ENVISAT ASAR Research Articles

An Analysis of Surface Subsidence in Chiba Using PSInSAR Technique

Abstract. Currently, surface subsidence has become an important problem what we are facing. Because of complex topography, uneven distribution of rainfall, and the fast development of urbanization, many cities of the world have undergone surface subsidence disaster, such as Chiba, Paris, Tokyo, Beijing. The surface subsidence has occurred in Chiba since the early twenty-first century. The surface subsidence seriously threatens the safety of human life and property. In order to monitor surface subsidence, people have done a lot of research, and time-series InSAR technique with its better coverage, lower cost and high measurement accuracy advantages shows great potentiality for monitoring surface subsidence. Time-series InSAR technique can be applied for analysis of subtle surface subsidence which occurred consistently for a long term period. This paper uses time-series InSAR technique, Permanent Scatterers Interferometric SAR (PSInSAR), to monitor surface subsidence of Chiba. The used dataset consists of thirty-four Envisat ASAR images from September 2006 to August 2010. For the experimental results, this paper uses GPS data to verify the reliability of the results, and the results can provide information for local government to prevent the occurrence of surface subsidence.

Using Satellite SAR to Characterize the Wind Flow around Offshore Wind Farms

Offshore wind farm cluster effects between neighboring wind farms increase rapidly with the large-scale deployment of offshore wind turbines. The wind farm wakes observed from Synthetic Aperture Radar (SAR) are sometimes visible and atmospheric and wake models are here shown to convincingly reproduce the observed very long wind farm wakes. The present study mainly focuses on wind farm wake climatology based on Envisat ASAR. The available SAR data archive covering the large offshore wind farms at Horns Rev has been used for geo-located wind farm wake studies. However, the results are difficult to interpret due to mainly three issues: the limited number of samples per wind directional sector, the coastal wind speed gradient, and oceanic bathymetry effects in the SAR retrievals. A new methodology is developed and presented. This method overcomes effectively the first issue and in most cases, but not always, the second. In the new method all wind field maps are rotated such that the wind is always coming from the same relative direction. By applying the new method to the SAR wind maps, mesoscale and microscale model wake aggregated wind-fields results are compared. The SAR-based findings strongly support the model results at Horns Rev 1.

A Backscattering Model of Rainfall Over Rough Sea Surface for Synthetic Aperture Radar

Spaceborne high-resolution synthetic aperture radar (SAR) is a potential powerful tool for rainfall pattern and intensity observations over the sea surface. However, many interesting rain-related phenomena revealed by SAR images are still not fully understood due to poor theoretical modeling of the rain–wind–wave interactions. This paper attempts to develop a physics-based radiative transfer model to capture the scattering behavior of rainfall over a rough sea surface. Raindrops are modeled as Rayleigh scattering nonspherical particles, whereas the rain-induced rough surface is described by the Log-Gaussian ring-wave spectrum. The model is validated against both empirical models and measurements. A case study of collocated Envisat ASAR data and NEXRAD rain data is presented to demonstrate the performance of the newly developed model. Finally, numerical simulation results suggest that rain-related scattering becomes significant as compared with wind-related scattering when the frequency is above C-band, whereas the raindrop volumetric scattering becomes significant above X-band.

Potential of diffuse scatterer interferometry for monitoring CO2 storage sites in European contexts (land cover types)

This article proposes to test the feasibility of long-term surface deformation monitoring based on synthetic aperture radar (SAR) interferometry on carbon dioxide (CO2) storage sites with land cover representative of potential European injection sites (agricultural or forests with minimum built-up land cover). Because no operational injection site is currently active in Europe, a SAR data set (based on EnviSAT–ASAR spaceborne data) is simulated by combining SAR scenes acquired over a potential future European injection site with deformation measurements from SAR analysis carried out on the In-Salah (Algeria) CO2 injection demonstrator site. The study shows that under such conditions, both persistent scatterer interferometry (PSI) and diffuse scatterer (DS) interferometry appear insufficient to provide a sufficiently dense measurement network to characterize surface deformation correctly. Alternative solutions, to be investigated in further studies, include the use of data archives with shorter acquisition time spans (e.g. Sentinel-1 data when available) or installation of corner reflectors. The cost of the latter mixed space/ground solution must be evaluated with respect to conventional ground-based measurement methods in the proposed context.

Tropical Forest Remote Sensing Services for the Democratic Republic of Congo inside the EU FP7 ReCover Project (Final Results 2000-2012)

Abstract. ‘ReCover’ was a 3-year EU-FP7 project (Nov. 2010 – Dec. 2013), aiming to develop and improve science based remote sensing services to support tropical forest management and activities to reduce emission from deforestation and forest degradation (REDD) in the tropical region (Häme et al., 2012). This is an overview of the final ReCover service delivery of 2000-2012 single-year optical (Landsat, ALOS AVNIR-2, RapidEye) and C-and L-band SAR (Envisat ASAR and ALOS Palsar, respectively) image mosaics, their derived forest/non-forest maps, a multi-sensor forest change map (2000-2010) and a biomass map (based on 2003-2009 ICESat GLAS) o he user of he De ocr ic Repub ic of Congo DRC), he Observatoir Satellitale des Forê s d’Afrique Cen r e OSFAC). The results are an improvement from a first iteration service delivery in 2012 after a critical review and validation process by both, the user and service providers, further method development and research, like a prior statistical data analysis considering temporal/seasonal variability, improved data pre-processing, and through the use of ground reference data collected in March 2013 for classification training. Validation with Kompsat-2 VHR data for the 2010 forest/non-forest maps revealed accuracies of 87% and 88% for optical and radar sensors, respectively.

Forest and Forest Change Mapping with C- and L-band SAR in Liwale, Tanzania

Abstract. As part of a Tanzanian-Norwegian cooperation project on Monitoring Reporting and Verification (MRV) for REDD+, 2007-2011 Cand L-band synthetic aperture radar (SAR) backscatter data from Envisat ASAR and ALOS Palsar, respectively, have been processed, analysed and used for forest and forest change mapping over a study side in Liwale District in Lindi Region, Tanzania. Land cover observations from forest inventory plots of the National Forestry Resources Monitoring and Assessment (NAFORMA) project have been used for training Gaussian Mixture Models and k-means classifier that have been combined in order to map the study region into forest, woodland and non-forest areas. Maximum forest and woodland extension masks have been extracted by classifying maximum backscatter mosaics in HH and HV polarizations from the 2007-2011 ALOS Palsar coverage and could be used to map efficiently inter-annual forest change by filtering out changes in non-forest areas. Envisat ASAR APS (alternate polarization mode) have also been analysed with the aim to improve the forest/woodland/non-forest classification based on ALOS Palsar. Clearly, the combination of C-band SAR and L-band SAR provides useful information in order to smooth the classification and especially increase the woodland class, but an overall improvement for the wall-to-wall land type classification has yet to be confirmed. The quality assessment and validation of the results is done with very high resolution optical data from WorldView, Ikonos and RapidEye, and NAFORMA field observations.

Technical Framework of Feature Extraction Based on Pixel-Level SAR Image Time Series

This study proposes a novel technical framework of feature extraction based on pixel-level synthetic aperture radar (SAR) image time series, to exploit the application potential of SAR image data with low and medium spatial resolution. This framework comprises three key parts: 1) construction of the pixel-level SAR image time series using a new matching technique based on progressive binary partition; 2) pixel-level similarity measurement via dynamic time warping (DTW); and 3) a new spatiotemporal similarity analysis method that improves feature extraction by considering both the similarity of a feature’s pixel-level time series and its spatial correlation. Two locations, covered by 31 low-resolution (150 m) and 26 medium-resolution (30 m) ENVISAT ASAR images, respectively, were selected as test cases to validate the proposed framework. Results show that the framework can identify features with a high level of accuracy, completeness, and correctness, outperforming methods using multitemporal images, as well as the time series-only (nonspatial) method, and other methods of spatiotemporal similarity analysis that use alternative similarity measures.

A User-Oriented Methodology for DInSAR Time Series Analysis and Interpretation: Landslides and Subsidence Case Studies

Recent advances in multi-temporal Differential Synthetic Aperture Radar (SAR) Interferometry (DInSAR) have greatly improved our capability to monitor geological processes. Ground motion studies using DInSAR require both the availability of good quality input data and rigorous approaches to exploit the retrieved Time Series (TS) at their full potential. In this work we present a methodology for DInSAR TS analysis, with particular focus on landslides and subsidence phenomena. The proposed methodology consists of three main steps: (1) pre-processing, i.e., assessment of a SAR Dataset Quality Index (SDQI) (2) post-processing, i.e., application of empirical/stochastic methods to improve the TS quality, and (3) trend analysis, i.e., comparative implementation of methodologies for automatic TS analysis. Tests were carried out on TS datasets retrieved from processing of SAR imagery acquired by different radar sensors (i.e., ERS-1/2 SAR, RADARSAT-1, ENVISAT ASAR, ALOS PALSAR, TerraSAR-X, COSMO-SkyMed) using advanced DInSAR techniques (i.e., SqueeSAR™, PSInSAR™, SPN and SBAS). The obtained values of SDQI are discussed against the technical parameters of each data stack (e.g., radar band, number of SAR scenes, temporal coverage, revisiting time), the retrieved coverage of the DInSAR results, and the constraints related to the characterization of the investigated geological processes. Empirical and stochastic approaches were used to demonstrate how the quality of the TS can be improved after the SAR processing, and examples are discussed to mitigate phase unwrapping errors, and remove regional trends, noise and anomalies. Performance assessment of recently developed methods of trend analysis (i.e., PS-Time, Deviation Index and velocity TS) was conducted on two selected study areas in Northern Italy affected by land subsidence and landslides. Results show that the automatic detection of motion trends enhances the interpretation of DInSAR data, since it provides an objective picture of the deformation behaviour recorded through TS and therefore contributes to the understanding of the on-going geological processes.

Characterizing C-band backscattering from thermokarst lake ice on the Qinghai–Tibet Plateau

On the basis of weather observations and field measurements of lake ice, this study investigates multi-temporal C-band VV-polarized radar backscattering values from the thermokarst lakes and alpine meadow on the QTP during the period 2003–2010. In order to understand the scattering mechanism of lake ice, a scattering model is developed for lake ice that updates some assumptions adopted in previously developed models, including the roughness of the ice–water interface and the shape of vertically stacked centimeter-sized bubbles in the lake ice. We conclude the following: First, with a incidence angle range near 24°, the backscattering intensities of C-band VV-polarized ENVISAT–ASAR data exhibit a strong dependence on time, which is related to the processes of ice growth and decay on the QTP. Some unique backscattering characteristics of lake ice in this high-altitude region, as compared to those for high-latitude regions, are also discussed and documented in the paper. Secondly, the timing of lake ice-on in fall and ice-off in spring for this region can be identified in radar images by using a threshold of −12dB for the backscatter intensity of the surrounding alpine meadow. Finally, the results of applying the scattering model indicate that surface scattering from the ice–water interface and volume scattering from gas bubbles embedded in the lake ice are the dominant scattering mechanisms for C-band VV polarized SAR and that the roughness of the ice–water interface and also bubble size are the most sensitive factors.

Ship detection method for single-polarization synthetic aperture radar imagery based on target enhancement and nonparametric clutter estimation

Ship detection with synthetic aperture radar (SAR) imagery often confronts severe speckle, heterogeneous regions, and system noise which cause false alarms due to the faint ship-sea contrast. Additionally, false negatives also occur when small vessels with low radar backscatter are observed. To solve these problems, a new ship detection method based on target enhancement and nonparametric clutter estimation is proposed. The method not only improves the ship-sea contrast for homogeneous and nonhomogeneous images but also adaptively estimates the clutter distribution in the enhanced image, which is crucial for the constant false-alarm rate (CFAR) detector. Subsequently, ships in the SAR image are detected by the proposed two-stage kernel density estimation CFAR (KDE-CFAR) with a low false-alarm rate and high detection probability. Compared with most existing algorithms, the proposed method provides a robust detection capability for both homogeneous and nonhomogeneous SAR images. Experimental results also reveal that the proposed method is an effective method for ship detection in various Radarsat-1 and Envisat ASAR images acquired with different operation modes.

One Operational Method for Offshore Wind Speeds Retrieval from SAR Image

The high resolution offshore wind speeds retrieval from SAR image is of great signification in the field of offshore wind energy estimation. In this paper, one operational method for offshore wind speeds retrieval from SAR image is conducted. Taking one scene ENVISAT ASAR image as a case study, the offshore wind speeds is operational retrieved combing with the NCEP/QSCAT blended sea surface wind directions. The retrieved wind speeds are compared with those from both the NCEP/QSCAT blended sea surface wind speeds and daily averaged Quick Scatter meter sea surface wind speeds. The results show that they are in good agreement. The root mean square errors of wind speed are 1.9 m/s and 1.6 m/s respectively, which show that the operational method for offshore wind speeds retrieval from SAR is available and give the orientation of SAR offshore sea surface wind energy business application in the future.

On the Detection of Oil Spill with China's HJ-1C SAR Image

This paper focuses on the analysis and evaluation of the China's HJ-1C SAR satellite with respect to oil spill identification. Six HJ-1C SAR images (S band, VV Pol, StripMap mode, 5 m resolution, Level-2) in a track in December 2012, covering the coastal region of Fujian Province of China, are used in this study.A comparison of the detectability of oil spill in between HJ-1C and Envisat ASAR images was investigated by introducing the Damping Coefficient s based on SAR intensity image.The difference of s was -1.3dB between the two oil spill samples considered in this paper revealed an expected result in accordance with visual inspection of themselves.

Time series synthetic aperture radar interferometry over the multispan cable-stayed Rio-Antirio Bridge (central Greece): achievements and constraints

The aim of the present study is to monitor by means of multitemporal synthetic aperture radar (SAR) interferometry the stability of the fully suspended cable-stayed Rio-Antirio Bridge (RAB) as well as the ground deformation of its surrounding area. The bridge is located in a region characterized by high hazard susceptibility, therefore, the monitoring of its behavior is of significant interest to mitigate potential risks. Envisat ASAR descending and TerraSAR-X ascending acquisitions were exploited using the persistent scatterer interferometry technique covering the periods 2002 to 2010 and 2010 to 2012, respectively. For both periods, ground displacement rates ranging from −12 to +12 mm/year indicate the absence of a significant deformation source acting during the period of investigation. Of interest is the differential motion pattern between Rio and Antirio for both SAR geometries, signifying the contribution of horizontal motion components, meanwhile allowing the quantification of the relative vertical displacement rates of these regions. For the RAB infrastructure, displacement histories were obtained from TerraSAR-X data analysis only for the stable part of the bridge, namely the viaducts and the four pylons, possibly due to the oscillation of its suspended part and the uncertainty of phase measurements over the pavement. The common behavior of the pylons was confirmed with an overall subsidence between −2 and −3 mm/year . The highest rates were observed for pylons established on specific soil types and were attributed to sediment consolidation.

Land Subsidence over Oilfields in the Yellow River Delta

Subsidence in river deltas is a complex process that has both natural and human causes. Increasing human activities like aquaculture and petroleum extraction are affecting the Yellow River delta, and one consequence is subsidence. The purpose of this study is to measure the surface displacements in the Yellow River delta region and to investigate the corresponding subsidence source. In this paper, the Stanford Method for Persistent Scatterers (StaMPS) package was employed to process Envisat ASAR images collected between 2007 and 2010. Consistent results between two descending tracks show subsidence with a mean rate up to 30 mm/yr in the radar line of sight direction in Gudao Town (oilfield), Gudong oilfield and Xianhe Town of the delta, each of which is within the delta, and also show that subsidence is not uniform across the delta. Field investigation shows a connection between areas of non-uniform subsidence and of petroleum extraction. In a 9 km2 area of the Gudao Oilfield, a poroelastic disk reservoir model is used to model the InSAR derived displacements. In general, good fits between InSAR observations and modeled displacements are seen. The subsidence observed in the vicinity of the oilfield is thus suggested to be caused by fluid extraction.

Estimation of Soil Moisture in Mountain Areas Using SVR Technique Applied to Multiscale Active Radar Images at C-Band

This paper presents an approach for retrieval of soil moisture content (SMC) from different satellite sensors with a focus on mountain areas. The novelties of the paper are: the extension of an already developed method to coarse resolution data (150 m) in mountain environment with high land heterogeneity, with only VV polarization and the proper selection of input features. During the result analysis, several algorithm characteristics were clearly identified: 1) the performances showed to be strongly related to input features such as topography and vegetation indices; 2) the algorithm needs a training phase; 3) the averaging window needs to be proper selected to take into account both the speckle noise and the characteristics of the area under investigation; and 4) the algorithm, being data driven, can be considered as site dependent. The experimental analysis is carried out on images acquired over the Südtirol/Alto Adige Province in Italy during 2010-2011 from the RADARSAT2 and Envisat ASAR in Wide Swath mode. SMC maps were compared with spatially distributed ground measurements, resulting in a root mean squared error (RMSE) value ranging from 0.045 to 0.07 m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> /m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> . Concerning the multiscale analysis, the results indicated that RADARSAT2 maps are able to detect the spatial heterogeneity and soil moisture dynamics at local scale, while ASAR WS SMC maps are able to identify mainly the two main classes of pasture and meadows. When these estimates are compared with SMC values from meteorological stations a RMSE value of 0.10 m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> /m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> for both satellites indicated a reduced capability to follow the temporal dynamics.

An Adaptive Approach of Satellite Baseline Estimation in InSAR

Baseline is an important parameter of radar interferometry. Generally, it can be estimated by satellite orbital data or ground control points. In this paper, an adaptive method is proposed to estimate it with combination satellite orbital data, and the accuracy of baseline estimated can be improved without ground control points; actual data of ERS and ENVISAT ASAR have been used in algorithm development and the final obtained elevation shows that the precise orbit data is more accurate than original orbit data in estimating baseline.

Multitemporal Analysis of the City of Nouakchott (Mauritania) Based on ENVISAT ASAR Images

Multitemporal Analysis of the City of Nouakchott (Mauritania) Based on ENVISAT ASAR Images The city of Nouakchott lies between the Atlantic Ocean to its west and the desert to its east. It is built on an almost level site located partially below sea level and is protected by a relatively narrow line of poorly vegetated coastal dunes displaying an average width of 150 m and an altitude less than 6 m. This setting fosters seawater incursion caused by storm surges. The city is also fractionated by a succession of highly mobile dunes which follow the northwestsouthwest wind lines with altitudes of up to twenty meters. The construction in 1986 of the “Port de l’Amitie” given its depth of 10 m, induced: (i) significant coastline growth north of the harbor; (ii) significant erosion south of the harbor. This rapid coastline evolution produced weakening of coastal dunes in certain sectors and led on several occasions, namely, December 1997, to seawater incursion. Rapid expansion, increased density of the urban fabric, erosion of costal dunes, increased frequency and intensity of rainfall, rising sea level, rising groundwater levels as well as densification of transportation and industrial infrastructures have made this city of over one million inhabitants increasingly vulnerable. Our job was to document urban sprawl and quantify coastline evolution via a diachronic study employing ENVISAT satellite ASAR radar imaging. For this, we produced 9 amplitude images at different dates (2004, 2005, 2008, 2009 and 2010) calibrated and Georeferenced to 20 meter resolution (WGS 84, UTM cartographic projection).

Sea Oil Spill Detection Method Using SAR Imagery Combined with Object-Based Image Analysis and Fuzzy Logic

Synthetic aperture radar (SAR), a sensor with all weather and day and night working capacity, has been considered one of the most powerful tools for sea surface oil spill detection. However, lookalikes frequently appear in SAR images, limiting the operational use of SAR to detect oil spilled at sea. 20 scenes of Envisat ASAR images, which were acquired during the oil spill accident in the Gulf of Mexico in 2010, are utilized, with the objective to study how to better differentiate oil spills from lookalikes. 145 and 134 samples for oil spill and lookalike, respectively, are extracted, and their object-based geometric, physical and textural features are analyzed, in order to find the most effective features for oil spill classification. Based on the results of feature analysis, fuzzy logic (FL) is employed to construct a classifier for oil spill detection. One advantage of the proposed method is that it can produce the crisp probability of a dark segment being oil spill. The experiment shows that our method can derive promising result.

Loess Slope Instability Assessment Based on PS-InSAR Detected and Spatial Analysis in Lanzhou Region, China

Lanzhou is a mountainous city in which serious disasters have occurred due to several slope hazards. We used PS-InSAR technique to detect surface deformation: an indicator of potential hazards. In the period extending from 2003 to 2010, 41 Envisat ASAR images were captured and analyzed using PS-InSAR. We identified 27186 PS points. The deformation velocity in this area is found to being 3.5 mm/year ~ -5.4 mm/year. The results were inserted into a GIS to derive spatial interpolations and map zones with different magnitudes of surface displacement. Then, we used the analytical hierarchic process (AHP) to statistically assess the susceptibility of loess slope hazards with lithology, slope, altitude, distance to road, Ndvi, land use and aspect. According to the result of the model, the study area could be classified into three categories: stable, less unstable and unstable. Causal mechanisms include human interactions in the landscape (construction, waste water discharge, etc.) and slope instability processes (landslide, subsidence, etc.).

Error Analysis on ESA’s Envisat ASAR Wave Mode Significant Wave Height Retrievals Using Triple Collocation Model

Nowadays, spaceborne Synthetic Aperture Radar (SAR) has become a powerful tool for providing significant wave height (SWH). Traditionally, validation of SAR derived SWH has been carried out against buoy measurements or model outputs, which only yield an inter-comparison, but not an “absolute” validation. In this study, the triple collocation error model has been introduced in the validation of Envisat ASAR derived SWH products. SWH retrievals from ASAR wave mode using ESA’s algorithm are validated against in situ buoy data, and wave model hindcast results from WaveWatch III wave model, covering a period of six years. From the triple collocation validation analysis, the impacts of the collocation distance and water depth on the error of ASAR SWH are discussed. It is found that the error of Envisat ASAR SWH product is linear to the collocation distance, and decrease with the decreasing collocation distance. Using the linear regression fit method, the absolute error of Envisat ASAR SWH was obtained with zero collocation distance. The absolute Envisat ASAR wave height error of 0.49 m is presented in deep and open ocean from this triple collocation validation work, in contrast to a larger error of 0.56 m in coastal and shallow waters. One of the reasons for the larger Envisat ASAR SWH errors in the coastal waters may be the inaccurate Modulation Transfer Function (MTF) adopted in the Envisat ASAR wave retrieval algorithm.