Satellite SAR Data Research Articles

Polarimetric ALOS PALSAR Time Series in Mapping Biomass of Boreal Forests

Here, we examined multitemporal behavior of fully polarimetric SAR (PolSAR) parameters at L-band in relation to the stem volume of boreal forests. The PolSAR parameters were evaluated in terms of their temporal consistency, inter-dependence and suitability for forest stem volume estimation across several seasonal conditions (frozen, thaw and unfrozen). The satellite SAR data were represented by a time series of PolSAR images acquired during several seasons in the years 2006 to 2009 by the ALOS PALSAR sensor. The study area was in central Finland, and represented a managed area in typical boreal mixed forest land. Utility of different PolSAR parameters, their temporal stability and cross-correlations were studied along with reference stand-level stem volume data from forest inventory. Further, two polarimetric parameters, cross-polarization backscatter and co-polarization coherence, were chosen for further investigation and stem volume retrieval. A relationship between forest stem volume and PolSAR parameters was established using the kNN regression approach. Ways of optimally combining PolSAR images were evaluated as well. For a single scene, best results were observed with polarimetric coherence (RMSE ≈ 38.8 m3/ha) for scene acquired in frozen conditions. An RMSE of 40.8 m3/ha (42.9%, R2 = 0.66) was achieved for cross-polarization backscatter in the best case. Cross-polarization backscatter was a better predictor than polarimetric coherence for few summer scenes. Multitemporal aggregation of selected PolSAR scenes improved estimates for both studied PolSAR parameters. Stronger improvement was observed for coherence with RMSE down to 34 m3/ha (35.8%, R2 = 0.77) compared to 38.8–51.6 m3/ha (40.8–54.3%) from separate scenes. Finally, the accuracy statistics reached RMSE of 32.2 m3/ha (34%, R2 = 0.79) when multitemporal HHVV coherence was combined with multitemporal HV-backscatter.

Circum-Arctic Changes in the Flow of Glaciers and Ice Caps from Satellite SAR Data between the 1990s and 2017

We computed circum-Arctic surface velocity maps of glaciers and ice caps over the Canadian Arctic, Svalbard and the Russian Arctic for at least two times between the 1990s and 2017 using satellite SAR data. Our analyses are mainly performed with offset-tracking of ALOS-1 PALSAR-1 (2007–2011) and Sentinel-1 (2015–2017) data. In certain cases JERS-1 SAR (1994–1998), TerraSAR-X (2008–2012), Radarsat-2 (2009–2016) and ALOS-2 PALSAR-2 (2015–2016) data were used to fill-in spatial or temporal gaps. Validation of the latest Sentinel-1 results was accomplished by means of SAR data at higher spatial resolution (Radarsat-2 Wide Ultra Fine) and ground-based measurements. In general, we observe a deceleration of flow velocities for the major tidewater glaciers in the Canadian Arctic and an increase in frontal velocity along with a retreat of frontal positions over Svalbard and the Russian Arctic. However, all regions have strong accelerations for selected glaciers. The latter developments can be well traced based on the very high temporal sampling of Sentinel-1 acquisitions since 2015, revealing new insights in glacier dynamics. For example, surges on Spitsbergen (e.g., Negribreen, Nathorsbreen, Penckbreen and Strongbreen) have a different characteristic and timing than those over Eastern Austfonna and Edgeoya (e.g., Basin 3, Basin 2 and Stonebreen). Events similar to those ongoing on Eastern Austofonna were also observed over the Vavilov Ice Cap on Severnaya Zemlya and possibly Simony Glacier on Franz-Josef Land. Collectively, there seems to be a recently increasing number of glaciers with frontal destabilization over Eastern Svalbard and the Russian Arctic compared to the 1990s.

The new landslide inventory of Tuscany (Italy) updated with PS-InSAR: geomorphological features and landslide distribution

In this paper, the updating of the landslide inventory of Tuscany region is presented. To achieve this goal, satellite SAR data processed with persistent scatter interferometry (PSI) technique have been used. The updating leads to a consistent reduction of unclassified landslides and to an increasing of active landslides. After the updating, we explored the characteristics of the new inventory, analysing landslide distribution and geomorphological features. Several maps have been elaborated, as sliding index or landslide density map; we also propose a density-area map to highlight areas with different landslide densities and sizes. A frequency-area analysis has been performed, highlighting a classical negative power-law distribution. We also explored landslide frequency for lithology, soil use and several morphological attributes (elevation, slope gradient, slope curvature), considering both all landslides and classified landslide types (flows, falls and slides).

Multimode Hybrid Geometric Calibration of Spaceborne SAR Considering Atmospheric Propagation Delay

The atmospheric propagation delay of radar signals is a systematic error that occurs in the atmospheric environment, and is a key issue in the high-precision geometric calibration of spaceborne SAR. A multimode hybrid geometric calibration method for spaceborne SAR that considers the atmospheric propagation delay is proposed in this paper. Error sources that affect the accuracy of the geometric calibration were systematically analyzed. Based on correction of the atmospheric propagation delay, a geometric calibration model for spaceborne SAR was established. The high precision geometric calibration scheme for spaceborne SAR was explored by considering the pulse-width and bandwidth of the signal. A series of experiments were carried out based on high-resolution Yaogan 13 (YG-13) SAR satellite data and ground control data. The experimental results demonstrated that the proposed method is effective. The plane positioning accuracy of YG-13 in stripmap mode without control points is better than 3 m, and the accuracy of the sliding spotlight mode is better than 1.5 m.

Exploitation of Satellite A-DInSAR Time Series for Detection, Characterization and Modelling of Land Subsidence

In the last two decades, advanced differential interferometric synthetic aperture radar (A-DInSAR) techniques have experienced significant developments, which are mainly related to (i) the progress of satellite SAR data acquired by new missions, such as COSMO-SkyMed and ESA’s Sentinel-1 constellations; and (ii) the development of novel processing algorithms. The improvements in A-DInSAR ground deformation time series need appropriate methodologies to analyse extremely large datasets which consist of huge amounts of measuring points and associated deformation histories with high temporal resolution. This work demonstrates A-DInSAR time series exploitation as valuable tool to support different problems in engineering geology such as detection, characterization and modelling of land subsidence mechanisms. The capabilities and suitability of A-DInSAR time series from an end-user point of view are presented and discussed through the analysis carried out for three test sites in Europe: the Oltrepo Pavese (Po Plain in Italy), the Alto Guadalentín (Spain) and the London Basin (United Kingdom). Principal component analysis has been performed for the datasets available for the three case histories, in order to extract the great potential contained in the A-DInSAR time series.

InSAR time-series monitoring of ground displacement trends in an industrial area (Oreokastro—Thessaloniki, Greece): detection of natural surface rebound and new tectonic insights

The industrial area of Oreokastro, NW of the city of Thessaloniki, is monitored using radar interferometry to determine the spatial evolution of the underlying ground deformation trends. Previous studies, using SAR data acquired between 1992 and 1999, have revealed subsidence; however, the driving mechanism has not been, so far, solidly explained. Here, SAR satellite data from ERS 1, 2 and ENVISAT missions, acquired between 1992 and 2010, are analysed to enhance our understanding of the ground displacement trends and provide a thorough interpretation of the phenomena. The analysis confirms a subsiding displacement pattern from 1992 to 1999, whereas the recent data indicate that after 2003 the motion direction has changed to uplift. This whole monitoring of subsidence and the subsequent uplift is a rarely documented phenomenon, and in the case of Oreokastro is not reflecting a natural process; on the contrary, the driver is anthropogenic, related to the regional aquifer activity. Our study also highlights the fact that the local faults act as groundwater barriers and captures the existence of a possible previously unknown tectonic structure.

Phase and amplitude analyses of SAR data for landslide detection and monitoring in non-urban areas located in the North-Eastern Italian pre-Alps

The main aim of this paper is to exploit information obtained from satellite SAR data to detect and monitor instability phenomena affecting hilly and scarcely urbanized areas, overtaking some of the restrictions due to the presence of thick vegetation. To this end, phase and amplitude analyses of COSMO-SkyMed SAR data were carried out on two landslides located in the North-Eastern Italian pre-Alps: Cischele roto-translational slide and Val Maso rotational slide—earth flow. In the first case, the careful choice of processing parameters allowed to evaluate landslide displacement fields considering the phase difference between SAR acquisitions. In the second case, the speed of movement and the deep changes in morphology and vegetation induced by the landslide did not allow to apply DInSAR techniques; in this case the variation in the amplitude between SAR acquisitions allowed to detect the area affected by the instability. Obtained results show that methods and techniques to analyse satellite SAR data could be further refined in order to provide useful tools for landslide mapping and monitoring.

Remote Sensing based Methane Emission from Rice Fields in Tiruchirapalli District

Rice cultivation has been recognized as one of the major anthropogenic source for CH4 emissions. Methane emission from rice fields is a microbial mediated anaerobic activity, mainly favoured by the flooded condition. SAR-based operational mapping of rice crop across a diverse range of environments is possible with the increasing availability of multi-temporal SAR satellite data. Precise estimation of methane emission from rice fields at regional scale depends on accurate assessment of rice area and the corresponding time of flooding in those fields with IPCC emission factor. Start of Season (SoS) map was derived from satellite data showing rice emergence dates in Tiruchirapalli district recording 87 to 121 days of flooding during rice growth period. The rate of methane emission based on IPCC factor ranged from 37.4 to 45.74 kg/ha for a period of 87 to 121 days of flooding. The total methane emission from Tiruchirapalli district was 1.57Gg during Samba season 2015-16.

Automatic Mexico Gulf Oil Spill Detection from Radarsat-2 SAR Satellite Data Using Genetic Algorithm

In this work, a genetic algorithm is exploited for automatic detection of oil spills of small and large size. The route is achieved using arrays of RADARSAT-2 SAR ScanSAR Narrow single beam data obtained in the Gulf of Mexico. The study shows that genetic algorithm has automatically segmented the dark spot patches related to small and large oil spill pixels. This conclusion is confirmed by the receiveroperating characteristic (ROC) curve and ground data which have been documented. The ROC curve indicates that the existence of oil slick footprints can be identified with the area under the curve between the ROC curve and the no-discrimination line of 90%, which is greater than that of other surrounding environmental features. The small oil spill sizes represented 30% of the discriminated oil spill pixels in ROC curve. In conclusion, the genetic algorithm can be used as a tool for the automatic detection of oil spills of either small or large size and the ScanSAR Narrow single beam mode serves as an excellent sensor for oil spill patterns detection and surveying in the Gulf of Mexico.

Subsidence mapping at regional scale using persistent scatters interferometry (PSI): The case of Tuscany region (Italy)

In this paper the mapping of subsidences in Tuscany (Italy) is presented. To achieve our goal satellite SAR data processed with persistent scatters interferometry (PSI) technique have been used. Several subsiding areas have been identified and three of them have been analyzed in detail and subsequently compared with literature work both to validate the results and to analyze the evolution of the identified subsidences. In general, this comparison confirmed the quality of the analyses and, furthermore, lead to the identification of an important ground uplift close to Prato city, an area that was historically affected by subsidence.

Multi-frequency satellite radar imaging of cultural heritage: the case studies of the Yumen Frontier Pass and Niya ruins in the Western Regions of the Silk Road Corridor

ABSTRACTSynthetic Aperture Radar (SAR) remote sensing is increasingly favoured in archaeological applications. However, the effectiveness of this technology for archaeological prospection has so far not been fully assessed. In this study, an integrated single-date and multi-temporal SAR data-processing chain was proposed to sharpen archaeological signs and hence their detection and monitoring. In total, 14 scenes of X-band Cosmo-SkyMed, C-band Sentinel-1 and L-band PALSAR data covering the Western Regions of the Silk Road Corridor in China were employed for two important archaeological sites including the Yumen Frontier Pass with emerging archaeological traces and Niya ruins with subsurface remains. The results pointed out that single-date satellite radar data were useful for the identification of subsurface traces buried under desert in the landscape-scale, whereas for the identification of emerging monuments, Sentinel-1 was limited by its lower spatial resolution compared to TerraSAR and PALSAR data. Multi-date products, such as interferometric coherence, the averaged radar signatures and RGB multi-temporal composites, were effective to sharpen archaeological traces as well as for change detection in Yumen Frontier Pass. This study presents a pilot assessment of satellite SAR data for the analysis and monitoring of archaeological features in the predominantly arid-sandy environmental characteristic of investigated sites.

Landslide stability evaluation using high-resolution satellite SAR data in the Three Gorges area

Because of its centimetre-level precision, SAR interferometry (InSAR) has been widely recognized as an effective tool for large-area deformation mapping. However, applications of InSAR technology are limited by temporal–geometric decorrelation and atmospheric disturbance. Large-field displacement could be underestimated as a result of these limitations. A point-like target offset tracking (PTOT) method that solely uses SAR pixel amplitude information through highly accurate image matching can measure 2D displacements in the azimuth and range directions. This method is minimally affected by decorrelation and weather, and it is more suitable for mapping large displacements. In this study, landslide-prone areas were identified using high-resolution TerraSAR-X InSAR data pairs with short normal baselines and temporal baselines covering Zigui County in the Three Gorges area, and the PTOT method was applied to study potential landslides using image pairs with long temporal baselines. An estimate of the cumulative deformation was given. Time series displacements measured at corner reflectors and point-like targets were analysed. The feasibilities of landslide detection using DInSAR and PTOT methods with high-resolution SAR images were then evaluated and summarized.

Investigation of Damage in and Around Kathmandu Valley Related to the 2015 Gorkha, Nepal Earthquake and Beyond

An earthquake with a magnitude of 7.8 (M w ) occurred at 11:56 NST (local time) on 25 April 2015, in the central part of Nepal (Gorkha).We organized a damage survey team and dispatched it to the affected area for several periods following the earthquake (May 26 to June 3: first trip, June 17 to 24: second trip, August 16 to 21: third trip and October 27 to November 2: forth trip) to investigate the damage and collect data. We found traditional construction methods are stronger than imagined. Many traditional earthquake-resistance technologies exist in Nepal. The first and second surveys were to collect timely statistical information on the damage to brick and stone masonry buildings and to confirm the availability of data and their sources for subsequent surveys. We also carried out a first-hand building damage survey in selected areas. The investigation of the strong-motion data set from the USGS Center for Engineering Strong Motion Data includes information from stations in Nepal that continued to function throughout the main shock and the several subsequent strong aftershocks of the 2015 earthquake. The third and fourth surveys were to collect the every building damage survey in selected areas. The motivation behind the survey was to obtain ground truth data for the calibration and improvement of a wide-area damage estimation system that uses satellite data; the system is currently under development by National Research Institute for Earth Science and Disaster Prevention (NEID) and the Japan Aerospace Exploration Agency (JAXA). A survey of the degree of damage was conducted for every house in Sankhu and Khokana by the European Macroseismic Scale (EMS) -98. This report outlines the findings of this investigation team into various aspects of the earthquake disaster in the Kathmandu Valley. The motivation behind the survey was to obtain ground truth data for the calibration and improvement of a wide-area damage estimation system that uses satellite data. Field surveys confirmed that the severely damaged urban area was well detected by the decrease derived from the ALOS-2 satellite SAR data. The higher classification accuracy for non-damaged area helps to detect the damaged urban area using this technique, immediately after a disaster.

Characteristics of short-period internal waves in the Kara Sea inferred from satellite SAR data

In this paper we present the results of short-period internal wave (SIW) observations in the Kara Sea on the basis of satellite ENVISAT ASAR data between July and October 2007. Altogether, 248 internal wave (IW) packets and solitons are identified in 89 SAR images. Detailed spatial statistics of IW signatures and their properties in the Kara Sea is presented. The primary regions of IW activity are the areas near the Kara Gates Strait, the southeastern part of the Novaya Zemlya Trough, and in the vicinity of Cape Zhelaniya. We identify the regions where large IW packets are observed with wavelengths up to 2–3 km and the front length exceeding 200 km. The mean interpacket distance for observed IWs is about 20 km, but it may reach 50–60 km. Consequent IW packets are observed to travel up to 500 km from the presumed generation points. The results of satellite observations are compared with results of previous studies.

Dike model for the 2012–2013 Tolbachik eruption constrained by satellite radar interferometry observations

Abstract A large dike intrusion and fissure eruption lasting 9 months began on November 27, 2013, beneath the south flank of Tolbachik Volcano, Kamchatka, Russia. The eruption was the most recent at Tolbachik since the Great Tolbachik Eruption from 1975 to 1976. The 2012 eruption was preceded by more than 6 months of seismicity that clustered beneath the east flank of the volcano along a NW–SE trend. Seismicity increased dramatically before the eruption, with propagation of the seismicity from the central volcano conduit in the final hours. We use interferometric synthetic aperture radar (InSAR) to compute relative displacement images (interferograms) for SAR data pairs spanning the eruption. We use satellite SAR data from the Canadian Space Agency's RADARSAT-2 and from the Italian Space Agency's COSMO-SkyMed missions. Data are modeled first through a Markov Chain Monte Carlo solution for a single tensile dislocation (dike). We then use a boundary element method that includes topography to model a distributed dike-opening model. We find the best-fitting dike dips 80° to the WNW with maximum opening of 6–8 m, localized in the near surface and more broadly distributed in distinct regions up to 3 km beneath the surface, which varies from 1 to 2 km elevation for the eruptive fissures. The distribution of dike opening and its correspondence with co-diking seismicity suggests that the dike propagated radially from Tolbachik's central conduit.

MERGING AIRBORNE LIDAR DATA AND SATELLITE SAR DATA FOR BUILDING CLASSIFICATION

Abstract. A frequent map revision is required in GIS applications, such as disaster prevention and urban planning. In general, airborne photogrammetry and LIDAR measurements are applied to geometrical data acquisition for automated map generation and revision. However, attribute data acquisition and classification depend on manual editing works including ground surveys. In general, airborne photogrammetry and LiDAR measurements are applied to geometrical data acquisition for automated map generation and revision. However, these approaches classify geometrical attributes. Moreover, ground survey and manual editing works are finally required in attribute data classification. On the other hand, although geometrical data extraction is difficult, SAR data have a possibility to automate the attribute data acquisition and classification. The SAR data represent microwave reflections on various surfaces of ground and buildings. There are many researches related to monitoring activities of disaster, vegetation, and urban. Moreover, we have an opportunity to acquire higher resolution data in urban areas with new sensors, such as ALOS2 PALSAR2. Therefore, in this study, we focus on an integration of airborne LIDAR data and satellite SAR data for building extraction and classification.

Tsunami Affected Farmland Extraction Using Morphological Profiles (MPs) Method by Satellite Images Including SAR and Visible Near-Infrared Band Data

Abstract. The agricultural fields along the coast were submerged under the sea water after the 2011 off the Pacific Coast of Tohoku Japan Tsunami. The conventional method of detecting Tsunami reached area by SAR satellite data is to compare the data obtained between previous to and after the Tsunami. However such kind of SAR data should be prepared prior to the natural disaster, but in many disaster cases, people have often encountered difficulties in finding such kind of data observed in advance in some regions. Therefore it is desirable to find a way to detect the flood suffering farmlands caused by a Tsunami, using only data observed after the disaster event. The morphological profiles (MPs) method are tested using ALOS/PALSAR and AVNIR-2 data. This MPs method is proposed as the tool for extracting information about the size, shape and the orientation of structures in single-band remote sensing images and has been improved to establish the extended morphological profiles(EMP) dealing with full-spectral information in the multi-/hyper-spectral data (Benediktsson, J.A. et al.,2003,2005). The author’s work is intended to apply this MPs method to combined single polarization SAR data and visual and near-infrared bands data. The results approximately coincide with the farmland regions actually reached by the Tsunami. This MPs method requires only data once obtained soon after a disaster, light computer resources and very short turnaround time. It should be suitable for the detection of Tsunami reached areas or tidal wave reached areas, caused by a Typhoon for example, using satellite data only once obtained after a disaster.

Combined use of SAR and optical data for environmental assessments around refugee camps in semiarid landscapes

Abstract. Over 15 million people were officially considered as refugees in the year 2012 and another 28 million as internally displaced people (IDPs). Natural disasters, climatic and environmental changes, violent regional conflicts and population growth force people to migrate in all parts of this world. This trend is likely to continue in the near future, as political instabilities increase and land degradation progresses. EO4HumEn aims at developing operational services to support humanitarian operations during crisis situations by means of dedicated geo-spatial information products derived from Earth observation and GIS data. The goal is to develop robust, automated methods of image analysis routines for population estimation, identification of potential groundwater extraction sites and monitoring the environmental impact of refugee/IDP camps. This study investigates the combination of satellite SAR data with optical sensors and elevation information for the assessment of the environmental conditions around refugee camps. In order to estimate their impact on land degradation, land cover classifications are required which target dynamic landscapes. We performed a land use / land cover classification based on a random forest algorithm and 39 input prediction rasters based on Landsat 8 data and additional layers generated from radar texture and elevation information. The overall accuracy was 92.9 %, while optical data had the highest impact on the final classification. By analysing all combinations of the three input datasets we additionally estimated their impact on single classification outcomes and land cover classes.

Combination of Conventional and Advanced DInSAR to Monitor Very Fast Mining Subsidence with TerraSAR-X Data: Bytom City (Poland)

In this work, the analysis of TerraSAR-X satellite images combining both conventional and advanced Differential Synthetic Aperture Radar Interferometry (DInSAR) approaches has proven to be effective to detect and monitor fast evolving mining subsidence on urban areas in the Upper Silesian Coal Basin (Poland). This region accounts for almost three million inhabitants where mining subsidence has produced severe damage to urban structures and infrastructures in recent years. Conventional DInSAR approach was used to generate 28 differential interferograms between 5 July 2011 and 21 June 2012 identifying 31 subsidence troughs that account up to 245 mm of displacement in 54 days (equivalent to 1660 mm/year). SqueeSARTM processing yielded a very dense measurement point distribution, failing to detect faster displacements than 330 mm/year, which occur within the subsidence troughs detected with conventional DInSAR. Despite this limitation, this approach was useful to delimit stable areas where mining activities are not conducted and areas affected by residual subsidence surrounding the detected subsidence troughs. These residual subsidence mining areas are located approximately 1 km away from the 31 detected subsidence troughs and account for a subsidence rate greater than 17 mm/year on average. The validation of this methodology has been performed over Bytom City were underground mining activity produced severe damages in August 2011. Conventional DInSAR permitted to successfully map subsidence troughs between July and August 2011 that coincide spatially and temporally with the evolution of underground mining excavations, as well as with the demolition of 28 buildings of Karb district. Additionally, SqueeSARTM displacement estimates were useful to delimit an area of 8.3 km2 of Bytom city that is affected by a residual mining subsidence greater than 5 mm/year and could potentially suffer damages in the midterm. The comparison between geodetic data and SqueeSARTM for the common monitoring period yields and average absolute difference of 7 mm/year, which represents 14% of the average displacement rate measured by the geodetic benchmarks. These results demonstrate that the combined exploitation of high-resolution satellite SAR data through both conventional and advanced DInSAR techniques could be crucial to monitor fast evolving mining subsidence, which may severely impact highly populated mining areas such as the Upper Silesia Coal Basin (USCB).

Practical Application of Satellite-Based SAR Interferometry for the Detection of Landslide Activity

After two decades of SAR satellite operation, their data, processed by interferometric techniques (InSAR), allows for a sensitive detection of terrain movements. Various projects have risen towards the detection of landslide activity and thus possibility of early warning system based on SAR data. The ability of InSAR techniques to detect a slope stability is limited and depends on slope orientation, movement rate, vegetation cover and temporal and spatial image resolution. This paper presents common issues found in past projects of the team of authors observing landslides using available satellite SAR data processed by various InSAR techniques. It is demonstrated that in some cases the basic differential InSAR combining only two images provides more valuable information compared to advance multi-temporal InSAR techniques.The paper aims at providing guidelines for maximal successful detection of landslide activity and to introduce pros and cons of the InSAR method, which often discussed in geology and geophysics circles. We prove the potential of techniques using satellite-based InSAR to identify creeping movement of structures built at moving slopes and the limited possibility to detect movements at moderately vegetated slopes by using especially the L-band or a combination of winter-season SAR and other images within very short temporal difference. It is possible to overcome misinterpretation of results by proper understanding of InSAR source phase component at slopes, including phase distortions due to SAR geometry, vegetation movement (vegetated mass movement) and atmospheric pressure changes correlated with height differences.