Conference Agenda

Southwestern China’s complex terrain and climate make landslides frequent, especially along highways where numerous high, steep artificial slopes are formed during construction. These slopes often deform or fail within 1–2 rainy seasons due to intricate geology, severely affecting construction and infrastructure safety. An automated, real-time monitoring and early-warning system is therefore urgently needed.

Conventional techniques (leveling, GPS, crack meters) are limited by small coverage, low efficiency, high cost, and inability to detect regional or hidden deformations. Spaceborne InSAR offers wide-area, high-precision, all-weather monitoring but faces severe decorrelation noise from dense vegetation and atmospheric delay errors in mountainous regions.

This study developed advanced InSAR methods for artificial slopes along the Huali Highway (G4216) in Yunnan Province. Using TCPInSAR and >240 Sentinel-1 images (2015–2025), we retrieved surface deformation throughout pre-construction, construction, and post-construction phases. To overcome local challenges, two novel correction approaches were proposed: (1) a noise-reduction method based on spatial correlation estimation of deformation signals, effectively suppressing vegetation-induced decorrelation; and (2) an atmospheric correction technique using Singular Spectrum Analysis (SSA), significantly reducing delays caused by complex weather.

Results show the improved InSAR system successfully detected multiple deformation zones along the corridor and provided reliable early warnings for safety management. By addressing key technical bottlenecks, this work validates the practicality and effectiveness of advanced InSAR for automated slope stability monitoring in geologically and environmentally complex regions, offering valuable reference for similar large-scale infrastructure projects.

Meteorological control of L-band forest backscatter from the BorealScat-2 radar tower

How strongly do weather conditions imprint on L-band radar signals from forests at sub-daily time scales? This question is investigated using the BorealScat-2 tower experiment in the Svartberget Experimental Forest (northern Sweden). The system acquires fully polarimetric, tomographic radar data at P, UHF and L band every 30 minutes, providing height-resolved backscatter profiles from the ground, through the trunk zone, into the upper canopy. Within the shared footprint, an ICOS flux mast delivers continuous measurements of CO₂, water vapour and energy fluxes, together with radiation, vapour pressure deficit (VPD), temperature, wind and precipitation. Sap-flow sensors, dendrometers and soil water probes further characterise water storage and transport in trees and soils, offering an unusually detailed description of forest water dynamics.

The study will focus on L-band backscatter during late spring and summer, quantifying how diurnal amplitude, phase and vertical centre-of-mass in different height zones and polarisations relate to VPD, temperature, radiation and rainfall. It will specifically assess the relative roles of atmospheric demand, canopy wetness and soil water status in driving sub-daily L-band variability, and examine differences between co- and cross-polarised channels and between structural layers. Overall, the study aims to provide process-based insight into how specific meteorological drivers control sub-daily L-band radar variability in boreal forests, supporting the interpretation and modelling of future vegetation radar missions.

The digital elevation model (DEM) based on synthetic aperture radar interferometry (SAR, InSAR) technology have become an important data source for large-scale topographic mapping, but their characteristics vary with satellite systems and methodologies. In this paper, we conduct the cross-validation for the first time to compare the LuTan-1 raw DEM (LT-1 RDEM) and GaoFen-7 (GF-7) satellite laser altimetry data. Besides, we compared the penetration capabilities of SAR satellites including C-band SRTM and X-band TanDEM-X. The optically derived ZiYuan-3 (ZY-3) DEM was also included for multi-source cross-validation. Taking Guyuan County, Hebei Province, China (including four landform types: plains, tablelands, hills, and mountains) as the study area, we introduced GF-7 laser altimetry points (LAPs) as the verification benchmark to cross-validate the elevation accuracy of LT-1 RDEM, SRTM, TanDEM-X DEM (TanDEM), and ZY-3 DEM. The results indicate that: (1) Topographic relief has a significant impact on accuracy, and the RMSE of the DEMs in the study area generally increases sequentially with the intensification of topographic relief; (2) Benefiting from the 10-meter spatial resolution, LT-1 RDEM performs best in detail representation; (3) In terms of mean height error, LT-1 RDEM exhibits a general negative bias, confirming the stronger penetration capability of the L-band, and its elevation values may be closer to the true ground surface; (4) The RMSE of LT-1 RDEM in the study area is 1.958m, slightly larger than TanDEM’s 1.65m, but in fact, the accuracy of TanDEM as a digital surface model (DSM) may be systematically overestimated by laser altimetry data.

This study evaluates the operational capability of the Chinese LuTan-1 (LT-1) L-band SAR constellation for monitoring the Hong Kong–Zhuhai–Macao Bridge (HZMB), a representative sea-crossing bridge under a complex subtropical marine climate. Leveraging the advantages of L-band SAR—including strong resistance to decorrelation and a spatial resolution of up to 3 meters—we applied the Small Baseline Subset (SBAS) technique to 47 ascending and descending orbital images. To the best of our knowledge, this represents one of the first comprehensive deformation studies of the HZMB using the LT-1 constellation. A key aspect of our methodology is the cross-validation between multi-orbit datasets, which confirmed both the reliability of the measurements and the complementary distribution of coherent points due to SAR imaging geometry. The results indicate overall structural stability of the HZMB, with the maximum deformation localized at the Jianghai Navigation Bridge, showing a Line-of-Sight (LOS) displacement rate of –4.3 mm/yr. In contrast, the two artificial islands exhibited minor deformation, with LOS rates not exceeding –3.0 mm/yr. These findings validate LT-1 as a powerful and reliable tool for the operational health monitoring of large-scale coastal infrastructure.

LuTan-1 (LT-1) satellites have been launched for about 4 years. About 771,282 images have been distributed to the users of China till 29th October, 2025. Main application purpose of LT-1 is geohazard monitoring and geoinformation production. Interferometric capability is the primary consideration for LT-1. In this paper, we assessed the interferometric applications in the natural resource monitoring industry. First, we overviewed the status of LT-1, the main interferometric products were introduced as S2A, S2B, S3A, S4A, S5A, S5B and S5C. They are geometrically calibrated single look complex (SLC) image, interferometrically calibrated SLC, differential interferometric synthetic aperture radar (SAR, InSAR, DInSAR) products, stacking, MTInSAR, digital orthorectified image, and digital surface model, respectively. S2A are generated after geometric calibration, the geometric accuracy is about 1.53 after calibration. The baseline is then calibrated for helix bistatic formation data and generate S2B whose accuracy is better than 0.96 m. S3A, S4A and S5A are all used for deformation monitoring, the accuracy values of them are 2.7 mm, 8.6 mm/yr, and 3.7 mm. Geometric accuracy of S5B is 12.5 m, and the height accuracy of S5C is better than 4.7 m. More than 330 geohazards were detected in Guangdong province. The geohazards recognition rate in the field working stage increase from 28% to 47.24%. Even a prediction has been made to avoid disaster for a family and saved 3 people. The application effectiveness has been validated through those years.

The influence of soil moisture change on interference phase information is fully taken into account for accurate deformation monitoring in this research. Especially the effects have more prominent contribution to L-band SAR data. In order to obtain high-precision surface deformation information over agricultural area, the interference phase component caused by soil moisture change should be considered, and the optimal processing of interference phase information is achieved. The reliable interference phase information characterizing the surface deformation details is obtained, thus the natural surface deformation information with high precision can be achieved. Firstly, the penetration depth of different band SAR for agricultural soil was analyzed and simulated. And the sensitivity between penetration depth variation and different band SAR signals were discussed. The fact of soil moisture changes for interferometric phase contribution is confirmed, which provided the foundation for reliable deformation montoring considering the soil moisture variation effects, especially for L-band SAR data. The periodic irrigation for the wheat fields will induce soil moisture variation, which may result in the penetration depth change for radar electromagnetic wave. Therefore, the phase component was derived by the variation of soil moisture over the wheat fields. Multi-temporal Lutan-1 SAR data were acquired over ShanDong agricultural plain in China. The obvious ‘deformation details’ induced by the soil moisture change were acquired over the agricultural area, which demonstrated the effect of soil moisture variation for interference phase. Therefore, the accurate deformation details over agricultural area can be obtained by the combination of soil moisture information.