Multitemporal interferometric synthetic aperture radar (InSAR) technology has become an important tool for digital elevation model (DEM) generation and surface deformation monitoring. The prerequisite is to obtain the correct unwrapped phase of the interferograms. However, it is still challenging to obtain reliable results by traditional 2-D phase unwrapping (PU) algorithms and even 3-D PU algorithms, when the phase continuity assumption fails due to large deformation gradients or abrupt topographic changes. This letter proposes an${L}^{ {1}}$-norm sparse 2-D PU algorithm based on reliable redundant network in the phase discontinuous region, which is obtained by implementing ambiguity detector on free network within a given distance. Experiment on real synthetic aperture radar (SAR) interferograms covering urban tall buildings verified that the algorithm can obtain more reliable results in phase discontinuous regions than traditional PU algorithms.

Nighttime light (NTL) radiance can reflect human settlements and activities. A lot of studies indicate that NTL brightness can be a sound proxy of socioeconomic factors on large scales, such as the population size, gross domestic product, electric power consumption, etc. However, few studies have been dedicated to these topics on fine scales. In this study, we examined the correlation between the Suomi National Polar-orbiting Partnership-Visible Infrared Imaging Radiometer Suite (S-NPP/VIIRS) NTL intensity (NLI) and population density, as well that between NLI and per capita income at two census units’ levels, census tract and block group, in two research areas. The result shows that the NLI has a moderate or weak positive correlation with the population density at both scales. However, when land use type is integrated with population density, the correlation becomes very strong. The NLI and per capita income have a weak or very weak negative correlation at both scales. Moreover, we find that the correlation coefficient is positively correlated with the unit’s size. The larger scale also has a higher correlation coefficient. The research conducted here could be beneficial for the application of S-NPP/VIIRS NTL data in studying socioeconomic activities in human settlement areas.

Digital elevation models (DEMs) are vital in the geosciences and many other fields. Interferometric synthetic aperture radar (InSAR), an advanced earth observation technology, has shown its potential in DEM reconstruction. Multi baseline InSAR (MB-InSAR) is currently improving the precision of DEM reconstruction by combining multiple interferograms. However, MB-InSAR for DEM generation can result in severe decorrelation, which may cause significant gaps in the final DEM product. To solve this problem, an improved MB-InSAR DEM reconstruction method is proposed in this study, which we term as the dynamic DEM calculation algorithm. The proposed method can estimate the DEM pixel-by-pixel, which allowed us to select the interferograms dynamically and therefore minimize the void values. For the performance test of the proposed method, 25 ascending and 20 descending TerraSAR-X images over Heifangtai (China) were collected to form repeat-pass interferograms and produce the DEM using the proposed method. Results showed that the number of valid pixels increased by approximately 20% compared with the traditional MB-InSAR DEM reconstruction method without loss of precision, thereby illustrating the feasibility of the proposed method.

Remotely sensed nighttime light (NTL) data provides an opportunity to observe human economic activities at night. However, existing NTL remote sensing data does not sufficiently reflect human activities at a fine resolution. In this study, we obtain a set of NTL data comprising volunteered passenger aircraft nighttime remote sensing (VPAN-RS) imagery by adopting a passenger plane as the remote sensing platform and using low-cost portable photography equipment as sensors. This method demonstrates the advantages of VPAN-RS data in high spatial resolution, frequent revisits, and low cost, which can supplement existing NTL data. The dataset acquired in this study covers 16 cities in China and one city in Japan, with a spatial resolution up to meter level. The data acquisition method and processing workflow are introduced in this article. Quality assessment shows that the reprojection error of the dataset falls within the range from 5–10 pixels, and the geometric error can be within 15 m. Via a comparison to reference data derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor of the Suomi-National Polar-Orbiting Partnership (NPP) polar-orbiting satellite, we found that the VPAN-RS data provides more details of city lighting. Additionally, the radiance of the VPAN-RS data suitably fits that of monthly composite NPP/VIIRS data. We further outline an application example of VPAN-RS nighttime imagery, examine the unique challenges associated with VPAN-RS data with a focus on the influence of the image acquisition method on the data quality, and provide an outlook for the future of VPAN-RS data. We conclude that VPAN-RS NTL images are an effective data source for nighttime earth observations and have the potential for various applications.

The proper use of distributed scatterer (DS) can improve both the density and quality of synthetic aperture radar (SAR) interferometry (InSAR) measurements. A critical step in DS interferometry (DSI) is the restoration of a consistent phase series from SAR interferogram stacks. Most state-of-the-art algorithms adopt an approximate likelihood function to calculate the likelihood by replacing the true coherence matrix with its estimation, more specifically, the sample coherence matrix (SCM). However, this approximation has a drawback in that the coherence estimates are greatly biased when the coherence is low. In this study, we derive a new likelihood function without such an approximation. Accordingly, a DSI framework using this function for phase estimation and point selection is provided. In this framework, the new likelihood function serves as a cost function for phase estimation and a quality measure for DS selection. Its performance is investigated by experiments in a simulation study and a real-world case study using Sentinel-1 data over Shenzhen airport in China. The results reveal that the proposed DSI framework outperforms the existing state-of-the-art approaches in different scenarios, in terms of providing a more accurate estimation and improving DS density and coverage.

The synthetic aperture radar (SAR) interferometry (InSAR) has been developed for more than 20 years for historical surface deformation reconstruction. In particular, the onboard Sentinel-1/A/B satellite, newly planned NASA-ISRO SAR (NISAR), and Germany Tandem-L will continue to provide unprecedented SAR data with an increased number of acquisitions. However, processing of real-time SAR data has been experiencing challenges regarding the InSAR deformation parameter estimation over a long time with the small baseline subsets (SBAS) InSAR technology. We use sequential adjustment for the estimation of the deformation parameters, which uses Bayesian estimation theory under the least square criteria to inverse long time-series deformation dynamically. Finally, both simulated and real Sentinel-1A SAR data verify the performance of the sequential estimation. It can be regarded as an effective data processing tool in the coming era of SAR big data.

Multi-source Synthetic Aperture Radar (SAR) datasets are used to investigate the deformation history and failure mechanism of small-scale loess landslide in the Heifangtai loess terrace, Gansu province, China. A total of 65 SAR datasets acquired by L-band ascending ALOS/PALSAR, X-band descending TerraSAR-X and C-band descending Sentinel-1A/B covering the different periods of Heifangtai terrace are fully exploited. In addition, groundwater level data are also involved to analyze the failure mechanism of loess landslide. The displacements occurred during the past eleven years were quantitatively identified for firstly by InSAR technique. The results show that three slopes, failed on October 1, 2017 had large cumulative deformations from January 2016 to November 2016. The acceleration dates of the deformation for the three slopes were successfully captured by Sentinel-1A/B data. Furthermore, the result shows that the magnitude of the landslide deformation is closely correlated to the groundwater level variation.

Aiming to mitigate the landslide hazard after event and to investigate the potential landslide over large area, the three-step landslide investigation strategy based on Synthetic Aperture Radar Interferometry (InSAR) is proposed, which includes (1) fast landslide mapping is calculated with small volume SAR data over specific landslide region on demand. (2) Pre-landslide deformation are precisely recovered with all archived SAR data to analyze the spatiotemporal landslide characteristics. (3) The potential landslides are fully investigated in the catchment scale with large volume SAR data. Sentinel-1A SAR data are continuously involved to give fast landslide monitoring and investigation over Baige landside and Jinsha River catchment.

The Linfen-Yuncheng Basin (LYB) is one of the most serious geo-hazards regions in China, which have been experiencing severe geo-tectonic movement, seismic, land subsidence and ground fissures. To monitor the complex surface deformation at LYB, Interferometric Synthetic Aperture Radar (InSAR) is employed. Forty-nine scenes acquired from three SAR tracks from 2007 to 2011 are used to obtain the ground deformation over LYB based on four multi-temporal InSAR analysis methods (i.e. PI-RATE, Stacking, SBAS and TCP). The maximum displacement is observed in Jishan County with the subsidence rate up to 120 mm/yr in the vertical direction. Two visually triangular areas are recognized at Jishan and Taocun-Xiaxian, which are controlled by local normal faults. In addition, cross-validation of the results in overlapping areas between adjacent tracks, ascending and descending tracks are conducted, which show good consistency among four methods.

Taiyuan graben basin has been suffering serious ground deformation due to the combined effects of groundwater pumping, ground fissures and faults. However, most ground deformation monitoring mainly focus on the single city, thus it is difficult to reveal the regional extent of the deformation. Fifty-five ALOS/PALSAR images acquired from three adjacent tracks from 2007 to 2011 are used to obtain annual deformation rate based on Small Baseline Subsets (SBAS-InSAR) technique. The standard deviations of deformation differences between two adjacent tracks are 3.7mm/a and 4.2mm/a, respectively. Large subsidence funnels mainly occur in the regions, where the groundwater pumping is intensive. The maximum subsidence is observed in Qingxu with the land subsidence rate up to 240mm/a, while regions with subsidence rates ranging from 50 to 90mm/a are detected in other locations. Meanwhile, significant deformation differences are retrieved in both sides of the faults, which could be explained as the faults-controlled deformation.

Underground mining induced displacements in most areas of China amount to meter-level while with small spatial coverage, spatially discontinuous and temporally nonlinear features. Traditional phase-based InSAR methods can hardly obtain large deformation in the center of land subsidence area due to the phase noise, maximum monitoring ability. This paper systematically studies the offset tracking technique based on SAR image intensity maps with and without pre-installed Corner Reflectors (CRs).The results of this experiment indicate that the high resolution SAR data with the aid of pre-installed CR points can better solve the large gradient deformation monitoring problem. In addition, offset tracking method has the potential to achieve two-dimensional deformation field along the line-of-sight and along the azimuth directions, which can provide more detailed information regarding mining induced deformation, which is complimentary to the traditional phase-based and intensity-based techniques.

InSAR has been widely used in monitoring land subsidence over large area. However, many factors in InSAR processing, such as decorrelation error, atmosphere error, height error and thermal noise limit the accuracy of InSAR measurements. The height error over urban area is particularly the most difficult issue in TerraSAR-X data processing for its shorter wavelength and higher spatial resolution. We employed a Multi-temporal InSAR (MTI) method based on the PS and SBAS method proposed by Hopper to estimate height of urban building and ground deformation simultaneously. By means of MTI method, the first raw urban DSM with 1,500 km2areas over urban area has been mapped with a height accuracy of about 5 m. The MTI-derived deformation shows that the established TerraSAR DSM reduced the height error influence on deformation phase effectively. GPS and leveling measurements are applied to calibrate the InSAR results. Precision of our InSAR annual subsidence can reach 6 mm.

Taiyuan Basin is one of the regions with complex geological structure and frequent seismic activities in China. Because of groundwater exploitation and tectonic activity, land subsidence has occurred widely in this region. For disaster prevention and mitigation, obtaining ground deformation characteristics within the basin is an urgent requirement. The Interferometric Synthetic Aperture Radar (InSAR) was used for mapping the ground deformation in this area. The ground deformation characteristics over Taiyuan Basin from 2007 to 2011 were obtained and the cross-correlation between the regional ground subsidence and fault activity were analyzed.

Three InSAR products and DEM data are involved to detect the potential landslides over Wudongde Hydropower Station Section, Jinsha River. More than ten known and unknown landslides are successfully detected. Meanwhile, Small Baseline Subsets (SBAS) InSAR technique is applied to calculate the time-series deformation of the Jinpingzi landslide. Then, in-situ georobot measurements are used for point-wise comparison. The precision in slide direction is 1.8 cm by comparing with in-situ georobot measurements. At last, the Erpingcun landslide is taken as an example to calculate the vertical and horizontal deformation components by fusing the ascending and descending line-of-sight results.