Spaceborne interferometric synthetic aperture radar (InSAR) methodology has been widely successfully applied to measure urban surface micro slow subsidence. However, the accuracy is still limited by the spatial resolution of currently operating SAR systems and the lacking precision of geolocation of the respective scatters. In this context, high-precision urban models, as provided by the active laser point cloud methodology through light detection and ranging (LiDAR) techniques, can assist in improving the geolocation quality of InSAR-derived permanent scatters (PS) and provide the precise contour of buildings for hazard analysis. This paper proposes to integrate InSAR and LiDAR technologies for an improved detailed analysis of subsidence levels and a hazard assessment for buildings in the urban environment. By the use of LiDAR data, most building contours in the main subsidence area were extracted and SAR positioning of buildings via PS points was refined more precisely. The workflow for the proposed method includes the monitoring of land subsidence by the TS-InSAR technique, the geolocation improvement of InSAR-derived PS, and building contour extraction by LiDAR data. Furthermore, a reasonable hazard assessment system of land subsidence was developed. Significant vertical subsidence of −40 to 12 mm per year was detected by the analysis of multisensor SAR images. The land subsidence rates in the Shenzhen District obviously follow certain spatial patterns. Most stable areas are located in the middle and northeast of Shenzhen except for some areas in Houhai, the Qianhai Bay, and the Wankeyuncheng. An additional hazard assessment of land subsidence reveals that the subsidence of buildings is mainly caused by the construction of new buildings and some by underground activities. The research results of this paper can provide a useful synoptic reference for urban planning and help reducing land subsidence in Shenzhen.

The disturbances of the ionosphere caused by thunderstorms or lightning events in the troposphere have an impact on global navigation satellite system (GNSS) signals. Gravity waves (GWs) triggered by thunderstorms are one of the main factors that drive short-period Travelling Ionospheric Disturbances (TIDs). At mid-latitudes, ionospheric GWs can be detected by GNSS signals. However, at low latitudes, the multi-variability of the ionosphere leads to difficulties in identifying GWs induced by thunderstorms through GNSS data. Though disturbances of the ionosphere during low-latitude thunderstorms have been investigated, the explicit GW observation by GNSS and its propagation pattern are still unclear. In this paper, GWs with periods from 6 to 20 min are extracted from band-pass filtered GNSS carrier phase observations without cycle-slips, and 0.2–0.8 Total Electron Content Unit (TECU) magnitude perturbations are observed when the trajectories of ionospheric pierce points fall into the perturbed region. The propagation speed of 102.6–141.3 m/s and the direction of the propagation indicate that the GWs are propagating upward from a certain thunderstorm at lower atmosphere. The composite results of disturbance magnitude, period, and propagation velocity indicate that GWs initiated by thunderstorms and propagated from the troposphere to the ionosphere are observed by GNSS for the first time in the low-latitude region.

The location service is an important part of the smart city. A unified location service for outdoor and indoor/overground and underground activity will assist the construction of smart cities. However, with different coordinate systems and data formats, it is difficult to unify various positioning technologies on the same basis. Global navigation satellite system (GNSS)-based positioning is the only way to provide absolute location under the Earth-centered, Earth-fixed coordinate system (ECEF). Increasing indoor and underground human activity places significant demand on location-based services but no GNSS signals are available there. Fortunately, a type of satellite that is indoors, known as pseudolite, can transmit GNSS-like ranging signals. Users can obtain their position by receiving ranging signals and their resection without adding or switching other sensors when they go from outdoors to indoors. To complete the outreach of the GNSS indoors and underground to support the smart city, how to adapt the pseudolite design and unify coordinate frames for linking to the GNSS remain to be determined. In this regard, we provide an overview of the history of the research and application of pseudolites, the research progress from both the system side and the user side, and the plans for pseudolite-based location services in smart cities.

Ionospheric delay is a critical error source for Global Navigation Satellite System (GNSS) users. The kriging method is widely adopted to estimate the ionospheric delay at users’ locations based on sampling observations collected from a wide area reference network with the assumption of the isotropic ionosphere, e.g., satellite-based augmentation systems (SBAS) in North America, Japan, and India. However, the isotropy assumption may deviate from the ionosphere spatial characteristics in certain regions, compromising the SBAS performance. In this study, a modified ordinary kriging approach is presented based on the anisotropy characteristic of the ionospheric delay. Firstly, variograms describing the spatial random characteristics for kriging are analyzed to investigate the differences along longitude and latitude directions. It is observed that the anisotropy behavior is obvious in low- and mid-latitude regions and becomes very weak in high-latitude region. Furthermore, the isotropic ordinary kriging (IOK) is expanded into anisotropic ordinary kriging (AOK) with regional anisotropic variogram models constructed for three regions at low, middle, and high latitudes. Experimental results show that AOK significantly improves the delay estimation accuracy compared with the previous IOK method. Specifically, based on a wide reference network in North America, the implementation of AOK reduces the magnitude of the root mean square fit residual by 24.48%, 14.92%, and 6.90% in low-, mid-, and high-latitude regions. Moreover, the AOK algorithm consistently outperforms both IOK and UnK across in low- and mid-latitude regions, regardless of solar activity levels. The anisotropy characteristic in ionosphere and the AOK technology facilitate the development of high-precision ionospheric delay modeling from isotropic to anisotropic models using a wide area reference network.