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Extracting building construction time is crucial for effective land resource management and sustainable urban development, particularly in fast-growing urban areas. However, acquiring building construction time remains challenging due to limited observations with multiple changes. To address this issue, we applied a monthly time series of remote sensing images and the LandTrendr change detection algorithm to extract building construction times. We identified the sensitive index of short wavelength infra-red (SWIR) from satellite observations for detecting changes in building construction, demolition, and reconstruction. Comparing composite results at different temporal intervals revealed that monthly data is more effective in accurately characterizing building changes compared to daily and yearly intervals. Additionally, our improved algorithm in Google Earth Engine identified the maximum change time as the construction turning point at the pixel level. We then revealed Beijing's construction time from 1990 to 2020 by overlaying building footprint data with extracted year information from Landsat images. Our results achieved an 82.32% agreement on identified construction time of buildings with a two-year tolerance strategy using 560 randomly collected building samples. Our results outperformed traditional methods such as annual time series composition with the same LandTrendr algorithm, historical surveying map, and building change time of social big data monitoring, with derived overall accuracies of 68.75%, 74.64%, and 67.47%, respectively, suggesting the good performance of the adopted approach. This study offered a potential avenue for detailed monitoring of urban building changes at a fine-grained spatial scale, with far-reaching implications for sustainable urban development practices.

Synthetic aperture radar (SAR) records important information about the interaction of electromagnetic waves with the Earth’s surface. However, long-term and high-resolution backscatter coefficient data are still lacking in many urban studies (e.g., building height estimation). Here, we proposed a framework to reconstruct the 1-km backscatter coefficient in 1990–2022 utilizing the Sentinel-1 Ground Range Detected data and Landsat time series data in the Jing–Jin–Ji (JJJ) region. First, we developed a regression model to convert the optical signals from Landsat into backscatter coefficients as the Sentinel-1 data, using observations from 2015 to 2022. Then, we reconstructed backscatter coefficients from 1990 to 2022 using the long-term Landsat data. Using the reconstructed backscatter coefficients, we analyzed the dynamic patterns of building height over the past decades. The proposed approach performs well on estimating the backscatter coefficient and its spatial pattern, with the annual mean absolute error, root mean square error, and R2 of 1.10 dB, 1.50 dB, and 0.64, respectively. The temporal trends revealed from the reconstructed backscatter data are reliable compared with satellite observations at a relatively coarse resolution, with Pearson’s coefficients above 0.92 in 6 sample cities. The derived building height from the reconstructed SAR data indicates that the JJJ region experienced a noticeable upward expansion in 1990–2022, e.g., Beijing has the fastest growth rate of 0.420 km3/decade regarding the total building volumes. The proposed framework of reconstructing SAR data from optical satellite images provides a new insight to complement the long-term and high-resolution backscatter from local to global scales.

Although several products of the global urban extent with fine resolutions (e.g. 30 m-38 m) have been developed, quantitative evaluations of these products across spaces and times are still missing, which is crucial to future urban growth modeling. Here, we analysed the discrepancy of six global fine resolution urban extent products across spaces and times. First, we measured the area variations of urban extent among these urban products in each 0.25° grid used in the Land-Use Harmonisation (LUH2), a commonly used product with future projections in Earth system modelling. Then, we analysed the potential urban growth within each 0.25° grid using the LUH2 data under eight scenarios shaped by shared socioeconomic pathways (SSPs) and representative concentration pathways (RCPs). Finally, we identified those regions with a large discrepancy and noticeable growth of urban extent under historic and SSP-RCPs scenarios. We found the discrepancy among six products occurs in either highly developed (e.g. the United States-US and Europe) or rapidly developing (e.g. China) regions. Moreover, Eastern US, Europe, and West Africa deserve more attention in the future due to their distinct urban growth and relatively large discrepancy of urban areas. The derived results are crucial to future global urban sprawl modeling .

Abstract Precise Point Positioning (PPP) with Ambiguity Resolution (AR) is an important high-precision positioning technique that is gaining popularity in geodetic and geophysical applications. The implementation of PPP-AR requires precise products such as orbits, clocks, code, and phase biases. As one of the analysis centers of the International Global Navigation Satellite System (GNSS) Service (IGS), the Wuhan University Multi-GNSS experiment (WUM) Analysis Center (AC) has provided multi-GNSS Observable-Specific Bias (OSB) products with the associated orbit and clock products. In this article, we first introduce the models and generation strategies of WUM rapid phase clock/bias products and orbit-related products (with a latency of less than 16 h). Then, we assess the performance of these products by comparing them with those of other ACs and by testing the PPP-AR positioning precision, using data from Day of the Year (DOY) 047 to DOY 078 in 2022. It is found that the peak-to-peak value of phase OSBs is within 2 ns, and their fluctuations are caused by the clock day boundary discontinuities. The associated Global Positioning System (GPS) orbits have the best consistency with European Space Agency (ESA) products, and those of other systems rank in the medium place. GLObal NAvigation Satellite System (GLONASS) clocks show slightly inconsistency with other ACs’ due to the antenna thrust power adopted, while the phase clocks of other GNSSs show no distortion compared with legacy clocks. With well-estimated phase products for Precise Orbit Determination (POD), the intrinsic precision is improved by 14%, 17%, and 24% for GPS, Galileo navigation satellite system (Galileo), and BeiDou-3 Navigation Satellite System (BDS-3), respectively. The root mean square of PPP-AR using our products in static mode with respect to IGS weekly solutions can reach 0.16 cm, 0.16 cm, and 0.44 cm in the east, north, and up directions, respectively. The multi-GNSS wide-lane ambiguity fixing rates are all above 90%, while the narrow-lane fixing rates above 80%. In conclusion, the phase OSB products at WUM have good precision and performance, which will benefit multi-GNSS PPP-AR and POD.

A catastrophic rock avalanche from a tableland escarpment occurred at the Pusa village, Guizhou Province, southwest (SW) China, causing 35 fatalities and huge economic losses. The steep slope lies in the Longtan Formation coal-bearing shale of Permian, which is widely distributed in SW China. It was overlaid by brittle superstrata in Triassic and followed by gently anticline tectonic movement in Cenozoic, thus forming large-scale tableland escarpments with an “upper brittle, lower ductile” structure. Affected by underground coal mining activity at the base, this escarpment has become unstable and prone to failure. In order to further clarify the geological conditions and other influence factors for the Pusa landslide, we propose a newly improved multiple Differential Interferometric Synthetic Aperture Radar (DInSAR), named average-DInSAR, to detect the displacements on escarpments in a broad region. Extensive experimental results show that there existed obvious pre-failure displacements on the swarming escarpments, evidencing their unstable state, which were verified by field inspection. The spatiotemporal correlation analysis suggests that this abnormal deformation is probably induced by underground coal mining in the vicinity. Further confirming that the special geological conditions and nearby coal mining activity were responsible for the 2017 Pusa rock avalanche. Our study also demonstrates that the average-DInSAR method is simple and effective, which can overcome low coherence and noise of DInSAR, especially for shorter X- or C-band SAR data. Application of proposed method would permit to detect displacement before slope failure with higher re-visiting frequency, thus helping define early warning strategies for landslides in area with similar geological conditions.

Precise point positioning with ambiguity resolution (PPP-AR) based on multiple global navigation satellite system (multi-GNSS) constellations is an important high-precision positioning tool. However, some unmodeled satellite and receiver biases (such as errors in satellite attitude) make it difficult to fix carrier-phase ambiguities. In order to fix ambiguities of eclipsing satellites, accurate integer clock and satellite attitude products (i.e., attitude quaternion) have been provided by the International GNSS Service (IGS). Nevertheless, the quality of these products and their positioning performance in multi-GNSS PPP-AR have not been investigated yet. Using the PRIDE PPP-AR II software associated with the corresponding rapid satellite orbit, integer clock and attitude quaternion products of Wuhan University (WUM), we carried out GPS/BDS PPP-AR using 30 days of data in an eclipsing season of 2020. We found that about 75% of GPS, 60% of BDS-2 and 57% of BDS-3 narrow-lane ambiguity residuals after integer clock corrections fall within ±0.1 cycles in the case of using nominal attitudes. However, when using attitude quaternions, these percentages will rise to 80% for GPS, 70% for BDS-2 and 60% for BDS-3. GPS/BDS daily kinematic PPP-AR after integer clock and nominal attitude corrections can usually achieve a positioning precision of about 10, 10 and 30 mm for the east, north and up components, respectively. In contrast, the counterparts are 8, 8 and 20 mm when using attitude quaternions. Compared with the case of using attitude quaternions only at the network end for the integer clock estimation, using attitude quaternions only at the user end shows a pronounced improvement of 15% in the east component and less than 10% in the north and up components. Therefore, we suggest PPP users apply integer clock and satellite attitude quaternion products to realize more efficient ambiguity fixing, especially in satellite eclipsing seasons.

Interferometric Synthetic Aperture Radar (InSAR) and Differential Interferometric Synthetic Aperture Radar (DInSAR) have shown numerous applications for subsidence monitoring. In the past 10 years, the Persistent Scatterer InSAR (PSI) and Small BAseline Subset (SBAS) approaches were developed to overcome the problem of decorrelation and atmospheric effects, which are common in interferograms. However, DInSAR or PSI applications in rural areas, especially in mountainous regions, can be extremely challenging. In this study we have employed a combined technique, i.e., SBAS-DInSAR, to a mountainous area that is severely affected by mining activities. In addition, L-band (ALOS) and C-band (ENVISAT) data sets, 21 TerraSAR-X images provided by German Aerospace Center (DLR) with a high resolution have been used. In order to evaluate the ability of TerraSAR-X for mining monitoring, we present a case study of TerraSAR-X SAR images for Subsidence Hazard Boundary (SHB) extraction. The resulting data analysis gives an initial evaluation of InSAR applications within a mountainous region where fast movements and big phase gradients are common. Moreover, the experiment of four-dimension (4-D) Tomography SAR (TomoSAR) for structure monitoring inside the mining area indicates a potential near all-wave monitoring, which is an extension of conventional InSAR.