Perpendicular Baseline Research Articles

The utility of TerraSAR-X, TanDEM-X, and PAZ for studying global volcanic activity: Successes, challenges, and future prospects

TerraSAR-X (TSX), TanDEM-X (TDX), and PAZ Synthetic Aperture Radar data have been used at over 120 volcanoes to assess surface characteristics and change over time. We examine previous work, adding additional examples to understand where and when these data are most useful for volcanology. We focus on volcanoes as part of the Committee on Earth Observation Satellites (CEOS) Volcano Demonstrator Project. TSX/TDX/PAZ data provide a valuable means of detecting small surface changes from amplitude images and topographic changes from bistatic TSX/TDX data. For short temporal and perpendicular baselines, TDX/TSX/PAZ can also provide useful deformation data, even in presence of vegetation. No global background mission currently acquires TSX/TDX/PAZ data at volcanoes: 70 % high spatial resolution data, limiting their suitability for studying pre-eruptive unrest. Coordinated targeting by SAR constellations of priority volcanoes would provide data and insights valuable for forecasting eruptions and associated hazards.

Mapping Lava Flows on Venus Using SAR and InSAR: Hawaiʻi Case Study

AbstractWe explore the potential for repeat‐pass SAR Interferometry (InSAR) correlation to track volcanic activity on Venus' surface motivated by future SAR missions to Earth's sister planet. We use Hawai'i as a natural laboratory to test whether InSAR can detect lava flows assuming orbital and instrument parameters similar to that of a Venus mission. Hawai'i was chosen because lava flows are frequent, and well documented by the United States Geological Survey, and because Hawai'i is a SAR supersite, where space agencies have offered open radar data sets for analysis. These data sets have different wavelengths (L, C, and X bands), bandwidths, polarizations, look angles, and a variety of orbital baselines, giving opportunity to assess the suitability of parameters for detecting lava flows. We analyze data from ALOS‐2 (L‐band), Sentinel‐1 (C‐band), and COSMO‐SkyMed (X‐band) spanning 2018 and 2022. We perform SAR amplitude and InSAR correlation analysis over temporal baselines and perpendicular baselines similar to those of a Venus mission. Fresh lava flows create a sharp, noticeable decrease in InSAR correlation that persists indefinitely for images spanning the event. The same lava flows are not always visible in the corresponding amplitude images. Moreover, noticeable decorrelation persists in image pairs acquired months after the events due to post‐emplacement contraction of flows. Post‐emplacement effects are hypothesized to last longer on the Venusian surface, increasing the likelihood of detecting Venus lava flows using InSAR. We argue for further focus on repeat‐pass InSAR capabilities in upcoming Venus missions, to detect and quantify volcanic activity on Earth's hotter twin.

Very high frequency radiation emitted by negative narrow bipolar events occurred over malacca strait

In this paper, Very-High Frequency (VHF) radiation pulses associated with 11 negative Narrow Bipolar Events (NBEs) produced by a tropical storm over Malacca Strait are examined. The lightning data were recorded from a measurement station (ST) which consisted of a fast antenna (FA) and three VHF sensors (two 5 m perpendicular baselines interferometer). The average rise time (RT), average zero-crossing time (ZCT), average pulse duration (PD), and range of peak currents of the negative NBEs were 1.4 ± 0.4 μs, 2.7 ± 1.0 μs, 12.0 ± 6.9 μs, and −10 to −64 kA, respectively. The key finding is that all VHF radiation pulses have been found to precede the negative NBEs with an average lead time of 0.7 ± 0.3 μs. An interferometer map for one negative NBE (labelled as NBE10) detected at 35.7 km from ST has shown a characteristic of mixed propagation direction of fast streamers. The first VHF radiation source was detected at 12.4 ± 0.4 km above sea level. The total length and estimated velocity of the main propagation of the VHF radiation sources were 2.2 ± 0.7 km and between 1.4 × 108 and 2.8 × 108 ms−1, respectively. Moreover, based on the Himawari satellite image, the maximum extent of the cloud top height was estimated to be around 20.9 km over sea level (over Malacca Strait). All the VHF radiation sources associated with NBE10 were suggested to be detected above the main negative charge region (6 km altitude that corresponds to −10 °C). Thus, it could be suggested that NBE10 was initiated most likely in the environment of the ice crystals alone, based on the first altitude of the VHF radiation source and maximum extent of cloud top height.

Evaluating the Uncertainty in Coherence-Change-Detection-Based Maps of Torrential Sediment Transport in Arid Environments

InSAR coherence-change detection (CCD) is a promising remote sensing technique that is able to map areas affected by torrential sediment transport triggered by flash floods in arid environments. CCD maps the changes in the interferometric coherence between synthetic aperture radar images (InSAR coherence), a parameter that measures the stability of the radar signal between two different SAR images, i.e., data acquisitions. In arid environments, such changes are mainly due to changes in the surface. However, the residual effect of other factors on the InSAR coherence cannot be completely excluded. Therefore, CCD-based maps contain the uncertainty of whether the detected changes are actual changes in the observed surface or just errors related to those residual effects. Thus, in this paper, the results of four CCD mapping methods, with different degrees of complexity and sensitivity to the different factors affecting the InSAR coherence, are compared in order to evaluate the existence of the errors and their importance. The obtained CCD maps are also compared with changes in satellite optical images and a field campaign. The results lead to the conclusion that CCD maps are reliable in the identification of the zones affected by sediment transport, although the precision in the delimitation of the affected area remains an open issue. However, highly rugged relief areas still require a thorough analysis of the results in order to discard the geometric effects related to the perpendicular baseline.

Revealing the Land Subsidence Deceleration in Beijing (China) by Gaofen-3 Time Series Interferometry

Revealing the land subsidence in Beijing, China, induced by the massive groundwater extraction in the past three decades, is important to mitigate the hazards and protect the residences and infrastructure. Many SAR (Synthetic Aperture Radar) datasets have been successfully applied to reveal the land subsidence over Beijing in previous research, while few works were achieved on land subsidence revealed by time-series InSAR (Interferometric Synthetic Aperture Radar) with Gaofen-3 SAR images. In this study, we successfully perform the time-series InSAR analysis with Gaofen-3 SAR images to extract the land subsidence in Beijing from 2020 to 2021. The Sentinel-1 SAR images were used to assess the accuracy of Gaofen-3 images. The subsidence scale and extent are consistent in detected major subsidence bowls between the two datasets. The spatial–temporal evolution and the deceleration of Beijing land subsidence were revealed by comparing with the Sentinel-1 results from 2017 to 2020. Moreover, we evaluated the interferometric performance of Gaofen-3 satellite SAR imagery and analyzed the main factors that mostly influence the coherence and quality of interferograms. Our results proved that the long perpendicular baselines decrease the coherence seriously over the study area, and the artifacts induced by inaccurate orbit information reduce the quality of the Gaofen-3 interferograms. Refining and removing the two main artifacts could improve the quality of interferograms formed by Gaofen-3 SAR images.

SAR Coherence in Detecting Fluvial Sediment Transport Events in Arid Environments

Coherence change detection (CCD) is a remote sensing technique used to map phenomena that, under certain conditions, can be directly related to changes in Interferometric SAR (InSAR) coherence. Mapping the areas affected by sediment transport events in arid environments is one of the most common applications of CCD. However, the reliability of these maps remains an unsolved issue. This paper focuses on verifying that InSAR coherence is indeed able to detect all the fluvial sediment transport events that have actually mobilised sediments in arid environments by building a classification model and validating its results. The proposed methodology is tested in three study areas in Salar de Atacama, Chile, using three years of Sentinel data plus a fourth year for validation, and meteorological records of rainfall, the relative humidity of the air and snow cover. The results prove that InSAR coherence can be used to remotely detect sediment transport events related to flash floods in arid environments, that it might have a greater detection ability than meteorological records and that the perpendicular baseline does have a relevant effect on the InSAR coherence that needs to be considered. All these findings will increase the reliability of maps based on InSAR coherence. In addition, the proposed method will allow focusing the mapping tasks only on the relevant dates and, once calibrated, the classification model will enable the automatised remote detection of new events.

Revising digital elevation models generation from Sentinel-1 synthetic aperture radar and interferometric technique in densely-vegetated humid tropical environment

Generation of digital elevation models (DEM) over densely vegetated humid tropics using Sentinel-1 data and Interferometry synthetic aperture radar (InSAR) technique is revised based on recommended optimum perpendicular baselines, and accuracy assessment based on coherence cells is introduced. Six pairs of Sentinel-1 data within the optimum perpendicular baseline of 150 − 400 m and different temporal baselines acquired between 2015 and 2021 were processed using Sentinel Application Platform. Results revealed: that due to the extreme difficulty of achieving good coherence, interferograms are characterized by noise, generated DEMs are dominated by artefacts, higher elevation accuracy can be achieved within coherence cells, and within the recommended optimum perpendicular baseline range, elevation accuracy within coherence cells is mainly determined by the perpendicular baseline compared to temporal baseline. Therefore, this study can provide practical guide for InSAR generated DEMs evaluation in densely vegetated environments, and remote sensing method for regional-scale measurement and mapping of spots heights.

Route Plans for UAV Aerial Surveys according to Different DEMs in Complex Mountainous Surroundings: A Case Study in the Zheduoshan Mountains, China

Accurate and error-free digital elevation model (DEM) data are a basic guarantee for the safe flight of unmanned aerial vehicles (UAVs) during surveys in the wild, especially in moun-tainous areas with large topographic undulations. Existing free and open-source DEM data gen-erally cover large areas, with relatively high spatial resolutions (~90, 30, and even 12.5 m), but they do not have the advantage of timeliness and cannot accurately reflect current and up-to-date topographical information in the survey area. UAV pre-scanning missions can provide highly accurate and recent terrain data as a reference for UAV route planning and ensure security for subsequent aerial survey missions; however, they are time consuming. In addition, being limited to the electric charge of the UAV, pre-scanning increases the human, financial, and time consumption of field missions, and it is not applicable for field aerial survey missions in reality, unless otherwise specified, especially in harsh environments. In this paper, we used interferometric synthetic aper-ture radar (InSAR) technology to process Sentinel-1a data to obtain the DEMs of the survey area, which were used for route planning, and other free and open-source DEMs were also used for flightline plans. The digital surface models (DSMs) were obtained from the structure of the UAV pre-scan mission images, applying structure for motion (SfM) technology as the elevation reference. Comparing the errors between the InSAR-derived DEMs and the four open-source DEMs based on the reference DSM to analyze the practicability of flight route planning, the results showed that among the four DEMs, the SRTM DEM with a spatial resolution of 30 m performed best, which was considered as the first reference for UAV route plans when the survey area in complex mountainous regions is covered with a poor or inoperative network. The InSAR-derived DEMs from the Sentinel-1 images have great potential value for UAV flight planning, with a large perpendicular baseline and short temporal baseline. This work quantitatively analyzed the errors among the different DEMs and provided a discussion regarding UAV flightline plans based on external DEMs. This can not only effectively reduce the manpower, materials, and time consumption of field operations, improving the efficiency of UAV survey tasks, but it also broadens the use of InSAR technology. Furthermore, with the launch of high-resolution SAR satellites, InSAR-derived DEMs with high spatial and temporal resolutions provide an optimistic and credible strategy for UAV route planning with small errors.

Monitoring Maize Growth and Calculating Plant Heights with Synthetic Aperture Radar (SAR) and Optical Satellite Images

The decrease in water resources due to climate change is expected to have a significant impact on agriculture. On the other hand, as the world population increases so does the demand for food. It is necessary to better manage environmental resources and maintain an adequate level of crop production in a world where the population is constantly increasing. Therefore, agricultural activities must be closely monitored, especially in maize fields since maize is of great importance to both humans and animals. Sentinel-1 Synthetic Aperture Radar (SAR) and Sentinel-2 optical satellite images were used to monitor maize growth in this study. Backscatter and interferometric coherence values derived from Sentinel-1 images, as well as Normalized Difference Vegetation Index (NDVI) and values related to biophysical variables (such as Leaf Area Index (LAI), Fraction of Vegetation Cover (fCover or FVC), and Canopy Water Content (CW)) derived from Sentinel-2 images were investigated. Sentinel-1 images were also used to calculate plant heights. The Interferometric SAR (InSAR) technique was applied to calculate interferometric coherence values and plant heights. For the plant height calculation, two image pairs with the largest possible perpendicular baseline were selected. Backscatter, NDVI, LAI, fCover, and CW values were low before planting, while the interferometric coherence values were generally high. Backscatter, NDVI, LAI, fCover, and CW values increased as the maize grew, while the interferometric coherence values decreased. Among all Sentinel-derived values, fCover had the best correlation with maize height until maize height exceeded 260 cm (R2 = 0.97). After harvest, a decrease in backscatter, NDVI, LAI, fCover, and CW values and an increase in interferometric coherence values were observed. NDVI, LAI, fCover, and CW values remained insensitive to tillage practices, whereas backscatter and interferometric coherence values were found to be sensitive to planting operations. In addition, backscatter values were also sensitive to irrigation operations, even when the average maize height was about 235 cm. Cloud cover and/or fog near the study area were found to affect NDVI, LAI, fCover, and CW values, while precipitation events had a significant impact on backscatter and interferometric coherence values. Furthermore, using Sentinel-1 images, the average plant height was calculated with an error of about 50 cm.

Spatiotemporal Change Detection of Coastal Wetlands Using Multi-Band SAR Coherence and Synergetic Classification

Synthetic aperture radar (SAR) signal can penetrate clouds and some vegetation canopies in all weather, and therefore, provides an important measurement tool for change detection and sustainable development of coastal wetland environments and ecosystems. However, there are a few quantitative estimations about the spatiotemporal coherence change with multi-band SAR images in complex coastal wetland ecosystems of the Yellow River Delta (YRD). In this study, C-band Sentinel-1 and L-band ALOS-2 PALSAR data were used to detect the spatiotemporal distribution and change pattern of interferometric coherence in the coastal wetlands of the YRD. The results show that the temporal baseline has a greater impact on the interferometric coherence than the perpendicular baseline, especially for short wavelength C-band SAR. Furthermore, the OTSU algorithm was proven to be able to distinguish the changing regions. The coherence mean and standard deviation values of different land cover types varied significantly in different seasons, while the minimum and maximum coherence changes occurred in February and August, respectively. In addition, considering three classical machine learning algorithms, namely naive Bayes (NB), random forest (RF), and multilayer perceptron (MLP), we proposed a method of synergetic classification with SAR coherence, backscatter intensity, and optical images for coastal wetland classification. The multilayer perceptron algorithm performs the best in synergetic classification with an overall accuracy of 98.3%, which is superior to a single data source or the other two algorithms. In this article, we provide an alternative cost-effective method for coastal wetland change detection, which contributes to more accurate dynamic land cover classification and to an understanding of the response mechanism of land features to climate change and human activities.

Spatio-temporal baseline and spatial coverage of lunar-based SAR repeat-track interferometry in single- and double-antenna configurations

ABSTRACT Spatio-temporal baseline and effective spatial coverage are key parameters for lunar-based synthetic aperture radar repeat-track interferometry (LB-SAR RTI). In the mode of lunar-based single-antenna SAR RTI (LB-SASAR RTI) Earth observation, the temporal baseline and effective spatial coverage are affected by perpendicular baseline, which depends mainly on the lunar revolution. However, the moon is a nature celestial body; multiple SAR antennas can be installed on its surface to increase the potential in Earth observation. In this study, we first designed the observation geometry of lunar-based double-antenna SAR RTI (LB-DASAR RTI) and calculate its spatio-temporal baselines and effective spatial coverage. Comparing with those of the single-antenna mode, the results show that: 1) the perpendicular baselines of LB-DASAR RTI are 0–3000 km shorter than those of LB-SASAR RTI during a year, and approximate 98% of them are between 2000 and 3000 km; 2) the amount of interferometric combinations increase by about 23.5%; 3) the amount of interferometric combinations with large swath width (4400 km) is approximately doubled, resulting in an increase of 12.3% in the percentage of large swath width (4400 km); 4) the observation duration in azimuth is increased by at least 2–3 hours, equivalent to 30° to 45° of azimuthal observation range; and 5) the repeated observation frequency is higher, the most significant increase of interferometric combinations is at 40° north and south latitudes, reaching up to 286 times a year. The study is helpful for the observation mode design of LB-SAR RTI and the implementation of observation data acquisition plan.

Extraction of Absolute Water Level Using TanDEM-X Bistatic Observations With a Large Perpendicular Baseline

The application of Wetland synthetic aperture radar interferometry (InSAR) has often been restricted in practical hydrological monitoring because it is based on relative estimates of water level changes between two synthetic aperture radar acquisitions, as opposed to absolute water levels obtained by ground measurements. TanDEM-X bistatic observations can provide absolute water level estimates using simultaneous phase measurements by a two-satellite constellation with TerraSAR-X. We evaluated two datasets of TanDEM-X bistatic observations acquired during an experimental science phase on August 26 and 31, 2015, with a very large baseline configuration to extract absolute water levels of Everglades wetland in southern Florida, USA. The perpendicular baselines are 1.43 and 1.36 km, and the ambiguities of height were calculated as 3.61 and 3.90 m in each interferometric pair, respectively. Hourly water level measurements provided by the Everglades depth estimation network (EDEN) were used to verify the estimated absolute water levels. Several stage stations located in densely vegetated areas that showed incoherence were excluded from the verification as outliers. The verification results show an excellent agreement (degree of determination > 0.95) between the InSAR derived absolute water levels and the stage station measurements. The root mean square error (RMSE) between the TanDEM-X results and stage records was 0.77 and 0.66 m, respectively. Severe volume decorrelations over the vegetated area, owing to the large perpendicular baselines, were detected, despite near zero temporal baseline of the bistatic observations. The absolute water levels can be used as excellent constraints for wetland surface flow models.

Dry Snow Parameter Retrieval With Ground-Based Single-Pass Synthetic Aperture Radar Interferometry

In this article, we investigate the potential of using single-pass InSAR model-based approaches to retrieve dry snow parameters. Two InSAR scattering models of dry snow are considered: the dense-medium random volume over ground (RVoG) model and the simple variant of the full penetration (FP) model. A quasi-crystalline approximation (QCA)-based extinction analysis confirms the negligible extinction dependence of the InSAR observables at L/C/X-band for fresh dry snow. The FP models the low-frequency (L/C/X-band) InSAR phase as a single constraint of snow depth and density, which can be supplemented by an extra observation (e.g., InSAR coherence or <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> depth/density). The single-pass InSAR models and inversion approaches were validated using X-band InSAR data collected from a tower-based three-frequency (X/Ku-low/Ku-high) fully polarimetric TomoSAR system, where a multi-frequency polarimetric InSAR analysis and ground-to-volume ratio-based snow condition analysis were conducted. We also analyzed the sensitivity and error propagation of the single-pass InSAR phase and coherence in measuring dry snow depth/density. It was found that the X-band HH-pol FP-modeled single-pass InSAR phase along with RVoG-modeled coherence or <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> depth is capable of measuring snow water equivalent (SWE) with a 23–26 mm uncertainty (13–15%) and a 20–26 mm bias (12–15%) for dry snow SWE of 0.2 m, and with an optimal perpendicular baseline on the order of a tenth of the snow depth (0.8 m) at our test site. This single-pass InSAR approach with the FP model is potentially useful and thus needs further investigation for large-scale dry snow retrieval with a wide range of snow conditions using ground-based/airborne/spaceborne low-frequency (L/C/X-band) InSAR observations.

Retrieval of digital elevation models from Sentinel-1 radar data – open applications, techniques, and limitations

AbstractWith the launch of Sentinel-1 in 2014, a new era of openly accessible spaceborne radar imagery was begun, and its potential has been demonstrated throughout all fields of applications. However, while interferometric approaches to detect surface deformations are continuously being published, only a few studies address the derivation of digital elevation models (DEMs) from Sentinel-1 data. This is mainly because of the narrow orbital tube, which was primarily designed for subsidence measurements using differential interferometry. Nonetheless, the technical conditions are provided for successful applications involving DEM generation. These are outlined in the first part of this article with a focus on potential error sources and the impact of the most important constraints, namely, temporal and perpendicular baselines. The second part evaluates 21 studies on this topic, their aims, and how they dealt with error sources and the necessity of validation. These studies are then discussed based on the main challenges and potentials including how these can be tackled in the future to lay a solid foundation for scientific discourse.

Riparian Wetland Mapping and Inundation Monitoring Using Amplitude and Bistatic Coherence Data From the TanDEM-X Mission

This article focuses on bistatic coherence as an additional feature complementing amplitudes in classification space, permitting to monitor temporal changes in water extent on the wetland comprising surface water and inundated vegetation. The research was conducted on a herbaceous wetland. The TanDEM-X images were acquired during the science phase in bistatic mode with long perpendicular baselines. Two different sets of observations were computed: polarimetric amplitudes (PAs) and interferometric coherences in single-pass mode. Next, the datasets composed of a multitemporal stack of images were classified using object-based image analysis. The main outcome of the experiment is that bistatic coherences increased greatly the overall accuracy (OA) of expected thematic classes. The OA shows that thematic categories were classified with higher accuracy when the bistatic coherence complemented PAs. The OA is greater than 85% for all analyzed datatakes. The accuracy achieved using amplitudes only was higher than 70% but varied overtime. The bistatic coherence at X-band turned out to be really helpful in mapping high vegetation, which can be an indicator that this methodology can be directly used in the monitoring of common reed mowing or mapping highly invasive vegetation. Additionally, we could observe that short inundated vegetation was also mapped correctly, allowing flooded areas in this floodplain to be mapped with great precision throughout the growing season.

A Multi-Sensor Comparative Analysis on the Suitability of Generated DEM from Sentinel-1 SAR Interferometry Using Statistical and Hydrological Models

Digital elevation model (DEM) plays a vital role in hydrological modelling and environmental studies. Many essential layers can be extracted from this land surface information, including slope, aspect, rivers, and curvature. Therefore, DEM quality and accuracy will affect the extracted features and the whole process of modeling. Despite freely available DEMs from various sources, many researchers generate this information for their areas from various observations. Sentinal-1 synthetic aperture radar (SAR) images are among the best Earth observations for DEM generation thanks to their availabilities, high-resolution, and C-band sensitivity to surface structure. This paper presents a comparative study, from a hydrological point of view, on the quality and reliability of the DEMs generated from Sentinel-1 data and DEMs from other sources such as AIRSAR, ALOS-PALSAR, TanDEM-X, and SRTM. To this end, pair of Sentinel-1 data were acquired and processed using the SAR interferometry technique to produce a DEM for two different study areas of a part of the Cameron Highlands, Pahang, Malaysia, a part of Sanandaj, Iran. Based on the estimated linear regression and standard errors, generating DEM from Sentinel-1 did not yield promising results. The river streams for all DEMs were extracted using geospatial analysis tool in a geographic information system (GIS) environment. The results indicated that because of the higher spatial resolution (compared to SRTM and TanDEM-X), more stream orders were delineated from AIRSAR and Sentinel-1 DEMs. Due to the shorter perpendicular baseline, the phase decorrelation in the created DEM resulted in a lot of noise. At the same time, results from ground control points (GCPs) showed that the created DEM from Sentinel-1 is not promising. Therefore, other DEMs’ performance, such as 90-meters’ TanDEM-X and 30-meters’ SRTM, are better than Sentinel-1 DEM (with a better spatial resolution).

Monitoring active open-pit mine stability in the Rhenish coalfields of Germany using a coherence-based SBAS method

With the recent progress in synthetic aperture radar (SAR) technology, especially the new generation of SAR satellites (Sentinel-1 and TerraSAR-X), our ability to assess slope stability in open-pit mines has significantly improved. The main objective of this work is to map ground displacement and slope instability over three open-pit mines, namely, Hambach, Garzweiler and Inden, in the Rhenish coalfields of Germany to provide long-term monitoring solutions for open-pit mining operations and their surroundings. Three SAR datasets, including Sentinel-1A data in ascending and descending orbits and TerraSAR-X data in a descending orbit, were processed by a modified small baseline subset (SBAS) algorithm, called coherence-based SBAS, to retrieve ground displacement related to the three open-pit mines and their surroundings. Despite the continuously changing topography over these active open-pit mines, the small perpendicular baselines of both Sentinel-1A and TerraSAR-X data were not affected by DEM errors and hence could yield accurate estimates of surface displacement. Significant land subsidence was observed over reclaimed areas, with rates exceeding 500 mm/yr, 380 mm/yr, and 310 mm/yr for the Hambach, Garzweiler and Inden mine, respectively. The compaction process of waste materials is the main contributor to land subsidence. Land uplift was found over the areas near the active working parts of the mines, which was probably due to excavation activities. Horizontal displacement retrieved from the combination of ascending and descending data was analysed, revealing an eastward movement with a maximum rate of ∼120 mm/yr on the western flank and a westward movement with a maximum rate of ∼ 60 mm/yr on the eastern flank of the pit. Former open-pit mines Fortuna-Garsdorf and Berghein in the eastern part of Rhenish coalfields, already reclaimed for agriculture, also show subsidence, at locations reaching 150 mm/yr. The interferometric results were compared, whenever possible, with groundwater information to analyse the possible reasons for ground deformation over the mines and their surroundings.

CORRELATION ANALYSIS FOR TROPICAL FOREST ABOVE GROUND BIOMASS AND VERTICAL REFLECTIVITY PROFILE

Abstract. Tropical forests play a key role in the carbon cycle and sustainable development and their above ground biomass (AGB) is applied as an quantitative parameter for the research on global carbon cycle and ecological function. Ten-baseline Polarimetric Synthetic Aperture Radar Interferometry (PolInSAR) images collected in Mondah, Gabon 4th Feb. 2016 during AfriSAR campaign are applied to extract the vertical scattering coefficient with SAR tomography (TomoSAR). Capon is used to reconstruct the vertical reflectivity profile and then the correlation analysis between backscattering coefficients at special height and the in-situ F-AGB is carried out. The results show that Capon performs well when the perpendicular baseline interval is similar and the vertical reflectivity relates closely with the F-AGB in plot scale.

Application of Time Series InSAR (SBAS) Method using Sentinel-1A Data for Land Subsidence Detection in Surabaya City

We studied land subsidence occurrence in Surabaya, considering the rapid urban growth in the city. It is evidenced by the increasing number of buildings (e.g., houses, apartments, offices) that have been realized before 2015 and the increasing transport activities in the industrial area. Land subsidence is a vertical deformation on the land surface that can be caused by landslides, earthquakes, soil consolidation process, or even human-made activities, depending on the material characteristics of the area. In this study, Time-series InSAR (TS-InSAR), specifically the Small Baseline Subset (SBAS) method, is applied to obtain the Line-of-Sight (LOS) velocities and time-series LOS displacements in Surabaya between May 2015 and September 2017. We used 28 Sentinel-1A data (IW mode) acquired by using Terrain Observation with Progressive Scan (TOPS) operation with the spatial resolution of 5 ´ 20 m and covers the area of 250 km2. DEM SRTM with 30 m spatial resolution was used to reduce topography effect contribution in the interferograms. Based on the SBAS method, interferogram pair selection is applied with the maximum value of 150 m for the perpendicular baseline and 100 days for the temporal baseline. The DInSAR process successfully generated seventy-four (74) interferogram pairs, and then by using SBAS algorithm, the LOS velocity and time-series LOS displacement were estimated. The results showed the varying displacements respond with the significant subsidence occurred in the North, East, and Southeast part of Surabaya. The SBAS result confirmed that the LOS velocity over the Surabaya area between May 2015 and September 2017 ranges from -40 to +30 mm/year. Significant land subsidence occurred in the Asemrowo area (North Surabaya) with the value of LOS displacement velocity up to -45 mm/yr.

Modeling the Optimal Baseline for a Spaceborne Bistatic SAR System to Generate DEMs

Interferometric synthetic aperture radar (InSAR) is one of the best methods for obtaining digital elevation models (DEMs). However, the problem of the uncertainty of DEM accuracy affected by the perpendicular baseline still persists, which should be as long as possible to ensure the sensitivity of the phase to the height measurement, and as small as possible to ensure a high spatial coherence. Moreover, the baseline configuration design of bistatic SAR system lacks a more detailed model for reference to generate high-precision DEM. Therefore, in this paper, the optimal baseline is modeled to maximize the accuracy of height measurement. First, we analyze the influence of system parameters on the height measurement accuracy, and a propagation model from the parameter estimation error to the elevation error is derived. Then, the phase unwrapping error (PUE) that considers the spatial baseline coherence, terrain slope and phase unwrapping effectiveness is modeled and analyzed after interferometric phase simulation and adaptive unscented Kalman filter phase unwrapping. Combining the relationship between the height error and the PUE, the optimal baseline model is obtained by statistical analysis. Finally, weighted averages are used to calculate the average slope of the complex terrain and the validity and reliability of the proposed optimal baseline model are verified by two examples of complex terrains with uniformly and nonuniformly distributed positive and negative slope angles. Moreover, the optimal baseline ranges of different terrain types are also derived for reference.