Land Deformation Monitoring Research Articles

Nationwide urban ground deformation in Japan for 15 years detected by ALOS and Sentinel-1

InSAR time series analysis has become a major tool for nationwide land deformation monitoring. Sentinel-1 SAR data have enabled us to measure and monitor ground deformation globally with high accuracy and resolution through InSAR time series analysis, due to its constant and frequent global coverage and open data policy since 2014. Although several datasets from previous SAR satellites were available before Sentinel-1, such comprehensive deformation monitoring was not performed due to several limitations such as data quality, analysis technique, data policy, and processing capacity at that time. However, since a large amount of ALOS InSAR products and an open-source InSAR time series analysis tool LiCSBAS have become openly and freely available, we can easily derive the deformation from 2006 to 2011 by using them. In this study, we detected the deformation time series and velocity in all major urban areas in Japan from 2006 to 2011 and compared the results with the deformation from 2014 to 2020 detected by Sentinel-1 data. The two deformation datasets with different time periods revealed various 15-year deformation histories, such as long-term constant subsidence in Tomakomai and Niigata, changes in deformation areas and/or velocities in Hirosaki, Kujyukuri, Kanazawa, and Matsushiro, and appearance or disappearance of deformation in Joso, Yoyogi, and Kyoto. Future abundant and continuous SAR data acquisitions will reveal more long-term deformation transitions and help to understand the details of the mechanisms.

Land deformation monitoring in the Taiyuan area based on PS-InSAR.

Land subsidence problems have become increasingly prominent. Traditional monitoring methods, such as level measurements, have high costs and low efficiency. Permanent scatterer interferometric synthetic aperture radar (PS-InSAR) has several advantages for land subsidence monitoring based on technological innovations. Aimed at resolving the key problems associated with PS-InSAR technology, the accuracy of three external digital elevations models (DEMs, namely, SRTM, ASTER GDEM, and PleiadesDEM) was analysed and compared. We found that the introduction of ground control points can significantly improve the elevation accuracy of DEMs. Herein, we introduce the specific processing steps and selection of the key parameters for IN-SAR data using the StaMPS software. We discuss the differences between IN-SAR technology and levelling measurements as well as the influence that the different external DEMs have on IN-SAR data. Based on 36 scenes of TerraSAR-X images, we obtained results for land deformation monitoring in Taiyuan City using PS-InSAR technology, which provided satisfactory monitoring results.

Application of Optimized Grey-Markov Model to Land Subsidence Monitoring With InSAR

Land subsidence prediction in mining areas is one of the most important applications of land deformation monitoring, which is significance for safe production. We used interferometric point target analysis (IPTA) timing series interferometry synthetic aperture radar (InSAR) processing technology to analyze the land subsidence results for the Xinfa mining area from 2017 to 2020; and compared them to global positioning system (GPS) static monitoring data. We proposed a residual correction theory based on deviation coefficient using the grey prediction and Markov models, and an optimized Grey-Markov model (RGM-M model) was established to predict the land subsidence of the mining area. Our results show that: (1) The maximum difference between InSAR timing processing results and GPS monitoring data in the same period is 10.91mm; they have roughly the same subsidence trend, indicating that IPTA timing series InSAR technology are strongly reliable in mining deformation. (2) Compared to the traditional Grey-Markov model, the improved residual correction and dynamic assignment of the Grey-Markov model improves the prediction accuracy. The optimized residual correction and dynamic empowerment of the Grey-Markov model prediction results are more suitable for the actual fluctuation of land subsidence value in the mining area. The maximum root mean square error of the prediction results is 0.751mm, and the maximum average absolute percentage error is 7.46%, which has a certain guiding significance for the work of monitoring, prediction and safety management of land deformation in the mining area.

Integrating InSAR and deep-learning for modeling and predicting subsidence over the adjacent area of Lake Urmia, Iran

ABSTRACT InSAR processing is vastly used for land deformation monitoring from the space. Machine learning methods are known as strong tools for data modeling as well as predicting. In this study, we are going to model and predict the future behavior of land subsidence by InSAR processing and leveraging deep learning methods over the lands in the vicinity of Lake Urmia (located in the northwest of Iran). Accordingly, Sentinel-1 data over 56 months from November 2014 to June 2019 and small baseline subsets (SBAS) InSAR methods were utilized. Several regions with a high rate of subsidence were identified (maximum monthly subsidence of 13.3 mm). Furthermore, environmental factors affecting subsidence were considered. Therefore, parameters such as rainfall, groundwater, and lake area variations were measured using TRMM, GRACE, and MODIS satellite data, respectively. In order to determine and assess the relation between land deformations and environmental variations, several machine learning methods were implemented. The environmental parameters were used as the input of models and ground deformations as the target to be predicted. Eventually, ground deformations were estimated using multi-layer perceptron (MLP), convolutional neural network (CNN), and long short-term memory (LSTM) networks, in which each network had strengths and weaknesses on different occasions. Thus, by blending the forecast of the three models, a weighted ensemble was constructed, which outperformed the single models and reached the root mean square error (RMSE), mean absolute error (MAE), and standard deviation (SD) of 8.2 mm, 6.4 mm, and ±5.2 mm, respectively. The result indicated that although each single model had proper accuracy, an ensemble model can improve land deformation anticipation using the strength of networks in various conditions.

LANDSLIDES MONITORING WITH TIME SERIES OF SENTINEL-1 IMAGERY IN YEN BAI PROVINCE-VIETNAM

Abstract. This paper presents an application of PS-InSAR method for determining landslide displacement velocity in Van Yen district, Yen Bai province, Vietnam. The used tools for processing data is a combination of two free software, SNAP 7.0 and STaMPS 4.1. With 27 Sentinel-1A images in descending direction acquired from 11th January 2019 to 1st March 2021, the landslide displacement values were calculated and exported. There were locations in which landslides correctly appeared, such as Lang Thip, Xuan Tam, Chau Que Ha, Phong Du Thuong communes and along provincial road 151. Landslide rate is determined from SAR image series with average value less than 16.5 mm/y in places with high terrain and steep slope. The distribution of permanent scatter (PS) points for landslides often appeared along the road slopes, especially the inter-communal and inter-provincial roads that have not been reinforced with structural mitigation measures. In 2013 a field survey was conducted by the Vietnam Institute of Geosciences and Mineral Resources for this area which was used to validate the results from SAR processing. Landslide velocity charts at certain landslide sites were derived. The current study demonstrated the feasibility of the method as well as the usage of Sentinel-1 data for land deformation monitoring in the mountainous area.

Land deformation monitoring by GNSS in the Nile Delta and the measurements analysis

Nile Delta, one of the most populated deltas around the world, is suffering from subsidence due to the natural compaction of its sediment. Land subsidence has a great impact on the infrastructure, economic, and social. This study investigatesthe evaluation of the land subsidence in Nile Delta using GNSS measurements. Eight stations of GNSS points through period 2013–2015 distributed around Nile Delta and the Northern part of Egypt are utilized using differential GPS with nine IGS stations by GAMIT/GLOBK V. 10.61. The main objective is to monitor the spatiotemporal variations of land surface within the Nile Delta by time series analysis of the ellipsoidal height. The northern part of Egypt can be divided into three major parts; the western part shows subsidence rate of 2 mm/year downward; Nile Deltaof 2.5 to 10 mm/year downward from west to east and the eastern part shows an uplift.

Landslide susceptibility mapping using MT-InSAR and AHP enabled GIS-based multi-criteria decision analysis

Landslide susceptibility maps (LSMs) are generally prepared by integrating multiple prominent thematic layers, including DEM derived products (elevation, slope, and aspect), and other parameters such as lithology, geomorphology, LULC, etc. These parameters can be assigned optimum weights using the analytic hierarchy process (AHP) method, followed by a GIS-based weighted overlay analysis. In recent years, multi-temporal interferometric synthetic aperture radar (MT-InSAR) techniques have been rigorously explored, for land deformation detection and monitoring, by extracting highly stable measurement pixels using tens of SAR acquisitions simultaneously. In this research work, a GIS-based multi-criteria decision analysis to prepare LSMs is proposed, with MT-InSAR derived displacement estimates used as a critical input parameter. An LSM is generated by processing 20 ERS-1/2 and Envisat ASAR images, acquired over ∼120 sq. km wide river basin, located in Uttarakhand, India. The generated LSM is found to be congruent with the susceptible maps made available by the Geological Survey of India (GSI) under the National Landslide Susceptibility Mapping (NLSM) program. Preliminary results indicate that the majority of the unstable zones along the Alaknanda River are correctly identified. The approach is further implemented to generate an updated susceptibility map using 60 scenes of freely available Sentinel-1A dataset, followed by validation through actual field survey. This resulted in the generation of an updated susceptibility map, which helped in the identification of 44.5% new landslide susceptible zones (LSZs). Furthermore, the status of previously identified zones is also quantified. The performance of the proposed approach suggests its usability in generating and updating near-real-time LSMs.

Land Deformation Monitoring in Lanzhou City Based on SBAS-InSAR Technology

With the continuous advancement of urban construction, the original natural landscapes such as wetlands, vegetation, and soil are converted into artificial landscapes such as buildings and roads, resulting in a wide range of changes in urban surface. Monitoring urban surface changes is of great significance to the healthy development of cities and the prevention of geological disasters. The traditional land deformation monitoring technology has the disadvantages of small monitoring range, large workload and low efficiency. Interferometric Synthetic Aperture Radar technology can effectively solve the defects in the traditional deformation monitoring technology. This paper takes Lanzhou as the research area, selects the Sentinel-1A data of 25 scenes from 2014 to 2016, and uses the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) for land deformation monitoring. The sedimentation observation results obtained by the SBAS-InSAR technique was analyzed with the methods of statistical analysis and time series analysis. The results show that: (1) The overall urban area of Lanzhou City has been slightly sunk, and the funnel in the deformation area is mainly concentrated in the mountainous areas, new residential buildings and subway stations. (2) From the perspective of each region, Shajingyiin Anning District, near XuanshengRundi in Jiuzhou, near Xiaodaping Driving Test Center, and near Xuanmagou-Badaoping Village in Chengguan, near Donggang Cargo Center, near Fulongping, near Hendafeicuihuating in Qilihe District, near Lanzhou West Railway Station and other places all showed strong subsidence trends, and the area with the highest deformation rate is Xiaodaping, which maximum average annual deformation velocity can reach 30.8mm/a, and the cumulative deformation is as high as 65.9mm.(3) The land deformation of Lanzhou City shows a non-linear downward trend, and the deformation gradually spreads in the east-west direction. Eventually, deformation also occurred in some foothills in the north and south, and in some urban areas. (4) The main driving factors for settlement in the urban area of Lanzhou are loess soil, rail transportation and urbanization.

Post-earthquake monitoring of landslides along the Southern Kaikōura Transport Corridor, New Zealand

The magnitude (Mw) 7.8 earthquake that struck North Canterbury on New Zealand’s South Island on the evening of 14 November 2016 caused widespread damage to infrastructure, in particular to road and rail within the South Kaikōura Transport Corridor (SKTC). This is the main transport corridor along the east coast of the South Island, and the coseismic landslides covered and destroyed parts of the State Highway 1 (SH1) road, as well as the railway lines. Post-earthquake aftershocks and significant rainfall events (e.g. Cyclones Debbie, Cook and Gita), further mobilised the de-stabilised greywacke rock mass and paleo-landslide debris that mantled the slopes. Indeed, the SKTC was affected by > 80 separate landslides that have impacted either the rail corridor, the road corridor, or both. A number of different landslide mechanisms occurred, including shallow translation slides of existing paleo-landslide debris and rotational slumping, as well as rock mass failure via wedge, planar or toppling. Here, we report on monitoring of three case study landslides, using multi-temporal analyses of digital elevation data (from LiDAR, TLS and UAV surveys), real-time extensometer and land deformation monitoring using GPS receivers, as well as survey prisms. These datasets provided important monitoring of near-surface movement, important for risk management along the transport corridor during the reinstatement works.

Land deformation monitoring using optical remote sensing and PS-InSAR technique nearby Gangotri glacier in higher Himalayas

In the present study, we have introduced a strategic technique for interrelating between slow land surface movement (SLSM) and land susceptibility (LS) map of a higher Himalayan region nearby Gangotri, India by integrating geospatial techniques based on modified frequency ratio technique acquired by optical remote sensing for LS mapping. On the other hand, PS-InSAR technique acquired by microwave remote sensing has been used for monitoring the SLSM. As SLSM is one of the major geological hazard susceptible for highly undulating terrain like Gangotri glacier basin in higher Himalaya which is also a most attractive tourist region in Uttarakhand, India. With the integration of this technology, it would be possible for monitoring SLSM and mapping LS of any hazardous area. PS-InSAR technique allows efficient planning by providing meticulous data about SLSM. PS-InSAR technique is used for monitoring SLSM in scale small within approximately millimetre range. Further, we have used SAR imageries of C band of ENVISAT satellite for the duration of March 2004–May 2007 for nearby Gangotri region. This work also comprises using satellite imageries of Landsat 7, Sentinel 2 and SRTM data for LS mapping purpose. The result shows that in the vicinity of the Gangotri region, the land surface movement was observed around 2 to 18 mm. Also, the study showed that the SLSM affected regions come under the High-risk zone of LS and vice versa.

Measuring Urban Subsidence in the Rome Metropolitan Area (Italy) with Sentinel-1 SNAP-StaMPS Persistent Scatterer Interferometry

Land subsidence in urban environments is an increasingly prominent aspect in the monitoring and maintenance of urban infrastructures. In this study we update the subsidence information over Rome and its surroundings (already the subject of past research with other sensors) for the first time using Copernicus Sentinel-1 data and open source tools. With this aim, we have developed a fully automatic processing chain for land deformation monitoring using the European Space Agency (ESA) SentiNel Application Platform (SNAP) and Stanford Method for Persistent Scatterers (StaMPS). We have applied this automatic processing chain to more than 160 Sentinel-1A images over ascending and descending orbits to depict primarily the Line-Of-Sight ground deformation rates. Results of both geometries were then combined to compute the actual vertical motion component, which resulted in more than 2 million point targets, over their common area. Deformation measurements are in agreement with past studies over the city of Rome, identifying main subsidence areas in: (i) Fiumicino; (ii) along the Tiber River; (iii) Ostia and coastal area; (iv) Ostiense quarter; and (v) Tivoli area. Finally, post-processing of Persistent Scatterer Inteferometry (PSI) results, in a Geographical Information System (GIS) environment, for the extraction of ground displacements on urban infrastructures (including road networks, buildings and bridges) is considered.

3D Land Mapping and Land Deformation Monitoring Using Persistent Scatterer Interferometry (PSI) ALOS PALSAR: Validated by Geodetic GPS and UAV

Complex topography and geological formation are the primary causes of frequent land deformation occurrence at Kelok Sembilan area, West Sumatra, Indonesia. This paper presents a research work on land mapping and land deformation monitoring carried out using persistent scatterer interferometry (PSI) synthetic aperture radar (SAR) technique at Kelok Sembilan bridge region. In this paper, 13 ascending Advanced Land Observation Satellite Phased Array L-band Synthetic Aperture Radar (ALOS PALSAR) scenes, taken from July 2007 to November 2010, were processed using PSI-SAR technique. Then, the land deformation analysis was performed in two of the critical landslide areas near the Kelok Sembilan bridge. For validation purpose, the results were compared with in situ ground measurement data obtained using both differential global positioning system technique, and 3-D photogrammetry technique based unmanned aerial vehicle. The land deformation analysis showed that both of the investigation areas are suffering a severe land movement of approximately −100 mm every year. In addition to that, the validation results showed erroneousness of less than 0.3%.

DEFORMATION EFFECTS OF DAMS ON COASTAL REGIONS USING SENTINEL-1 IW TOPS TIME SERIES: THE WEST LESVOS, GREECE CASE

Abstract. Coastal zones are vulnerable to erosion and loss by level sea rise. Subsidence caused by the reduction of fluvial sediments in coastal zones found close to dams, is another important deformation factor. Quantification of the deformation rate of coastal region is essential for natural and anthropogenic activities. The study utilizes Interferometric SAR (Synthetic Aperture Radar) techniques and exploits the archive of Sentinel-1 TOPS data for the period 2014–2016. The freely available, wide ground coverage (250 × 170 km) and small temporal resolution Sentinel-1 TOPS datasets are promising for coastal applications. Persistent Scatterer Interferometry (PSI) methodologies are considered state-of-the-art remote sensing approaches for land deformation monitoring. The selected PSI method is the Small Baseline Subset (SBAS) multitemporal InSAR technique. The study area of this study is the coastal zone of west region of Lesvos Island, Greece. The main characteristic of the area is the reduction of the fluvial sediment supply from the coastal drainage basins due to construction of dams and the abstraction of riverine sediments. The study demonstrates the potentials of the SBAS method for measuring and mapping the dynamic changes in coastal topography in terms of subsidence rates and discusses its advantages and limitations. The results show that natural and rural environments appear to have diverse ground deformation patterns.

DEFORMATION MEASUREMENT USING SENTINEL-1A/B IMAGERY

Abstract. Land deformation monitoring based on C-band Synthetic Aperture Radar Sentinel-1A/B imagery is the main focus of this paper. This type of data is exploited using a Persistent Scatterer Interferometry technique. The paper describes a deformation monitoring strategy, which is related to a specific monitoring scenario: a relatively small deformation area of interest surrounded by a stable area. In the case study considered in this work, the scenario corresponds to an area of potential subsidence induced by underground water pumping. In this specific case, the deformation area of interest has a radius of approximately 1 km. The proposed monitoring strategy takes advantage of the specific scenario at hand, and, in particular, of the availability of stable areas close to the area that potentially is affected by deformation. In this paper we briefly describe the proposed data analysis strategy. The key component of the strategy, i.e. the estimation of the atmospheric component, is illustrated in detail. Some examples of the two main products of the procedure, i.e. the deformation velocity map and the deformation time series, are discussed.

GEOSPATIAL ANALYSIS USING REMOTE SENSING IMAGES: CASE STUDIES OF ZONGULDAK TEST FIELD

Inclined topographies are one of the most challenging problems for geospatial analysis of air-borne and space-borne imageries. However, flat areas are mostly misleading to exhibit the real performance. For this reason, researchers generally require a study area which includes mountainous topography and various land cover and land use types. Zonguldak and its vicinity is a very suitable test site for performance investigation of remote sensing systems due to the fact that it contains different land use types such as dense forest, river, sea, urban area; different structures such as open pit mining operations, thermal power plant; and its mountainous structure. In this paper, we reviewed more than 120 proceeding papers and journal articles about geospatial analysis that are performed on the test field of Zonguldak and its surroundings. Geospatial analysis performed with imageries include elimination of systematic geometric errors, 2/3D georeferencing accuracy assessment, DEM and DSM generation and validation, ortho-image production, evaluation of information content, image classification, automatic feature extraction and object recognition, pan-sharpening, land use and land cover change analysis and deformation monitoring. In these applications many optical satellite images are used i.e. ASTER, Bilsat-1, IKONOS, IRS-1C, KOMPSAT-1, KVR-1000, Landsat-3-5-7, Orbview-3, QuickBird, Pleiades, SPOT-5, TK-350, RADARSAT-1, WorldView-1-2; as well as radar data i.e. JERS-1, Envisat ASAR, TerraSAR-X, ALOS PALSAR and SRTM. These studies are performed by Departments of Geomatics Engineering at Bülent Ecevit University, at İstanbul Technical University, at Yıldız Technical University, and Institute of Photogrammetry and GeoInformation at Leibniz University Hannover. These studies are financially supported by TÜBİTAK (Turkey), the Universities, ESA, Airbus DS, ERSDAC (Japan) and Jülich Research Centre (Germany).

Application of Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) technique to Land Deformation Monitoring in Warri Metropolis, Delta State, Nigeria

Warri is one of the mega cities in Delta State in the coastal region of Nigeria hosting many industries. One of the three of Nigeria oil refineries is located in Warri. This study reveals the occurence of land deformation in the Warri area which is not only because it was formed in a tectonic setting but because of the high demand of the underground water for indutrial and domestics uses, high population density and oil and gas exploration in the area. Land deformation in this area is currently being accelerated by this indiscriminate withdrawal of underground water from the aquifers and exploration of the oil and gas leading to the compacting sediments. In this study Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) technique was applied to monitor land deformation in Warri metropolis in the period between 09/02/2006 and 12/08/2010 with Envisat data obtained from European Space Agency (ESA). The processing was done using Stanford Method for Persistent Scatterers/Multi-Temporal InSAR (StaMPS). From the analysis of the results, land deformation is occurring in Warri metropolis at a moderate rates (±5mm/yr). During the preliminary investigations, structures, particularly buildings, were physically observed subsiding while some others with cracks of various types and degrees.

Land deformation monitoring in mining area with PPP-AR

The mining area deformation monitoring theory and method using precise point positioning (PPP) ambiguity resolution (AR) were studied, and an ambiguity fixing model with satellite and receiver combination phase delay (CPD) was proposed for zero-differenced PPP ambiguity fixing and its corresponding formula derivation was given. The data processing results for 1h at six IGS stations in China show that 93% of ambiguities can be fixed within 10min and all ambiguities can be fixed within 15min. After ambiguity fixing, the positioning accuracy is improved by more than 85% in the E and N directions, with absolute positioning accuracy reaching millimeter level, and it was improved by 70% in the U direction, reaching centimeter level; the proposed zero-differenced ambiguity fixing model can effectively improve the convergence rate and positioning accuracy in PPP. Data monitoring continuously conducted for half a year at four CORS stations of Shanxi China Coal Pingshuo Group validated the feasibility of using PPP in mining area deformation monitoring.

Monitoring Ground Deformation Using Extracted DEM from Stereo-Pair Images of ALOS/PRISM

This paper used high resolution stereo-pair images from PRISM of Advanced Land Observing Satellite to generate high precision digital elevation model of target areas, which adopts the method of object space automatic matching and control detection. Compared with the same resolution of DEM from the other way in the same area, the paper educes the area of land subsidence and changed trend and analyzes the factors of accuracy for building DEM. The New DEM has higher precision than the standard DEM and reflects the real geomorphology. Through the experimental statistical analysis, the proposed method can be used for large areas of land subsidence and deformation monitoring, which is timeliness to explore reasons of region deformation.

Land deformation monitoring using coherent target-neighbourhood networking method combined with polarimetric information: a case study of Shanghai, China

In this article, an advanced approach for land deformation monitoring using synthetic aperture radar (SAR) interferometry combined with polarimetric information is presented. The linear and nonlinear components of the deformation, the error of the digital elevation model (DEM) and the atmospheric artefacts can be achieved by a coherent target (CT)-neighbourhood networking approach. In order to detect recent land deformation in Shanghai, China, 12 ENVISAT advanced synthetic aperture radar (ASAR) alternating polarization images acquired from January 2006 to August 2008 are employed for deformation analysis. Over a 2.5-year period, two deformation velocity fields from HH and VV modes over Shanghai are derived using the CT-neighbourhood networking SAR interferometry (InSAR), then integrated into a final deformation map by a fusion scheme. It is found that the annual subsidence rates in the study area range from −20 to 10 mm year−1 and the average subsidence rate in the downtown area reaches −7.5 mm year−1, which is consistent with the local government statistics published in 2007.

Spaceborne Differential SAR Interferometry: Data Analysis Tools for Deformation Measurement

This paper is focused on spaceborne Differential Interferometric SAR (DInSAR) for land deformation measurement and monitoring. In the last two decades several DInSAR data analysis procedures have been proposed. The objective of this paper is to describe the DInSAR data processing and analysis tools developed at the Institute of Geomatics in almost ten years of research activities. Four main DInSAR analysis procedures are described, which range from the standard DInSAR analysis based on a single interferogram to more advanced Persistent Scatterer Interferometry (PSI) approaches. These different procedures guarantee a sufficient flexibility in DInSAR data processing. In order to provide a technical insight into these analysis procedures, a whole section discusses their main data processing and analysis steps, especially those needed in PSI analyses. A specific section is devoted to the core of our PSI analysis tools: the so-called 2+1D phase unwrapping procedure, which couples a 2D phase unwrapping, performed interferogram-wise, with a kind of 1D phase unwrapping along time, performed pixel-wise. In the last part of the paper, some examples of DInSAR results are discussed, which were derived by standard DInSAR or PSI analyses. Most of these results were derived from X-band SAR data coming from the TerraSAR-X and CosmoSkyMed sensors.