The Geostationary Environment Monitoring Spectrometer (GEMS), launched in February 2020, performs hourly measurements of earthshine radiances to retrieve column amounts of air pollutants over Asia. However, the charge-coupled device detector of GEMS has bad pixels that exhibit abnormal radiometric responses, which translates to a decrease in the quality of radiance measurements. Permanent bad pixels result in an information gap in the aerosol product at ~14.4–16.1°N latitudes (e.g., in Manila, the Philippines, and Mainland Southeast Asia), which cannot be filled even with long-term observations owing to the structure of the East-West scanning mechanism of GEMS. Here, we propose a robust method to reconstruct radiances measured inaccurately by the bad pixels, based on spectral correlation induced mainly by the Fraunhofer line structures. The reconstruction aims at the bad pixels in the wavelength range of ~485–491 nm, which affects aerosol retrieval. We estimate that uncertainties in the reconstructed optical depths are ~2 orders of magnitude smaller than typical aerosol optical depths. Our results convincingly demonstrate that the reconstructed radiances effectively restore the physical distributions of visible aerosol indices, improving the determination of aerosol types. Furthermore, the reconstructed radiances enhance retrievals of aerosol layer height (ALH), holding particular significance for the long-term accumulation of ALH data over Southeast Asia using GEMS.

North Korea conducted the sixth nuclear test in Punggye-ri on 3 September 2017. An artificial earthquake of Mw 6.3 was reported near North Korea's Punggye-ri nuclear test site. Several minutes later, a second smaller earthquake followed the initial event, and it was characterized as a collapse of the cavity. The large and complex deformations related to the earthquakes occurred in the ground surface. It is very important to measure the artificial earthquake-related deformations, because it enables us to estimate the location, depth and cavity radius of the nuclear test. We observed the three-dimensional surface deformations related to the sixth North Korea nuclear test using the ascending and descending ALOS-2 PALSAR-2 radar offset-tracking. We used the multi-kernel offset tracking method to improve the precision of the offset-tracking measurement. The maximum deformation of more than 3 m was observed in the horizontal direction. We estimated the location, depth and cavity radius using the Mogi model. The estimated depth and cavity radius are about 600 m and about 52 m, respectively. The satellite offset-tracking observation will contribute to the nuclear test monitoring and characterization.

Monitoring of mountain glaciers using SAR interferometry is challenging, yet it is necessary to improve our understanding of glacier dynamics in a changing climate, by estimating their precise movements. Although there are significant difficulties of spatial and temporal decorrelation for observing mountain glaciers, multiple aperture interferometry (MAI) can be a promising solution compared to other existing methods. In this study, we will present temporal variations of Himalayan glaciers' behavior focusing on the velocity estimation and glacier outline mapping. These results will be provided for estimating the rate of glacier melt, and in turn play an important role in better understanding the hydrology and climate change in the Himalayan region.

Measurement of precise three-dimensional surface displacements is really helpful to understand Earth's internal processes. In this point of view, many researches have been performed to retrieve three-dimensional surface displacements using three or more surface displacements maps from SAR, which represent different geometries respectively [1-6]. SAR interferometry, Multiple-aperture SAR interferometry or Offset tracking have been selectively employed to restore three-dimensional surface displacements occurring by earthquakes, volcanisms, glaciers or land subsidence [7-14]. However the limitations are still remain. SAR interferometry is difficult to measure large surface displacements. Although offset tracking is appropriate to measure large surface displacements, generally produce the surface displacements map of worse measurement precision than SAR interferometry [1]. Meanwhile, recent developments in SAR sensor and improvements in offset tracking have made it possible to complement each of these limitations [9]. In this study, we precisely measured the large surface displacements by employing the integration of SAR Interferometry and Offset tracking methods. Figure 1 show the shaded relief map for Kumamoto, Japan. Three interferometric pairs, which cover surface displacements occurring by the 2016 Kumamoto Earthquakes, were collected from ascending and descending paths of L-band ALOS PALSAR-2 datasets (asc1: 20151115_20160616; asc2: 20160211_20160602; dsc: 20160307_20160419) (Fig. 1). When the offset tracking map and integrated LOS displacements map are compared, integrated LOS map could observe surface displacements without unwrapping error, even in the decorrelated region of SAR interferometry because of the large surface displacements [15]. It enable us to extract the three-dimensional displacements without unmeasured area. Figure 2 shows three-dimensional surface-deformation field for the 2016 Kumamoto Earthquakes. The maximal surface displacements for east-west, north-south and up-down direction were -1.91, -1.57 and -2.49 m respectively. The root mean square errors of 1.76, 1.41 and 1.85 cm in the east, north and up directions, respectively, were estimated by comparing with the GPS measurements [16]. These results suggest that the integration method can be help to map the three-dimensional surface displacements even near the fault lines, which was impossible to observe by conventional SAR interferometry. Since it can be applied not only to earthquakes but also to large surface displacements of various factors, the observation method of this study will be produce more beneficial data to understand the Earth's internal processes.

Bias compensation of rational polynomial coefficients (RPCs) is one of the most important preprocessing steps in high-resolution satellite image processing. It generally requires accurate ground control points (GCPs), but GCP acquisition is both time consuming and laborious. In this paper, we propose a time- and cost-efficient method for automated bias compensation of the RPC of high-resolution stereo image pairs. Two Korean Multi-purpose Satellite-2 (KOMPSAT-2) stereo image pairs acquired in Daejeon and Busan, Korea, and the Shuttle Radar Topographic Mission (SRTM) digital elevation model (DEM) with the spatial resolution of 3 arcsec (~90 m) were used for analysis. In the two study areas, 33 and 29 check points were respectively used for the performance evaluation. After bias compensation with the proposed method, the root-mean-square (RMS) errors for both of the study areas were less than 10 m, in all coordinate components, while the RMS error vectors were approximately 10 m. Although the RMS error vectors were slightly larger than the standard deviations of the residual errors of the initial ground coordinates, it would seem that they yielded acceptable values because the proposed method largely depends on the spatial resolution, the error of the SRTM DEM, the tie point selection error, and so on. Therefore, it can be concluded that the proposed method allows for the automated bias compensation of RPCs of KOMPSAT-2 images.

Despite several studies using the multiple-aperture interferometry (MAI) technique, X-band SAR has rarely been applied to MAI-based studies due to their shorter decorrelation timescale. However, the relatively short antenna length and high temporal resolution of the COSMO-SkyMed X-band SAR system provides an opportunity to measure the precise displacement in the along-track direction. In this study, we have assessed the MAI performance in comparison with GPS and established an empirical uncertainty model of MAI measurements with respect to interferometric coherence. It enables us to confirm the difference between theoretical and practical uncertainties of the MAI method. Moreover, this study will be helpful for evaluating the reliability of MAI measurements where GPS data are unavailable.

Recently a multiple-aperture interferometry (MAI)-based azimuth shift method has been proposed to correct the ionospheric phase on synthetic aperture radar (SAR) interferograms. This method needs to determine integral constants required for azimuth integration. The exact estimation of the integral constants plays a key role in this MAI-based method. In this paper, we propose an efficient method for improving the performance of integral constant estimation, which functions by simultaneously removing the ionospheric and orbital phase artifacts from the interferometric SAR interferogram. We validate the performance improvement of the proposed method using two Advanced Land Observation Satellite Phase Array L-band SAR (ALOS PALSAR) interferometric pairs. The proposed method is compared with a MAI-based method, which does not work well due to azimuth integration errors. The proposed method successfully corrects the ionospheric and orbital phase artifacts. In addition, we compare the performances of the previous and proposed methods using the in situ Global Positioning System velocities. The root-mean-square error (RMSE) in line-of sight velocity from the previous method is about 7.0 mm/yr, whereas the RMSE from the proposed method is about 4.3 mm/yr. An RMSE reduction of about 38.6% is achieved when using the proposed method. These results indicate: 1) that the proposed method successfully estimates and corrects the ionosphere and orbital phase distortions; and 2) that the proposed method is superior to the previous method.

The SuperSAR imaging system, a novel multi-azimuth synthetic aperture radar (SAR) system capable of detecting Earth surface deformation in three dimensions from a single satellite platform, has recently been proposed. In this paper, we investigate the feasibility of detecting precise 3-D surface displacement measurements with the SuperSAR imaging system using a point target simulation. From this simulation, we establish both a relationship between the interferometric SAR phase and the across-track displacement and a relationship between the multiple-aperture interferometry phase and the along-track displacement based on the SuperSAR imaging geometry. The theoretical uncertainties of the SuperSAR measurement are analyzed in the across- and along-track directions, and the theoretical accuracy of the 3-D displacement measurement from the SuperSAR system is also investigated according to both the decorrelation and the squint and look angles. In the case that the interferometric coherence is about 0.8 and that five effective looks are employed, the theoretical 2-D measurement precision values are about 3.67 and 6.35 mm in the across- and along-track directions, respectively, and the theoretical 3-D measurement precision values for 3-D displacement are about 4.05, 4.56, and 3.45 mm in the east, north, and up directions, respectively. The result of this study demonstrates that the SuperSAR imaging system is capable of measuring the 3-D surface displacement in all directions with subcentimeter precision.

We construct a 3-D surface displacement map for the March 5-9, 2011 Kamoamoa fissure eruption at Kilauea Volcano, Hawai'i, by integration of multitemporal InSAR and multiple aperture interferometry (MAI) measurements from the COSMO-SkyMed SAR system. It was the first attempt to measure along-track displacements by X-band data. In spite of the potential risk of decorrelation by their short-wavelength signal, the high temporal resolution of COSMO-SkyMed provides the opportunity to map the precise 3-D displacement maps effectively. To assess the measurement accuracies of the untested data, a comparison with GPS data has been carried out for multi-stacked MAI interferogram and the 3-D components of surface deformation. Root-mean-square errors of 0.99, 0.80, and 0.65 cm for the east, north, and up components, respectively, support the suitability and effectiveness of COSMO-SkyMed for the 3-D observation.

Orbital errors, characterized typically as longwavelength artifacts, commonly exist in interferometric synthetic aperture radar (InSAR) imagery as a result of inaccurate determination of the sensor state vector. Orbital errors degrade the precision of multitemporal InSAR products (i.e., ground deformation). Although research on orbital error reduction has been ongoing for nearly two decades and several algorithms for reducing the effect of the errors are already in existence, the errors cannot always be corrected efficiently and reliably. We propose a novel model that is able to jointly estimate deformation rates and orbital errors based on the different spatial-temporal characteristics of the two types of signals. The proposed model is able to isolate a long-wavelength ground motion signal from the orbital error even when the two types of signals exhibit similar spatial patterns. The proposed algorithm is efficient and requires no ground control points. In addition, the method is built upon wrapped phases of interferograms, eliminating the need of phase unwrapping. The performance of the proposed model is validated using both simulated and real data sets. The demo codes of the proposed model are also provided for reference.

The accuracy of L-band synthetic aperture radar (SAR) differential interferometry (InSAR) on crustal deformation studies is largely compromised by ionosphere path delays on the radar signals. The ionosphere effects cause severe ionospheric distortion such as azimuth streaking and long wavelength phase distortion similar to orbital ramp error. Effective detection and correction of ionospheric phase distortion from L-band InSAR images are necessary to measure and accurately interpret surface displacement. In this paper, we investigate the performance improvement of L-band InSAR interseismic deformation measurements in southern California through the joint correction of both ionosphere noise and orbital error. Our results show that this method can effectively remove orbit and ionosphere phase distortions. In comparison with in situ GPS measurements, the achieved InSAR measurement accuracy is improved from ~ 30 mm to ~ 10 mm by the proposed joint correction method. We show that, after the joint correction, the remaining atmosphere noise can be further mitigated through stacking, leading to an RMS error of ~ 4.7 mm/year in resultant line-of-sight velocity, as compared with ~ 11.3 mm/year before the correction. Our results demonstrate that the proposed joint correction technique provides a promising way to jointly correct orbital and ionospheric artifacts in L-band InSAR studies of crustal deformation.

Melt pond statistics (size and shape) have previously been retrieved from aerial photography and high-resolution visible satellite data. These submeter- or meter-resolution visible data can provide reasonably accurate information on melt ponds, but are greatly constrained by the limited solar illumination and frequent cloud cover in the Arctic region. In this study, we venture into exploring high-resolution synthetic aperture radar (SAR) or imaging radar method for melt pond mapping, which is not severely disrupted by cloud or low solar zenith angle. We analyzed high-resolution airborne SAR images (0.3-m resolution) of midsummer sea ice, acquired from a helicopter-borne SAR system in the northern Chukchi Sea. The pond area and shape (circularity) derived from the airborne SAR images showed that the statistics were comparable to those previously observed from aerial photographs. We argue that high-resolution SAR, together with one-to-one comparison with coincident aerial photographs, can be used to map melt ponds at a level of detail comparable to aerial photography or high-resolution optical satellite remote sensing. Our encouraging results suggest the possibility of using high-resolution SAR (current or future systems) to map melt ponds in the Arctic region.

The European Space Agency's Sentinel-1, a C-band imaging radar mission to be launched in mid-2013, will provide a continuity of radar data for monitoring the changing Earth. The azimuth resolution of Sentinel-1's background mode, interferometric wide-swath (IW) mode, is four times lower than that of European remote-sensing satellite (ERS) and Envisat systems. Therefore, the measurement accuracy of along-track displacement from Sentinel-1 IW images presumably will be significantly reduced. In this paper, we test the feasibility of along-track displacement measurement from Sentinel-1 IW mode. We simulate Sentinel-1 IW synthetic aperture radar (SAR) images from the ERS raw data that captured the coseismic deformation of the 1999 Hector Mine earthquake in California. Along-track displacement maps are generated using multiple-aperture interferometric SAR (MAI) and intensity tracking techniques, respectively, and are compared with GPS measurements. The root-mean-square (rms) error between the synthetic Sentinel-1 MAI and GPS measurements is about 9.6 cm, which corresponds to only 0.5 % of the azimuth resolution. The rms error between the along-track displacements from synthetic Sentinel-1 offset tracking and GPS is about 27.5 cm, which is about 1.4 % of the azimuth resolution. These results suggest that the MAI method will still be useful to measure along-track displacements from Sentinel-1 IW InSAR imagery and that it would be difficult to effectively measure the along-track displacements by the Sentinel-1 offset tracking method.

Interferometric synthetic aperture radar (InSAR) is a powerful technique that precisely measures surface deformations at a fine spatial resolution over a large area. However, the accuracy of this technique is sometimes compromised by ionospheric path delays on radar signals, particularly with L- and P-band SAR systems. To avoid ionospheric effects from being misinterpreted as ground displacement, it is necessary to detect and correct their contributions to interferograms. In this paper, we propose an efficient method for ionospheric measurement and correction and validate its theoretical and experimental performance. The proposed method exploits the linear relationship between the multiple-aperture interferometry phase and the azimuth derivative of the ionospheric phase. Theoretical analysis shows that a total electron content (TEC) accuracy of less than$1.0 \times 10^{-4}$TEC units can be achieved when more than 100 neighboring samples can be averaged (multilooked), and the coherence is 0.5. The regression analysis between the interferometric phase and the topographic height shows that the root-mean-square error can be improved by a factor of two after ionospheric correction. A 2-D Fourier spectral analysis indicates that the ionospheric wave pattern in the uncorrected power spectrum has disappeared in the power spectrum of the corrected interferogram. These results demonstrate that the proposed method can effectively remove ionospheric artifacts from an ionosphere-distorted InSAR image. Note that the method assumes that there is no appreciable surface displacement in the along-track dimension of the interferogram.

Surface deformation caused by an intrusion and small eruption during June 17-19, 2007, along the East Rift Zone of Kilauea Volcano, Hawaii, was three-dimensionally reconstructed from radar interferograms acquired by the Advanced Land Observing Satellite (ALOS) phased-array type L-band synthetic aperture radar (SAR) (PALSAR) instrument. To retrieve the 3-D surface deformation, a method that combines multiple-aperture interferometry (MAI) and conventional interferometric SAR (InSAR) techniques was applied to one ascending and one descending ALOS PALSAR interferometric pair. The maximum displacements as a result of the intrusion and eruption are about 0.8, 2, and 0.7 m in the east, north, and up components, respectively. The radar-measured 3-D surface deformation agrees with GPS data from 24 sites on the volcano, and the root-mean-square errors in the east, north, and up components of the displacement are 1.6, 3.6, and 2.1 cm, respectively. Since a horizontal deformation of more than 1 m was dominantly in the north-northwest-south-southeast direction, a significant improvement of the north-south component measurement was achieved by the inclusion of MAI measurements that can reach a standard deviation of 3.6 cm. A 3-D deformation reconstruction through the combination of conventional InSAR and MAI will allow for better modeling, and hence, a more comprehensive understanding, of the source geometry associated with volcanic, seismic, and other processes that are manifested by surface deformation.

This paper presents the categorization and restoration of defective lines developed in pushbroom images. About 100 of the 3000 SPOT 4 SWIR detectors malfunction, which degrades image quality. Conventional methods have difficulties in effectively detecting and restoring defective lines, because they ignore the heterogeneity of the ground surface and the presence of sporadically unstable detectors with gain and offset that vary during a scan. While all defective lines have previously been considered as a single type, here they are categorized into three types according to the variation pattern in the scanning direction: constant defective lines, irregular defective lines, and irrecoverable defective lines. The detection procedure utilizes summed data and standard deviation data that consist of abnormal peaks originating from defective lines and a slowly varying baseline reflecting the surface characteristics within the image. The defective lines are detected by finding abnormal peaks, and classified and restored by using either a moment-matching method or interpolation, depending upon their types. Three SPOT 4 images were used to test and evaluate the performance of the proposed method. From the test results, the constant defective line was the most common type, comprising about 60%, while the irregular defective lines caused serious image degradation because of the difficulty of detecting and classifying them. Commission and omission errors were less than 10% and detection accuracy was higher than 90%. The analysis of signal-to-noise ratio (SNR) showed that the low SNR created by the defective lines was effectively removed. Our method gave a significant improvement of the detection and restoration capability.

Multiple-aperture synthetic aperture radar (SAR) interferometry (MAI) enables the measurement of along-track surface deformations by means of split-beam SAR processing. This paper examines the effects of flat-Earth and topographic phases on the MAI phase and derives formulas to correct them. Detailed MAI processing steps are introduced and discussed with particular consideration given to coherence improvement, as well as to computational efficiency. Forward- and backward-looking MAI pairs have different perpendicular baselines, which play a key role in phase distortion; consequently, an orbital deviation of only a few centimeters could result in a significant flat-Earth phase. A second-order polynomial model was used to estimate the perpendicular baseline difference. European Remote Sensing 2 satellite SAR data sets of the Hector Mine earthquake event in 1999 were used for performance evaluation. The proposed processing with the flat-Earth and topographic phase corrections achieved precision of along-track deformation ranging from 10.2 to 13.1 cm. Two coseismic pairs were compared and the standard deviation of the difference between the two independent measurements was 7.0 cm, with a mean difference of -0.24 cm. Thus, the measurement accuracy of MAI was improved using flat-Earth correction and coherence enhancement.

Synthetic aperture radar (SAR) data have serious geometric distortions caused by inherent side looking geometry and are usually corrupted by speckle noises so that it is difficult to identify ground control points (GCPs). The location of the pixel in a given SAR image can be derived from the knowledge of sensor position and velocity. We propose a GCP extraction algorithm that has an improved capability. The algorithm is based on the geocoding process of the radar image and requires precise orbit information. Whereas conventional geolocation algorithms depend on the knowledge of the target height relative to an assumed Earth ellipsoid model, more precise positioning can be achieved if utilizing an available digital elevation model (e.g. USGS GTOPO-30 DEM, SRTM DEM, etc.). The ERS SAR data with precise Delft orbit information and the national digital elevation model (DEM) were used. We analyze the accuracy of the results from our algorithm by using digital map. In case of using SRTM DEM, the mean values of the planimetric distance error are 9.1 m and 14.7 m with standard deviations of 6.4 m and 9.3 m in northing and easting direction, respectively. The errors in northing direction depend mainly on the imaging pulse time, and those in easting direction are related to the accuracy of used digital elevation model. The GCPs extracted were used for georectification of optical images as well as SAR data.