerosols is mostly affected by irregular turbulence. Additionally, large mean differences of 4-8 km for Mie-cloudy versus WPR winds may be related to the high content of cloud liquid water in the middle troposphere, influenced by the topography of the Tibetan Plateau. (4) The differences in both Rayleigh-clear and Mie-cloudy versus WPR winds had changed. Deviations of 58.9% and 59.6% were concentrated between ±5m/s for Rayleigh-clear versus WPR winds with GF and EOFc quality control, respectively. In contrast, 69.1% and 70.2% of deviations appeared between ± 5 m/s for Rayleigh-clear versus WPR and EOFc WPR winds, respectively. These results shed light on the comprehensive applications of multi-source wind profile data in mountainous cities or areas with sparse ground-based wind observations. [ABSTRACT FROM AUTHOR]

An important geological risk to which many towns in Puglia are exposed is sinking cavities in urban areas. For urban centers, studying, mapping, providing geological and speleological descriptions, classifying, and cataloging the forms and types of cavities is essential because cavities are linked to past local anthropic and natural processes at different sites. These circumstances could lead to the enhancement of existing underground cavities in urban areas through conservation and continuous monitoring. Unfortunately, in many cases, these underground cavities have been used as landfills and subsequently abandoned. In late March 2007, one of these cavities collapsed inside Gallipoli's inhabited center, causing damage to the structures but fortunately not human lives. In the area surrounding the collapsed cavity, a series of geophysical investigations were undertaken using ground penetrating radar in an attempt to delimit the area of collapse and develop possible interventions for restoration. In the same area, these measures were repeated 16 years later in December 2022 due to another collapse. The comparison between data acquired in these two periods shows that there were no strong changes apart from an increased presence of subsoil moisture in 2022. [ABSTRACT FROM AUTHOR]

Extracting buildings in urban scenes from remote sensing images is crucial for the construction of digital cities, urban monitoring, urban planning, and autonomous driving. Traditional methods generally rely on shadow detection or stereo matching from multi-view high-resolution remote sensing images, which is cost-intensive. Recently, machine learning has provided solutions for the estimation of building heights from remote sensing images, but challenges remain due to the limited observation angles and image quality. The inherent lack of information in a single modality greatly limits the extraction precision. This article proposes an advanced method using multi-source remote sensing images for urban building height estimation, which is characterized by multi-level cross-fusion, the multi-task joint learning of footprint extraction and height estimation, and semantic information to refine the height estimation results. The complementary and effective features of synthetic aperture radar (SAR) and electro-optical (EO) images are transferred through multi-level cross-fusion. We use the semantic information of the footprint extraction branch to refine the height estimation results, enhancing the height results from coarse to fine. Finally, We evaluate our model on the SpaceNet 6 dataset and achieve 0.3849 and 0.7231 in the height estimation metric δ 1 and footprint extraction metric D i c e , respectively, which indicate effective improvements in the results compared to other methods. [ABSTRACT FROM AUTHOR]

Ground penetrating radar (GPR) survey can be used to image geological hazards such as cavities, faults, fissures and also for identifying buried utilities. Sinkholes formed in the Secunderabad-Patny stretch road, Hyderabad, India were speculated to have been caused due to leaking from the sewer pipe. GPR survey using 200 MHz antenna was used in order to study the sinkholes formed in the collapsed area. GPR profiles were taken both parallel to and perpendicular to the road section to get a complete 3D visualization. Subsurface images acquired the marked position of the manholes, cavities, loose soil, different utilities, and sewer pipeline in the area. The results showed that there was no leaking in the sewer pipeline, instead, a water pipeline was damaged due to poor maintenance. Thus, GPR can be efficiently used to delineate the subsurface infrastructure and has further played an important role in identifying, delineating the zone of sinkhole in a busy street in Secunderabad. [ABSTRACT FROM AUTHOR]

Ground deformation is one of the crucial issues threatening many cities in both societal and economic aspects. Interferometric synthetic aperture radar (InSAR) has been widely used for deformation monitoring. Recently, there has been an increasing availability of massive archives of SAR images from various satellites or sensors. This paper introduces Multi-Satellite SBAS that exploits complementary information from different SAR data to generate integrated long-term ground displacement time series. The proposed method is employed to create the vertical displacement maps of Almokattam City in Egypt from 2000 to 2020. The experimental results are promising using ERS, ENVISAT ASAR, and Sentinel-1A displacement integration. There is a remarkable deformation in the vertical direction along the west area while the mean deformation velocity is −2.32 mm/year. Cross-validation confirms that the root mean square error (RMSE) did not exceed 2.8 mm/year. In addition, the research findings are comparable to those of the previous research in the study area. Consequently, the proposed integration method has great potential to generate displacement time series based on multi-satellite SAR data; however, it still requires further evaluation using field measurements. [ABSTRACT FROM AUTHOR]

The standard Permanent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) technique, which is commonly used for surface motion analysis, assumes linear deformation velocities. While effective for monitoring urban subsidence over short periods, it falls short when dealing with non-linear, earthquake-related deformations over extended timeframes. To address this limitation, we use a non-linear PSInSAR technique, which is an enhancement of PSInSAR, to identify non-linear deformation patterns. We processed Sentinel-1A images from ascending and descending orbits in the Islamabad/Rawalpindi region from December 2015 to January 2023 using non-linear PSInSAR. By calculating the differences in deformation, we analyzed surface movements and assessed the impact of the 2017 earthquake on urban areas. Our findings reveal that the earthquake significantly increased the deformation in ascending and descending orbit tracks, with an average deformation of up to 70 mm/yr and a line-of-sight movement of up to 30 mm/yr. Our observations indicate that the deformation is directed towards the line of sight in the north and south of the deformed area, suggesting subsidence between the two uplifting faults, potentially linked to a concealed fault line along the deformation zone boundary. This contradicts previous arguments, suggesting that water extraction is the leading cause of deformation. Our analysis with non-linear PSInSAR demonstrates that tectonics play a significant role in deformation, providing valuable insights into tectonic-activity-induced deformations in urban areas over the long term. [ABSTRACT FROM AUTHOR]

Hail damage is a leading cause of insured losses in Australia, but changes in this hazard have not been robustly quantified. Here, we provide a continental-scale analysis of changes in hail hazard in Australia. A hail proxy applied to reanalysis data shows that from 1979–2021 annual hail-prone days decreased over much of Australia but increased in some heavily populated areas. For example, the annual number of hail-prone days increased by ~40% around Sydney and Perth, the largest cities on Australia's east and west coasts, respectively. Changes in atmospheric instability have driven the trends. Radar observations, while covering shorter time spans and a more limited area than the reanalysis, corroborate the broad pattern of results. This study shows consistent hail-frequency trends in radar indicators and atmospheric environments and demonstrates substantial increases in hail frequency in major Australian cities where hail impacts are most significant. [ABSTRACT FROM AUTHOR]

Ulva prolifera (U. prolifera), a global eco-environmental issue, has been recurring annually in the Yellow Sea of China since 2007, leading to significant impacts on the coastal ecosystem and the economies of coastal cities. To enhance the frequency of daily monitoring for U. prolifera and to advance the multi-source remote sensing monitoring system, a combination of the Sentinel-1 SAR remote sensing satellite and the Sentinel-3 OLCI and NPP VIIRS optical remote sensing satellites was employed. This comprehensive analysis encompassed the examination of Sentinel-1 C band characteristics, the range of influence of U. prolifera, and the migration trajectory of its enrichment zones. On 6 June 2021, three satellite images depicted the northwest drift of U. prolifera, followed by a southward movement after making contact with the coast of Qingdao, China, on 12 June. The most extensive impact area caused by U. prolifera was observed on 18 June. Subsequently, the images revealed a contraction and enrichment of U. prolifera in an eas–-west direction. The amalgamation of radar and optical remote sensing satellites in a multi-frequency monitoring approach allows for a continuous all-weather surveillance mechanism for U. prolifera. This mechanism serves to provide timely alerts for the prevention and management of U. prolifera outbreaks. [ABSTRACT FROM AUTHOR]

Deformation monitoring has conventional increasing consideration in recent years due to its great importance in modern engineering. Darbandikhan town was hit by a strong earthquake on 12th November 2017 which is the Sarpol-e Zahab earthquake. Interferometric Synthetic Aperture Radar (InSAR) technique has been used to investigate Darbandikhan town stability and the surrounding areas of the Kurdistan region in Iraq. The purpose of this research is to estimate the ground vertical displacement induced by the earthquake as well as the east-west deformation components. Moreover, previous research covered more of Iran's side country that the earthquake had an impact on with little on Iraq's side (Northern-eastern of Iraq), so it was worth researching on Darbandikhan town and surrounding structures to estimate the displacement on its infrastructures. For this study, two pairs of Sentinel-1 Synthetic Aperture Radar (SAR) images are used from each ascending and descending tracks over the study area to validate the work. Then, two differential interferograms are created from these images, along Darbandikhan town and the surrounding areas. These differential interferograms are then converted to line of sight (LOS) displacements using open source software (SNAP 8.0). The overall vertical displacement of the residential area of Darbandikhan was estimated from -4 to -10 cm after the earthquake, and the overall east-west displacement was ranging from 2 to 6.4 cm. The current study does not only examine the northern east of Iraq but the whole area of Iran and Iraq in general that lies within the influence of the earthquake. This research could be useful to estimate the overall deformation of Darbandikhan town in particular and the whole area in general. Therefore, the authorities and civil engineers could think of more sustainable buildings and structures before they start to plan within the area of earthquake impact. [ABSTRACT FROM AUTHOR]

A tornado hit the northeastern suburbs of Hamburg, Germany, on 7 June 2016. It had an estimated strength of upper end F1 on the Fujita scale and was short-lived with an approximate duration of only 13 min and a path length of just about 1.3 km. We demonstrate that such a small-scale, extreme event can be observed and forecasted accurately by a low-cost radar and by an atmospheric model with low computational costs, respectively. Observations from a low-cost single polarized X-band radar covering the urban area of Hamburg with 60 m spatial and 30 s temporal resolution are analyzed with respect to their ability to capture the development as well as the track of the tornado. In contrast to the national C-band radar network, the X-band radar is capable of capturing the hook echo of the tornado as well as the circular pattern in rain rates, because of its higher resolution in space and time. High-resolution forecasts of the tornado event are conducted with the computational efficient Conformal Cubic Atmosphere Model (CCAM) in order to test the capability of predicting the tornado with a lead time of a few hours. A three step downscaling method is used to obtain a spatial resolution of 1 km with initial conditions taken from the NCEP analysis. Calculated severe weather indices clearly indicate a potential for a tornado. CCAM cannot explicitly resolve small scale tornadic features but the model simulates a strong convective cell only a few kilometers apart from the tornadic thunderstorm observed by the radar. [ABSTRACT FROM AUTHOR]

A timely and accurate spatial mapping of built-up areas (BA) is crucial in making cities and human settlements safe, resilient, and sustainable. Synthetic Aperture Radar (SAR) data are useful for BA mapping due to strong coherent backscatter from diverse human-made targets, distinct texture patterns, and sensitivity to its geometric characteristics. However, BA mapping using SAR data is still challenging due to various geometrical and physical factors that often lead to misinterpretations. Therefore, this study presents a novel method to map BA using single-date dual polarized Sentinel-1 SAR data to overcome such challenges in complex built-up scenarios. Here, we propose three normalized descriptors derived from the Stokes vector elements. These three descriptors are found to be vital in characterizing different types of BA structures. We then consider the symmetric quadratic mean of the normalized descriptors to propose a novel dual polarimetric radar built-up index (DpRBI). The proposed index provides information about the average normalized polarized power, which is useful for mapping diverse types of BA or their combination in an image. We assess the proposed methodology utilizing the Sentinel-1 image acquired over three major cities: Delhi, Milan, and Barcelona. The BA map accuracy for all three cities was found to be ≈ 85 % with a low BA omission error. We compared the mapping results with available BA/land cover products: World Settlement Footprint 2019 (WSF-19) and World cover 2020 (WC-20). The BA map obtained using the proposed index was better than WSF-19 and WC-20, particularly for BA omission errors. For example, we observed a relatively low BA omission error of 22.34 % using DpRBI compared to 31.86 % and 41.79 % for WC-20 and WSF-19, respectively, over Milan, Italy. The code is available at: https://github.com/navv37/DpRBI [ABSTRACT FROM AUTHOR]

Over the past several decades, subsidence has emerged as a significant issue affecting urban, coastal, and mining areas worldwide. This phenomenon has been exacerbated by a decrease in groundwater resources, which has become a major problem on a global scale. Insufficient availability of surface water has led to excessive exploitation of the earth's groundwater system through unplanned processes. As a result, serious problems have arisen, including economic challenges, hazardous activities, and damage to the Earth's surface. One of the most significant and impactful consequences of excessive groundwater extraction is land subsidence. During a comprehensive literature review focusing on land displacement, 40 research papers were analyzed and discussed. These studies explored various techniques employed to monitor subsidence, such as synthetic aperture radar (SAR), interferometry synthetic aperture radar (InSAR), persistent scatterer interferometry synthetic aperture radar (PS-InSAR), and differential synthetic aperture radar (D-InSAR). Researchers have consistently found a strong correlation between the over extraction of underground fluids, such as water, oil, and gas, and land subsidence. One prominent cause of land subsidence identified by researchers is the over extraction of underground fluids. When excessive amounts of water, oil, or gas are extracted from underground reservoirs, the resulting voids and reduced pressure cause the overlying land to sink and compact. This process can have severe consequences for human settlements, infrastructure, and ecosystems in affected areas. The depletion of groundwater reserves, in particular, has become a pressing concern because of its vital role in supporting agricultural, industrial, and domestic water needs. Furthermore, the underground construction of tunnels has also been identified as a significant contributor to land subsidence. The excavation of tunnels creates voids and alters the natural balance of underground structures, leading to ground settlement and subsidence. This issue is particularly relevant in urban areas where extensive tunneling projects are undertaken to facilitate transportation, utilities, and infrastructure development. To monitor and assess land subsidence, various methods and processes are employed. SAR, InSAR, PS-InSAR, and D-InSAR techniques are valuable tools in this regard. SAR uses satellite-based radar systems to capture high-resolution images of the Earth's surface, enabling the detection of subtle changes over time. In contrast, InSAR employs two or more radar images to measure ground deformation by analyzing interference patterns. PS-InSAR focuses on persistent scatterers, which are specific targets that exhibit stable radar reflections over time, providing precise measurements of subsidence. D-InSAR combines two radar images acquired at different times to accurately calculate differential ground movements. By using advanced monitoring methods, scientists can assess the extent of subsidence and develop strategies to mitigate its negative impacts. It is crucial to adopt sustainable practices and ensure careful management of groundwater resources to effectively address this pressing issue. [ABSTRACT FROM AUTHOR]

Coastal urban areas in tropical regions, such as Greater Jakarta (GJ) in Indonesia, are susceptible to flood hazards from torrential rainfall. Efforts to understand the convective mechanisms leading to this type of rainfall have been carried out extensively, especially for events occurring in the wet season. However, hydrometeorological risks persist even in the dry season, when the rainfall is more closely correlated with the diurnal wind circulation. Among the aspects of convective activities and this diurnal circulation, the details of the updraft remain the least studied and open for discussion. We investigate the role of the updraft in urban torrential rainfall over GJ, using data from a C‐band Doppler radar and reanalysis dataset during the dry season of 2018–2019. Employing back‐trajectory calculations, we locate updraft origins corresponding to the peak of daytime inland rainfall. Most updraft origins are localized at an NW–SE‐oriented front nearly parallel to the coastline on the low‐lying plain, suggesting a region of atmospheric destabilization favorable for convective activity. The dry‐season torrential rainfall over GJ may involve convective activity from this front, that from earlier updrafts originating above the densely populated area, and further enhancement coming from orographic contributions. Our findings suggest the important role of updrafts in the rainfall generation, providing insights into the convective mechanism over GJ. [ABSTRACT FROM AUTHOR]

In this article an analysis of urban rainfall from hourly to seasonal scales is conducted for the Netherlands, with a focus on its capital, Amsterdam. In addition, the potential of synoptic weather types and local wind directions to categorize extreme rainfall in Amsterdam is assessed. An analysis of gauge‐adjusted daily radar rainfall retrievals with 1 km spatial resolution for 10 years shows that rainfall is enhanced over Dutch cities compared to their rural surroundings, with a maximum of a 14.2% increase over the largest cities in winter. The annual cumulative rainfall in Amsterdam appears to be significantly higher compared to its surroundings. This is due both to the higher frequency of occurrence of urban rainfall and to the higher hourly mean intensities. Extreme hourly rainfall rates appear to be affected by urban areas only in summer. Diurnal and weekly rainfall cycles do not reveal any significant urban influence. A wind direction analysis reveals that extreme rainfall events can primarily be attributed to westerly and next to southerly air masses. An analysis of the Jenkinson and Collinson (JC) and the German Weather Service (Deutscher Wetterdienst, DWD) weather types with rainfall and extreme rainfall events reveals that the JC weather types are more indicative of situations associated with rainfall extremes, whereas the DWD weather types are more indicative of situations resulting in higher accumulated rainfall amounts. [ABSTRACT FROM AUTHOR]

Climate change represents an important cause of subsidence, especially in coastal cities affected by changes in surface water level and water table. This paper presents a complementary study of Interferometric Synthetic Aperture Radar (InSAR) and Ground Penetrating Radar (GPR) for the early detection of subsidence and sinkhole phenomena. The methodology was applied to a coastal urban area in Galicia, northwest Spain (humid region), showing apparent signs of subsidence and building settlement during the last two years. Two different InSAR methods are compared for the period from June 2021 to March 2022: PSI (Persistent Scatterer Interferometry) and SBAS (Small Baseline Subsets), and the average deformation velocities obtained resulted in −3.0 mm/yr and −4.1 mm/yr, respectively. Additional GPR data were collected in January 2022 to validate the InSAR results, which detected subsidence in agreement with the persistent scatters obtained from the PSI method. This is crucial information to plan preventive maintenance. [ABSTRACT FROM AUTHOR]

Globally many urban areas, including the coastal megacity of Mumbai, have witnessed the increasing threat of heavy rainfall and flooding in recent decades. This paper provides the first results of a radar campaign that has been set up to study the precipitation systems over Mumbai in 2018. Results indicate that the coastal city experiences heavy rainfall spells during both the pre-monsoon and monsoon periods and the convective systems originate from the eastern and western parts of the region, respectively. The collocated observations of clouds and precipitation fields identify a distinct diurnal variation in rainfall occurrences with three peaks for the pre-monsoon period. No such features were evident during the monsoon months. The rainfall peaks correspond to an intense meso-convective environment as observed from the S-band doppler radar. The feedback of the urban convective environment during the pre-monsoon period and the offshore moisture supply to the city during the monsoon months are the likely contributing factors for these contrasting diurnal behaviour. The microphysical characteristics of rainfall show that the raindrops of diameter greater than 1.5 mm dominate the pre-monsoon months compared to the monsoon period. The convective urban environment characterized by higher localized CAPE aids strong thermals leading to smaller drops shifting aloft and allowing bigger drops to precipitate locally during the pre-monsoon season. [ABSTRACT FROM AUTHOR]

An extensive magnetic survey has been carried out on a large part of the Roman and late antique city of Pollentia (Alcúdia, Mallorca, Spain), combined with ground penetrating radar (GPR) and electric resistivity imaging (ER Imaging) to obtain data for a better understanding of the ancient city. For magnetic measurements, the 7‐probe fluxgate gradiometer array was used. The GPR data were collected by means of a system equipped with two dual‐frequency antenna boxes of 200 and 600 MHz, respectively. The geophysical data provide some new insights into the layout of the city, with the identification of numerous structures in areas that are still unexplored by archaeological investigation. The results fill the gap of previous partial geophysical surveys and show an interesting, unseen image of ancient Pollentia. [ABSTRACT FROM AUTHOR]

A dense system of pre-Hispanic urban centers has been found in the Upano Valley of Amazonian Ecuador, in the eastern foothills of the Andes. Fieldwork and light detection and ranging (LIDAR) analysis have revealed an anthropized landscape with clusters of monumental platforms, plazas, and streets following a specific pattern intertwined with extensive agricultural drainages and terraces as well as wide straight roads running over great distances. Archaeological excavations date the occupation from around 500 BCE to between 300 and 600 CE. The most notable landscape feature is the complex road system extending over tens of kilometers, connecting the different urban centers, thus creating a regional-scale network. Such extensive early development in the Upper Amazon is comparable to similar Maya urban systems recently highlighted in Mexico and Guatemala. [ABSTRACT FROM AUTHOR]

The use of solar energy has shown the fastest global growth of all renewable energy sources. Efforts towards careful evaluation are required to select optimal locations for the installation of photovoltaics (PV) because their effectiveness is strongly reliant on exposure to solar irradiation. Assessing the shadows cast by nearby buildings and vegetation is essential, especially at the city scale. Due to urban complexity, conventional methods using Digital Surface Models (DSM) overestimate solar irradiation in dense urban environments. To provide further insights into this dilemma, a new modeling technique was developed for integrated 3D city modeling and solar potential assessment on building roofs using light detection and ranging (LiDAR) data. The methodology used hotspot analysis to validate the workflow in both site and without-site contexts (e.g., trees that shield small buildings). Field testing was conducted, covering a total area of 4975 square miles and 10,489 existing buildings. The results demonstrate a considerable impact of large, dense trees on the solar irradiation received by smaller buildings. Considering the site's context, a mean annual solar estimate of 99.97 kWh/m2/year was determined. Without considering the site context, this value increased by 9.3% (as a percentage of total rooftops) to 109.17 kWh/m2/year, with a peak in July and troughs in December and January. The study suggests that both factors have a substantial impact on solar potential estimations, emphasizing the importance of carefully considering the shadowing effect during PV panel installation. The research findings reveal that 1517 buildings in the downtown area of Austin have high estimated radiation ranging from 4.7 to 6.9 kWh/m2/day, providing valuable insights for the identification of optimal locations highly suitable for PV installation. Additionally, this methodology can be generalized to other cities, addressing the broader demand for renewable energy solutions. [ABSTRACT FROM AUTHOR]

Analyzing land subsidence using Multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) technology holds significant importance for the secure development of urban areas. Shenzhen, being a crucial component of the Pearl River Delta, faces the threat of land subsidence, similar to most deltaic cities. Numerous studies have already indicated the presence of severe land subsidence in certain localities of Shenzhen. However, due to limitations in data scope and research methodologies, the comprehensive spatial-temporal distribution of land subsidence across the entire city of Shenzhen remains unclear. This study initially employed MT-InSAR technology to process a total of 534 Sentinel-1A SAR images from three different frames (P11F71, P113F71, P11F65), covering the entire city of Shenzhen. This processing resulted in the generation of subsidence rate maps and subsidence time series. Subsequently, the temporal evolution patterns of the subsidence were analyzed while significant subsidence regions were identified. By integrating information from optical images reflecting human activities on the Earth's surface, the study deduced the subsidence mechanisms in various significant subsidence areas. Research findings indicate that land subsidence in Shenzhen is primarily caused by construction activities, with a concentration in the western coastal areas of Shenzhen, reaching a maximum rate of 80 mm/yr, located at the estuary of Dongbao River (113.770385, 22.745305). The cumulative subsidence from March 2017 to June 2023 amounts to 500 mm. The expansion of the Qinglinjing Reservoir has led to an increased demand for water, resulting in a significant rise in formation pressure and subsequent land subsidence. InSAR land subsidence monitoring and analysis in urban areas can address the spatial and temporal resolution limitations of traditional subsidence monitoring methods, providing effective recommendations for widespread subsidence prevention and control. [ABSTRACT FROM AUTHOR]

Tomographic synthetic aperture radar (TomoSAR) obtains elevation resolution by adding multiple baselines successively in the direction perpendicular to the line of sight, thereby realizing three-dimensional (3D) reconstruction of complex scenes and significantly promoting the development of the 3D application field. However, a large data redundancy and long mapping time in traditional 3D imaging lead to a large data transmission burden, low efficiency, and high costs. To solve the above problems, this paper proposes a distributed SAR high-resolution and wide-swath (HRWS) 3D imaging technology scheme. The proposed scheme overcomes the size limitation of traditional single-satellite antennas through the multi-channel arrangement of multiple satellites in the elevation direction to achieve HRWS imaging; meanwhile, the distributed SAR system is integrated with tomographic processing technology to realize 3D imaging of difficult areas by using the elevation directional resolution of TomoSAR systems. HRWS 3D SAR increases the baseline length and channel number by transmission in turn, which leads to excessive pulse repetition frequency and causes echoes of different pulse signals to overlap in the same receiving cycle, resulting in range ambiguity and thus seriously affecting the quality of the 3D reconstruction. To solve this problem, this paper proposes a range ambiguity resolution algorithm based on multi-beam forming and verifies it on the measured data from airborne array SAR. Compared with the traditional TomoSAR, the distributed HRWS 3D SAR scheme proposed in this paper can obtain a greater mapping bandwidth with the same resolution in a single flight, thereby enhancing the time correlation, reducing data redundancy, and greatly improving mapping efficiency. [ABSTRACT FROM AUTHOR]

During the last decades, synthetic aperture radar (SAR) image exploitation has matured with the launch of different satellite missions and the development of different techniques, which allow exploiting the capabilities of the radar images. Among these techniques, persistent scatterer interferometry (PSI) has proven to be a powerful tool to derive terrain deformations over urban areas. It is based on the use of a large number of images over wide areas in order to obtain terrain displacements time series. The imagery from the different SAR missions has led to an archive with data that covers up to 30 years in the past. Moreover, different methods and algorithms have been proposed in order to perform this complex task. In this line, this work aims at identifying if data from different missions and processed by different techniques can be combined in order to study the evolution of urban monitoring. Three different PSI techniques are used in order to process data from four SAR missions: European Remote Sensing (ERS)-1/2, Environmental Satellite, COSMO-SkyMed, and the recent Sentinel-1 A/B. The rapidly evolving urban area of Madrid, where numerous undergrounding works have been carried out in the last decade, has been chosen as the testing environment. The density of persistent scatterers, the deformation accuracy validated with GPS displacements and deformation trends are used as the key performance items for the assessment. [ABSTRACT FROM PUBLISHER]

Lima, Peru's capital, has about 9.6 million inhabitants and keeps attracting more residents searching for a better life. Many citizens, without access to housing subsidies, live in informal housing and shack settlements. A typical social phenomenon in Lima is the sudden illegal occupation of areas for urban settlements. When such areas are unsafe against natural hazards, it is important to relocate such a population to avoid significant future losses. In this communication, we present an application of Sentinel-1 synthetic aperture radar (SAR) images to map the extension of a recent occupation of an area with unfavorable soil conditions against earthquakes. [ABSTRACT FROM AUTHOR]

Health monitoring is important for densely distributed urban infrastructures, particularly in cities undergoing rapid economic progress. Permanent scatterer interferometry (PSI) is an advanced remote sensing observation technique that is commonly used in urban infrastructure monitoring. However, the rapid construction of infrastructures may easily cause a loss of coherence for radar interferometry, inducing a low density of effective permanent scatterer (PS) points, which is the main limitation of PSI. In order to address these problems, a novel time-series synthetic aperture radar interferometry (InSAR) process based on the adaptive window homogeneous pixel selection and phase optimization (AWHPSPO) algorithm and thermal expansion linear model (TELM) is proposed. Firstly, for homogeneous point selection, information on both the time-series intensity and deformation phases is considered, which can compensate for the defects of insufficient homogeneous samples and low phase quality in traditional distributed scatterer interferometric synthetic aperture radar (DS-InSAR) processing. Secondly, the physical, thermal expansion component, which reflects the material properties of the infrastructures, is introduced into the traditional linear model, which can more rationally reflect the temporal evolution of deformation variation, and the thermal expansion coefficients can be estimated simultaneously with the deformation parameters. In order to verify our proposed algorithm, the Orange Island area in Changsha City, China, was selected as the study area in this experiment. Three years of its historical time-series deformation fields and thermal expansion coefficients were regenerated. With the use of high-resolution TerraSAR-X radar satellite images, a maximum accumulated settlement of 12.3 mm and a minor uplift of 8.2 mm were detected. Crossvalidation with small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) results using Sentinel 1A data proved the reliability of AWHPSPO. The proposed algorithm can provide a reference for the control of the health and safety of urban infrastructures. [ABSTRACT FROM AUTHOR]

As urban economies flourish and populations become increasingly concentrated, urban surface deformation has emerged as a critical factor in city planning that cannot be overlooked. Surface deformation in urban areas can lead to deformations in structural supports of infrastructure such as road bases and bridges, thereby posing a serious threat to public safety and creating significant safety hazards. Consequently, research focusing on the monitoring of urban surface deformation holds paramount importance. Interferometric synthetic aperture radar (InSAR), as an important means of earth observation, has all-day, wide-range, high-precision, etc., characteristics and is widely used in the field of surface deformation monitoring. However, traditional solitary InSAR techniques are limited in their application scenarios and computational characteristics. Additionally, the manual selection of ground control points (GCPs) is fraught with errors and uncertainties. Permanent scatterers (PS) can maintain high interferometric coherence in man-made building areas, and distributed scatterers (DS) usually show moderate coherence in areas with short vegetation; the combination of DS and PS solves the problem of manually selecting GCPs during track re-flattening and regrading, which affects the monitoring results. In this paper, 45 Sentinel-1B data from 16 February 2019 to 14 December 2021 are used as the data source in the urban area of Horqin District, Tongliao City, Inner Mongolia Autonomous Region, for example. A four-threshold (coherence coefficient threshold, FaSHPS adaptive threshold, amplitude divergence index threshold, and deformation velocity interval) GCPs point screening method for PS-DS, as well as a Small Baseline Subset-Permanent Scatterers-Distributed Scatterers-Interferometric Synthetic Aperture Radar (SBAS-PS-DS-InSAR) method for selecting PS and DS points as ground control points for orbit refinement and re-flattening, are proposed. The surface deformation results obtained using the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) and the SBAS-PS-DS-InSAR proposed in this paper were comparatively analysed and verified. The maximum cumulative line-of-sight settlements were −90.78 mm and −83.68 mm, and the maximum cumulative uplifts are 74.94 mm and 97.56 mm, respectively; the maximum annual average line-of-sight settlements are −35.38 mm/y and −30.38 mm/y, and the maximum annual average uplifts are 25.27 mm/y and 27.92 mm/y. The results were evaluated and analysed in terms of correlation, mean absolute error (MAE), and root mean square error (RMSE). The deformation results of the two InSAR methods were evaluated and analysed in terms of correlation, MAE, and RMSE. The errors show that the Pearson correlation coefficients between the vertical settlement results obtained using the SBAS-PS-DS-InSAR method and the GPS monitoring results were closer to 1. The maximum MAE and RMSE were 13.7625 mm and 14.8004 mm, respectively, which are within the acceptable range; this confirms that the monitoring results of the SBAS-PS-DS-InSAR method were better than those of the original SBAS-InSAR method. SBAS-InSAR method, which is valid and reliable. The results show that the surface deformation results obtained using the SBAS-InSAR, SBAS-PS-DS-InSAR, and GPS methods have basically the same settlement locations, extents, distributions, and temporal and spatial settlement patterns. The deformation results obtained using these two InSAR methods correlate well with the GPS monitoring results, and the MAE and RMSE are within acceptable limits. By comparing the deformation information obtained using multiple methods, the surface deformation in urban areas can be better monitored and analysed, and it can also provide scientific references for urban municipal planning and disaster warning. [ABSTRACT FROM AUTHOR]

In recent years, Synthetic Aperture Radar (SAR) Tomography (TomoSAR) has ascertained great potential for the three-dimensional (3-D) reconstruction of observed scenes, especially in urban areas. However, the number of proceed snapshots (observations) is usually less than that of slant height samples (unknowns) in TomoSAR inversion processes. This impairs the quality of the reconstructed vertical information. To cope with this issue and improve the reliability of reconstructed vertical information, this paper investigates the possible potential of a deterministic descriptive regularization-based method. Deterministic descriptive regularization is a well-conditioned optimization framework based on the descriptive idea of a regularization solution. This strategy can help to mitigate the effect of the ill-posed problem. Thus, it can assist SAR tomography to deal with the possible impairing issues arising from low numbers and the distribution of baselines. For this purpose, the result of the proposed strategy is compared with the outcomes from the standard TomoSAR techniques, including Beamforming, Capon, and Minimum Norm. The proposed method for reconstruction of the reflectivity function of the observed scene has been performed on a dataset acquired by the Sentinel-1 sensor in 2022 over Tehran City, Iran. The experimental results indicate that the proposed algorithm can estimate building heights with a vertical accuracy of better than 91%. These results demonstrate the great potential of the proposed method for reconstructing the full 3-D images of urban areas. [ABSTRACT FROM AUTHOR]

Urban land subsidence is one of the important limiting factors for urban development, and strengthening the monitoring of urban surface subsidence contributes to long-term urban planning and construction needs. As a subcentral city in the Yangtze River Delta region of China, it is particularly important for Heifei to enhance the monitoring of surface subsidence. In this study, the persistent scatterer interferometric synthetic aperture radar (PS-InSAR) and small baseline subset (SBAS) techniques were used to process 139 scenes of Sentinel-1A SAR satellite ascending orbit data covering the central urban area of Hefei from July 2015 to July 2020, obtaining subsidence information for the region. The results show that the overall urban area of Heifei is relatively stable, but there are certain deformation trends in local areas. Four regions with obvious deformation were selected for the in-depth analysis of their deformation time series. The experimental study in this paper demonstrates that the PS-InSAR and SBAS techniques can achieve the accurate monitoring of large-scale ground subsidence in urban areas, ensuring the safety of buildings and their surrounding environments, and providing information support for urban security maintenance monitoring. [ABSTRACT FROM AUTHOR]

The paper presents the acquisition and data processing approach for the Ground Penetrating Radar (GPR) and laser scanner surveys carried out within the SOS project (the acronym comes from 'SOtto Siena', in English 'Beneath Siena'). SOS is a program aimed to overcome some of the problems and limitations currently present in the study of cities with long-term continuity of life, responding in particular to the need for a better understanding of the city's ancient fabric and hence to improvements in its conservation by: GPR city survey full coverage (of all the public spaces, streets, squares, courtyards, gardens, etc.), GIS data entry of the historical-archaeological and geoarchaeological knowledge and the development of a 3D Archaeological WEBGIS.The paper discusses the procedure for the creation of a 3D viewer within an already active WEBGIS platform, specifically created for the visualisation and management of archaeological data. The GPR data, once acquired, were exported in 3D in the form of point clouds and subjected to a procedure of cleaning and filtering from noise, so as to eliminate geometries not referable to anomalies and therefore to the presence of buried structures or cavities, and then transformed into mesh to meet the needs of the subsequent process of semantic enrichment. The GPR survey of the underground was flanked by laser scanning of some of the most significant structures in the historic centre (e.g. the cathedral). All 3D geometries were then inserted into the new visualiser via a pipeline using open-source tools and libraries. [ABSTRACT FROM AUTHOR]

The radar-retrieved refractivity fields provide detailed depictions of the near-surface moisture distribution at the meso-γ scale. This study represents a novel application of the refractivity fields by examining the spatiotemporal characteristics of moisture variability in a summertime coastal region in Taiwan over 4 weeks. The physiography in Taiwan lends itself to a variety of flow features and corresponding moisture behavior, which has not been well studied. High-resolution refractivity analyses demonstrate how a highly variable moisture field is related to the complex interaction between the synoptic-scale winds, diurnal local circulations, terrain, storms, and heterogeneous land use. On average, higher refractivity (water vapor) is observed along the coastline and refractivity decreases inland toward the foothills. Under weak synoptic forcing conditions, the daytime refractivity field develops differently under local surface wind directions determined by the synoptic-scale prevailing wind and the sea-breeze fronts. High moisture penetrates inland toward the foothills with southwesterly winds, but it stalls along the coastline with southerly and northwesterly winds. The moisture distribution may further affect the occurrence of the inland afternoon storms. During the nighttime, the dry downslope wind decreases the moisture from the foothills toward the coast and forms a refractivity gradient perpendicular to the meridionally oriented mountains. Furthermore, the refractivity fields illustrate higher-resolution moisture distribution over surface station point measurements by showing the lagged daytime sea-breeze front between the urban and rural areas and the detailed nighttime heterogeneous moisture distribution related to land-use and rivers. [ABSTRACT FROM AUTHOR]

To achieve carbon neutrality quickly and deal with urban greenhouse effect, it is necessary to study the energy consumption of urban buildings. Energy consumption prediction is an important step in planning and managing energy use in buildings. At present, few studies have comprehensively considered the relationship between geometric features, functional types, location and energy use of buildings in urban built-up areas. In this paper, a spatial data-driven framework is introduced for the analysis and assessment of building energy consumption. The framework is grounded in the building centroid and is combined with single photon radar and point of interest data through the utilization of the nearest neighbor classification algorithm. Two megacities, Beijing and Shanghai, are taken as examples to illustrate the method and to generate the regional building energy use database. The results show that: a) building physical feature (geometric form, functional type) have a significant impact on energy consumption, and energy consumption is correlated with the economic level of the region; b) Energy use in urban built-up areas has obvious spatial agglomeration characteristics, and the siphon effect is obvious in region with high energy consumption. The contribution of the framework is to provide insights into the feasibility of employing multiple spatial data fusion for the analysis of energy consumption within urban built-up areas. This can be employed to address energy planning concerns and help promote sustainable environmental practices in urban areas worldwide. • This paper attempts to provide a feasible framework for analyzing urban building energy use by utilizing real-time urban semantic perception information and building features. • The proposed framework have comprehensively considered the relationship between geometric features, functional types, location and energy use of buildings. • The proposed methodology can obtain regional energy consumption stocks and produce spatial distribution results, thus improving the interpretability of the data. • The results show that energy use in urban built-up areas has obvious spatial agglomeration characteristics, and the siphoning effect is obvious in regions with high energy consumption. [ABSTRACT FROM AUTHOR]

New scattering models are constantly emerging to extract the detailed polarization information of ground targets. They contribute to the refined interpretation of Polarimetric Synthetic Aperture Radar (PolSAR) images. However, an increasingly prominent problem lies ahead of model decomposition methods when there are similar scattering models for a decomposition scheme. It is difficult to separate the polarization power of similar scattering mechanisms reasonably and robustly. Therefore, in this paper, we first analyze the necessity of orthogonality between scattering models. Following this, we propose two mutually orthogonal rank-1 scattering models, which can degenerate to mostly current scattering models. The orthogonality and adaptability of scattering models are considered in the model derivation. Simulated PolSAR data, real ALOS-2/PALSAR-2, GF-3, and E-SAR data are selected to validate the proposed method. As shown by the results, first, the proposed method enhances the double-bounce scattering contribution in urban areas and maintains the volume-scattering contribution in vegetation areas because it separates the polarization power of different scattering mechanisms more reasonably. Second, the proposed method is powerful in the robust interpretation of different ground targets, resulting from the orthogonality of scattering models. These two characteristics of orthogonal scattering models are expected to play a positive role in large-scale applications, especially in land-cover classification. [ABSTRACT FROM AUTHOR]

Due to the difficulty in detecting the upper breakpoint of active buried faults, high-resolution detection of active buried faults in urban areas is very important for urban planning and disaster risk mitigation. The seismic reflection technique is the most common technique used to image faults at depth, but it is difficult to precisely locate the upper breakpoint of active buried faults. Ground-penetrating radar (GPR) provides high-resolution imaging in ultrashallow exploration, but the penetration depth of traditional GPR is shallow. In this work, we conducted six GPR surveys with multifrequency (25 MHz, 50 MHz and 100 MHz) and high-power GPR antennas across the possible range of the Shuiyu fault based on seismic reflection results. We obtained the trace of the Shuiyu fault within 45 m of the surface in Datong city, and the fault was found to dip approximately 70–80° to the SE. According to the GPR results, we selected a location for trenching and excavated one trench across the Shuiyu fault. The trench results verified the accuracy of the fault imaging in the GPR profiles and helped to interpret the stratigraphic information in the GPR profiles. In the accurate detection of active buried faults in other urban areas, the seismic reflection method can be used to determine the main strike of faults at depth, and then GPR can be used to detect the near-surface distribution of the faults in detail and guide trench location selection. The application of high-power GPR antennas with different frequencies in the fast detection of the upper breakpoint of active buried faults in urban areas is of great significance to earthquake hazard analysis and urban planning in Datong city. • The GPR can quickly and effectively locate the upper breakpoint of buried faults. • The combination of reflection seismic and GPR is reliable and high resolution. • The surface location of SYF in Datong city was obtained for the first time. • The SYF was active in late Late Pleistocene, the earthquake risk cannot be ignored. [ABSTRACT FROM AUTHOR]

Geomorphological hazards are considered as one of the environmental hazards that can be associated with many losses. Many areas, including the southern slopes of Alborz, are susceptible to a variety of geomorphological hazards, therefore, this study investigates the hazards of vertical displacement and landslides in the urban area and urban margin of Lavasan, located on the southern slopes of Alborz. This study was carried out in two stages, in the first step, to evaluate the vertical displacement of the region using the Sentinel radar image and SBAS time series method. In the second step, the geomorphological, geological and human parameters as well as the fuzzy logic model and ANP are used to evaluate the potential landslide prone areas. Thirdly, based on the results of the vertical displacement assessment as well as the potential assessment of landslide prone areas, hazardous areas of the study area have been identified. The results of the SBAS time series method show that the range of studies over the 3 year period has been about 12.4 mm uplift as well as 103.2 mm subsidence. Potential results of landslide-prone zones also indicate that limited northern study areas have great potential for landslides. Also the results of the evaluation of the hazardous areas in the study area indicate that the landslide susceptible areas of 30.1 km2, Areas with displacement more than 45 mm 26.27 km2 as well as landslide prone areas with displacement more than 45 mm 6.97 km2. [ABSTRACT FROM AUTHOR]

Peshawar is one of the most densely populated cities of Pakistan with high urbanization rate. The city overexploits groundwater resources for household and commercial usage which has caused land subsidence. Land subsidence has long been an issue in Peshawar due to insufficient groundwater removal. In this research, we employ the persistent scatterer interferometry synthetic aperture radar (PS-InSAR) technique with Sentinel-1 imaging data to observe the yearly land subsidence and generate accumulative time-series maps for the years (2018 to 2020) using the SAR PROcessing tool (SARPROZ). The PS-InSAR findings from two contiguous paths are combined by considering the variance over the overlapping area. The subsidence rates in the Peshawar are from −59 to 17 mm/yr. The results show that subsidence is −28.48 mm/yr in 2018, the subsidence reached −49.02 mm/yr in 2019, while in 2020, the subsidence reached −49.90 mm/yr. The findings indicate a notable rise in land subsidence between the years 2018 and 2020. Subsidence is predicted in the research region primarily due to excessive groundwater removal and soil consolidation induced by surficial loads. The correlation of land subsidence observations with groundwater levels and precipitation data revealed some relationships. Overall, the proposed method efficiently monitors, maps, and detects subsidence-prone areas. The utilization of land subsidence maps will enhance the efficiency of urban planning, construction of surface infrastructure, and the management of risks associated with subsidence. [ABSTRACT FROM AUTHOR]

Permafrost, known for its high sensitivity to climate change and human activities, plays a crucial role in comprehending the environmental sustainability of Arctic cities. Yakutsk, being the largest city situated in continuous permafrost, has suffered irreversible damage to surface buildings due to the widespread permafrost thaw. Therefore, it is imperative to conduct detailed monitoring and assessment of surface deformation to ensure the stable operation of building facilities and to plan urban development situated above the permafrost. This study utilized 138 scenes of Sentinel‐1B images captured between 2017 and 2021 to process the surface deformation variations of Yakutsk using the Persistent Scatterer Interferometric Synthetic Aperture Radar (PS‐InSAR) method. The surface deformation rate map reflects that the study area is undergoing extensive surface subsidence. The cumulative deformation time series maps effectively trace the temporal and spatial evolution of surface deformation, with the highest surface subsidence rates exceeding 40 mm/year and maximum cumulative subsidence exceeding 250 mm. In‐depth analysis of the obtained results indicated that the permafrost in Yakutsk is undergoing degradation, and the primary reason for surface subsidence is the thawing of foundation soils and the degradation of ice‐bearing permafrost. This study provides basic data for the investigation of geohazards caused by surface subsidence in Yakutsk. [ABSTRACT FROM AUTHOR]

The increased need for water resources in urban sprawls and intense droughts has forced more aggressive groundwater extraction resulting in numerous urban areas undergoing land subsidence. In most cases, only some large metropolitan areas have been well-characterized for subsidence. However, there is no existing country-wide assessment of urban areas, population, and households exposed to this process. This research showcases a methodology to systematically evaluate urban localities with land subsidence higher than − 2.8 cm/year throughout Mexico. We used Interferometric Synthetic Aperture Radar (InSAR) tools with a dataset of 4611 scenes from European Space Agency's Sentinel-1 A/B SAR sensors acquired from descending orbits from September 2018 through October 2019. This dataset was processed at a supercomputer using InSAR Scientific Computing Environment and the Miami InSAR Time Series software in Python software. The quality and calibration of the resulting velocity maps are assessed through a large-scale comparison with observations from 100 continuous GPS sites throughout Mexico. Our results show that an urban area of 3797 km2, 6.9 million households, and 17% of the total population in Mexico is exposed to subsidence velocities of faster than − 2.8 cm/year, in more than 853 urban localities within 29 land subsidence regions. We also confirm previous global potential estimations of subsidence occurrence in low relief areas over unconsolidated deposits and where groundwater aquifers are under stress. The presented research demonstrates the capabilities for surveying urban areas exposed to land subsidence at a country-scale level by combining Sentinel-1 velocities with spatial national census data. [ABSTRACT FROM AUTHOR]

Recently, global urbanization and industrialization have resulted in excessive groundwater exploitation, and the occurrence and damage of land subsidence to human life and property are increasing accordingly. The present study assessed the impact of tunnel excavation on the groundwater system and potential land subsidence in a Korean metropolitan area. A numerical model was established to predict groundwater level variations with tunnel excavation, and the mechanisms and cases of land subsidence worldwide were reviewed. The established model adequately represented the groundwater system in the study area. The tunnel excavation decreased the groundwater level along the tunnel line, and significant groundwater drawdown primarily occurred up to 6.1 m at locations with high permeability, leading to the temporary development of a large depression cone. The study area has favorable conditions for land subsidence, and curved tunnel excavation may induce ground disturbance, resulting in groundwater inflow and soil loss in the region. In addition, the risk of land subsidence is expected to persist owing to the lag time caused by the creep phenomenon, even though the groundwater level recovers. Efforts to effectively reduce land subsidence damage in urban areas are crucial, requiring measures such as controlling land subsidence occurrence and implementing prevention measures through early recognition, including artificial recharge of groundwater, underground cavity observation with ground penetrating radar, land subsidence observation with a borehole extensometer, and groundwater level monitoring systems. [ABSTRACT FROM AUTHOR]

Raindrop size distribution (DSD) information is fundamental in understanding the precipitation microphysics and quantitative precipitation estimation, especially in complex terrain or urban environments which are known for complicated rainfall mechanism and high spatial and temporal variability. In this study, the DSD characteristics of rainy seasons in the Beijing urban area are extensively investigated using 5-year DSD observations from a Parsivel 2 disdrometer located at Tsinghua University. The results show that the DSD samples with rain rate < 1 mm h -1 account for more than half of total observations. The mean values of the normalized intercept parameter (log⁡10Nw) and the mass-weighted mean diameter (Dm) of convective rain are higher than that of stratiform rain, and there is a clear boundary between the two types of rain in terms of the scattergram of log⁡10Nw versus Dm. The convective rain in Beijing is neither continental nor maritime, owing to the particular location and local topography. As the rainfall intensity increases, the DSD spectra become higher and wider, but they still have peaks around diameter D∼0.5 mm. The midsize drops contribute most towards accumulated rainwater. The Dm and log⁡10Nw values exhibit a diurnal cycle and an annual cycle. In addition, at the stage characterized by an abrupt rise of urban heat island (UHI) intensity as well as the stage of strong UHI intensity during the day, DSD shows higher Dm values and lower log⁡10Nw values. The localized radar reflectivity (Z) and rain rate (R) relations (Z=aRb) show substantial differences compared to the commonly used NEXRAD relationships, and the polarimetric radar algorithms R(Kdp) , R(Kdp , ZDR) , and R(ZH , ZDR) show greater potential for rainfall estimation. [ABSTRACT FROM AUTHOR]

Polarimetric decomposition is an effective way to analyze the scattering mechanism of targets in polarimetric synthetic aperture radar (PolSAR) images. However, the analysis of urban areas is frequently a challenge. Most decomposition methods use a rotated dihedral derived via rotation matrix to model the double-bounce scattering mechanism of buildings. However, according to electromagnetic theory, the existing dihedral model is not accurate, especially when the orientation angle of the dihedral is large. Therefore, the double-bounce scattering contribution in urban areas with large orientation angles will be difficult to extract. To address this problem, based on physical optics (PO) and geometric optics (GO), the interaction process of electromagnetic waves and the rotational dihedral is analyzed, and then a modified rotational dihedral model (MRDM) is proposed for the accurate representation of the rotational double-bounce scattering mechanism. Accordingly, MRDM is introduced to a five-component decomposition method (MRDM-5SD) to analyze the scattering components in an urban area. The validity of MRDM-5SD is demonstrated using several data sets. The experimental results show that the power contributions of double-bounce scattering in urban areas with large orientation angles increase by using MRDM-5SD. Therefore, MRDM can provide support for feature extraction and target detection in urban areas. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar (SAR) tomography (TomoSAR) has been widely used in the three-dimensional (3D) reconstruction of urban areas using the multi-baseline (MB) SAR data. For urban scenarios, the MB SAR data are often acquired by repeat-pass using the spaceborne SAR system. Such a data stack generally has long time baselines, which result in different atmospheric disturbances of the data acquired by different tracks. These factors can lead to the presence of phase errors (PEs). PEs are multiplicative noise for observation data, which can cause diffusion and defocus in TomoSAR imaging and seriously affect the extraction of target 3D information. In this paper, we combine the methods of the block-building network (BBN) and phase gradient autofocus (PGA) to propose a novel phase compensation method called BBN-PGA. The BBN-PGA method can effectively and efficiently compensate for PEs of the MB SAR data over a wide area and improve the accuracy of 3D reconstruction of urban areas. The applicability of this proposed BBN-PGA method is proved by using simulated data and the spaceborne MB SAR data acquired by the TerraSAR-X satellite over an area in Barcelona, Spain. [ABSTRACT FROM AUTHOR]