Hao Luo, Xiao Yan, Xinyan Li, Qiming Zeng, Yuhao Lin, Shanshan Feng, Hao Wang, Jiawei Jiang. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2026.

Smart contract is a kind of self-executing code based on blockchain technology with a wide range of application scenarios, but the traditional generation method relies on manual coding and expert auditing, which has a high threshold and low efficiency. Although Large Language Models (LLMs) show great potential in programming tasks, they still face challenges in smart contract generation w.r.t. effectiveness and security. To solve these problems, we propose FSM-SCG, a smart contract generation framework based on finite state machine (FSM) and LLMs, which significantly improves the quality of the generated code by abstracting user requirements to generate FSM, guiding LLMs to generate smart contracts, and iteratively optimizing the code with the feedback of compilation and security checks. The experimental results show that FSM-SCG significantly improves the quality of smart contract generation. Compared to the best baseline, FSM-SCG improves the compilation success rate of generated smart contract code by at most 48%, and reduces the average vulnerability risk score by approximately 68%.

SAR data acquisition is increasingly challenged by the overcrowded radio frequency bands, a phenomenon known as Radio Frequency Interference (RFI), particularly at L-band. We implement a robust algorithm to measure global RFI in SAR data. We process the entire L-band SAR data archive acquired by the JAXA JERS-1 and ALOS-1 satellites to provide a global view of RFI in L-band SAR data. The RFI detection results are saved in a predefined format. These RFI products can provide guidance on SAR data applications and prepare us for the upcoming L-band era.

Three-dimensional (3-D) deformation could be resolved using multi-track Interferometric Synthetic Aperture Radar (InSAR), with the accuracy dependent on the magnitude of multi-source errors within InSAR measurements. To improve the precision of 3-D deformation, it is essential to understand the error propagation mechanism and then develop the methodology for reducing error impacts in 3-D decomposition processing. In this article, we present an error propagation model that incorporates both systematic and stochastic error propagation, which determines the error contribution of the multi-track InSAR measurements in the 3-D direction. The systematic error propagation includes generic systematic error and additional systematic errors (ASE) in the vertical and east directions caused by neglecting the north component. For stochastic error propagation, we construct the covariance matrix by considering variance and correlation from different InSAR measurements when using differential and multi-temporal InSAR techniques. Accordingly, we propose a new 3-D deformation inversion method, combining the covariance matrix and L2-norm regularization based on multi-track InSAR (CovRM-InSAR) to improve the precision of 3-D deformation with noise reduction. In the case study, we applied Sentinel-1A and ALOS-2 InSAR datasets from four tracks to map 3-D velocity in Wuhai and analyzed the time-series error propagation and 3-D uncertainty. The precision of 3-D deformation resolved by CovRM-InSAR has improved by up to 90%, 44%, and 98% in the vertical, east, and north directions, respectively. Additionally, the CovRM-InSAR has effectively reduced the stochastic errors by up to 38%, 15%, and 90% in the vertical, east, and north directions, respectively.

Persistent Scatterer (PS) is the measuring point of the PS-InSAR, its quantity and density directly determine the accuracy of the deformation monitoring results. The spatial distribution density of PS is mainly affected by the land cover type. However, there is a lack of quantitative understanding of the distribution probability of PS on various land cover types. The PS probability of a pixel in a specific land cover type is heavily dependent on the backscattering properties of the ground type, but the disturbance of the area proportion of land cover types will also affect the probability distribution of PS. In order to solve the above problems, we proposed to use Bayesian estimation to correct the influence of the area proportion of land cover types on the spatial distribution of PS, revealing the probability that a pixel of a specific land cover type is PS in essence.

Distributed scatterers interferometric synthetic aperture radar (DS-InSAR) has been widely used in measuring non-urban area displacement. However, the process of identifying homogeneous pixels (HPs) through hypothesis testing is often time-consuming, and the results may not provide sufficiently consistent signals for phase reconstruction. This letter proposed a method to identify geomorphic statistical homogeneous pixels (GSHPs) by introducing land cover types and terrain features as constraint condition. Water, shadow and layover area are masked off. And the land cover types, slope and aspect are used for HPs test. GSHPs is tested in the Three Gorges Dam Reservoir Area and the Three Parallel Rivers of Yunnan in China using Sentinel-1 data (2020-2022). The results show that GSHPs method saves 23% identification time and improves the consistency of HPs signal compared to classical SHPs. Several reported landslides’ activities are successfully detected by GSHPs.

Using Weather Research and Forecasting (WRF) to simulate water vapor is one of the efficient and reliable methods of current InSAR atmospheric correction. However, its preprocessing is complicated and requires a higher computing environment, and its running time is longer. The above-mentioned characteristics limit the use of WRF. Different initializations have a non-negligible impact on the running time and simulation results. We use ERA5 and FNL to drive WRF to simulate water vapor and the results are used for tropospheric correction in the Beijing region. The comparative evaluation with MERIS and GACOS proved the reliability of WRF with ERA5 as the initialization for InSAR atmospheric correction. The high time resolution of ERA5 effectively shortens the simulation time of WRF and provides the possibility for its atmospheric correction application in time series InSAR.

Digital elevation models (DEMs) are the basic data of science and engineering technology researches. The quality of DEMs affects the results of applications. Therefore the quality assessment of DEMs is valuable. DEMs' quality was reported by distribution agencies at a global scale, but they are not representative at a local scale. There are multiple DEMs products in the same local area. Researchers don't know the exact quality of these products and will be confused when choosing the one to use in the subsequent applications. SRTM and ASTER GDEM with 30 m spatial resolution are currently widely used global DEMs, which are freely available and accurate. As a global DEM product, TanDEM-X DEM with 12 m resolution, distributed in September 2016, has attracted users' attention due to its unprecedented accuracy. The geometric resolution, accuracy, and ability to depict complex topography of TanDEM-X DEM 12 m is excellent. It was then resampled to a 30 m pixel size. To help researchers choose the proper DEMs for their studies, we assessed the quality of these 30 m resolution DEMs on selected Chinese regions by taking TanDEM-X DEM 12 m as reference. The quality assessment of the datasets was carried out based on analyses of the differences in elevation between TanDEM-X DEM 12 m and each DEMs. Before calculating the height differences, co-registration is needed to eliminate the effect of systematic errors on quality assessment. This study proposes an improved Least Z-Difference (LZD) algorithm with nine parameters to complete co-registration. Quantile-quantile plots were then generated for visual inspection of normality of registered and non-outliers residuals' distribution between DEMs. The plots showed a residual non-normality. By statistical analysis of residuals, we found that TanDEM-X DEM 30 m had the highest vertical quality relative to the reference DEM, while ASTER GDEM had the worst one. SRTM had a relatively good quality.

A three-component scattering model was developed by Freeman and Durden to fit and interpret polarimetric synthetic aperture radar (PolSAR) data, after which it experienced a fast-paced development and was applied widely for its simplicity in concept and effectiveness in exposing the scattering mechanism. However, there remain problems, such as unfitness models and negative powers. In this paper, we proposed a novel model-based decomposition approach by replacing the unfitness model with a new adaptive model and reducing negative powers. Furthermore, the novel approach shows potential of retrieving target's physical properties of symmetry, shape and orientation. We evaluated the proposed approach by comparing it with existing approaches and applied it to classification and earthquake-induced damage detection. The results indicate that it not only works better than the existing approaches for significantly lower negative powers but also is effective in classification and earthquake-induced damage detection.

The accuracy of low frequency space-borne Interferometric Synthetic Aperture Radar (InSAR) is seriously affected by ionospheric path delay. Range Split-Spectrum (RSS) method is a widely-used method to remove ionospheric delay phase from interferogram. This method distinguishes ionospheric component from other non-dispersive components for its dispersive character. However, the estimated ionospheric delays differ a lot with different parameters (including multilook number and filter window). For general remote sensing users, setting above parameters is more subjective and arbitrary, which will finally affect the ionospheric delay correction effect. Based on International Reference Ionosphere (IRI) model, we present a method to determine RSS parameters. Different ionospheric delays estimated by RRS method with different parameters are compared and evaluated referring to IRI. Meanwhile, we find that there is a bias between the ionospheric delays estimated by RSS and IRI. Removing this bias may further improve the effect of ionospheric delay correction.

Timely detection and identification of building damage is vitally important for rescue planning after a catastrophic earthquake. Synthetic aperture radar (SAR) is a powerful tool for monitoring large-scale damage and can provide quick response. Compared with single-polarization SAR, fully polarimetric SAR (PolSAR) provides richer backscatter information of targets, making it possible to assess building damage with only post-event SAR data. In this study, we propose a novel building damage assessment method from post-seismic PolSAR image. This method combines the optimization of polarimetric contrast enhancement (OPCE) algorithm and the template matching thoughts to build a new building damage detector. The Radarsat-2 PolSAR image acquired in affected areas after the 2010 Yushu earthquake is used to analyze the performance of the proposed method. The result shows the effectiveness of the proposed method, and the detection rate of serious building damage areas can up to 83.2%.

In coal mining areas, ground subsidence persistently happens, which brings serious environmental issues and affects the safety of infrastructure. In order to effectively assess and control the security problems especially traffic problems brought by mining in Dayan mining area which located in Hulunbeier, Inner Mongolia, China. This paper uses the sentinel-1 data to monitor land subsidence through D-InSAR. According to D-InSAR results, it can be clearly found that the uplifting of railways and the subsidence basin caused by human activities. Subsidence basin is the most risky area and should be concerned, so we analyzed it carefully through combining subsidence profile and coherence profile. By comparing with the leveling results, the accuracy of D-InSAR reaches 7.7 mm. The research shows that D-InSAR can accurately reflect the trend of land subsidence, which is important for land deformation monitoring in mining areas and D-InSAR results can provide data support for mine safety assessment.

Boundary and area information could be used to study various interesting relations of multiple disasters such as "magnitude-area" relation for earthquakes. In this paper, a new method using InSAR-derived interferograms to determine the boundary of the crustal deformation area is introduced. Although InSAR has been widely used in crustal deformation monitoring, little is known about boundary detection using interferograms. The proposed method conducted Atmospheric Phase Screen (APS) correction to the interferograms based on Numerical Weather Prediction (NWP) model offered by Generic Atmospheric Correction Online Service for InSAR (GACOS). Moreover, this study proposed a suggestion to identify points in the interferograms at which the deformation changes smoothly that could be determined as the far-field boundary. Here we used a pair of Sentinel-1A images to investigate the deformation boundary associated with the 2017 Iran Sangsefid earthquake as an example. It was experimentally shown that the proposed method provided an inspiring scheme for boundary detection based on InSAR interferograms.

Earthquake damage assessment using multi-temporal medium-resolution SAR data with dual polarization is possible. In this study Sentinel-1 SAR data have applicated for earthquake damage assessment using existing change detection method. Sentinel-1 data are applicable due to universal availability of pre- and post-earthquake SAR imageries for maximum six days. The normalized difference of intensity correlation coefficient (NDIC), normalized difference of interferometric coherence coefficient (NDCC), co-seismic intensity correlation (IC) and difference in the backscattering coefficient (DBC) images were used in order to create damage maps. In this investigation, histogram of damaged and intact building in the values of NDIC, NDCC and statistical distribution of IC-DBC were analyzed with different window size of correlation coefficients r and local mean values m. It was found that damaged buildings are better detectable with NDIC and NDCC variables than IC-DBC. Artifical neural network (ANN) supervised classification method has better results of producer's accuracy for damaged building classes. Producer's accuracy of damaged building class is achieved 95.6%, however, there are misclassification between intact building and none built-up area, it is decreased by using GIS data having mask of built-up area. These results lend support to the idea of realization low-cost method of damage assessment after natural disasters based on Sentinel-1 and GIS data, which are required for insurance companies and governments. Amatrice and Sarpol-e Zahab cities were studied in this investigation, which have been more affected by the earthquakes in 2016-2017.

Digital elevation model (DEM) is an important input data in geometric correction of Synthetic Aperture Radar (SAR) image. The accuracy of elevation and spatial resolution will affect the result of geometric correction. The quality assessment and comparison of the 12m & 30m resolution WorldDEM products and SRTM v3 and GL1 DEM are carried out, and all the data are respectively used to geometrically correct Radarsat2 SAR images. The results show that WorldDEM elevation accuracy is significantly better than SRTM DEM and can significantly improve the quality of image correction in SAR geometric correction.

A modified volume scattering model for Freeman-Durden three-component decomposition is proposed in this study. Due to the inconsistency between uniform oriented dipole mode and the actual volume scattering mechanism for terrain types, the power of surface scattering and double-bounce scattering are occasionally negative. We established the volume scattering model using dipoles with two dominant orientations and proved it can decrease the probability of negative power occurrence in mathematics. The new volume scattering model is better to mimic the building with sloped roofs. We carried out three-component decomposition with proposed volume scattering model and other three models respectively using the L-band AIRSAR polarimetric SAR data. The results show that the pixels with negative powers are significantly decreased by our model and thus the effectiveness of the new model are demonstrated. In particular, the proposed volume scattering model work well in the forest and oriented building areas.

Repeat-pass spaceborne differential synthetic aperture radar interferometry (DInSAR) is commonly used to measure surface deformation. However, the phase delay due to the atmospheric water vapor has a significant influence on the accuracy of DInSAR results. On the other hand, the signal delay in DInSAR can give the spatial variation information of water vapor during the two image acquisitions. There are some ripple-like phase signals in DInSAR, which are probably due to the mountain wave in the study area. In this paper, the weather research and forecasting (WRF) model is used to simulate the atmospheric delay and compared to the phase delay derived from DInSAR results to understand the mountain-wave phases in interferograms. The results indicate that the ripple-like phase signal in the DInSAR phase is due to different intensities of the mountain wave in two acquisitions. The WRF model can be used to explain the mechanism of mountain-wave phase in DInSAR, which may then, hopefully, be used for DInSAR atmospheric correction.

The Water Vapor simulated from the Weather Research&Forecast Model (WRF-WV) has been utilized for InSAR (Interferometric Synthetic Aperture Radar) atmospheric correction in recent years, but its reliability in terms of accuracy of the water vapor itself and application in InSAR process are controversial. Therefore this paper inspected it by comparing WRF-WV with Medium Resolution Imaging Spectrometer (MERIS) products with higher resolution. Our results demonstrate that are WRF-WV are mostly consistent with those of MERIS, with RMSE (Root Mean Square Error) 0.3751 and 0.2126, respectively. Then its reliability of application is carefully examined in InSAR process using ASAR data in Bam non-deforming area and the results indicate that the mean LOS displacement decreased from 1.634 mm to 0.819mm, with standard deviation declining to 5.788mm from 7.17mm.

Compared with DEM generated from single frequency or single baseline repeat pass inteferometric SAR data, the quality of DEM fused with multi-baseline multi-frequency InSAR has been improved effectively. However, the quality of fused DEM by using same orbital and illuminating direction has still been constrained by some factors, among of which the layover and shadow effects are the most important ones, especially in areas where topography reliefs change rapidly. In this paper, we proposed an innovation method to fuse ascending and descending multi-baseline multi-frequency InSAR results to generate higher quality DEMs, which included how to access the effective information in the DEMs generated by using ascending and descending interferometric data, and to complement each other to eliminate potential deficient in layover and shadow areas. The key point of the fusion strategy was to set fusion weight for each resolution element according to the reliabilities, effective mean coherences and resolution ratios of ascending and descending DEMs to be fused. Experiments with real SAR data proved that the proposed method could improve the DEM quality effectively.

A geocoding method for SAR image based on Triangulated Irregular Network (TIN) lookup table is proposed in this paper. Firstly, TIN DEM is generated from Grid DEM. Then, each node in TIN DEM is geocoded by Range-Doppler model to produce a TIN lookup table. Finally, geocoded image is resampled by TIN lookup table. Experimental results show TIN lookup table can reduce file size with losing less precision, which compared with original Grid lookup table. Although TIN lookup table takes some time to create TIN DEM from Grid DEM, it takes less time than original lookup table in geocoding process. So it could save running time for large number of SAR images geocoding in the same area. TIN lookup table can balance between precision and file size, when its height tolerance approximately is less than accuracy of DEM products.

The water vapor plays an important role on the microwave propagation. Plenty of methods to reduce its effects in the differential InSAR technique have been put forward, such as using MERIS, MODIS, GPS and the weather models. In order to analyze the water vapor effects quantitatively, we selected several time-series related Envisat ASAR images with their corresponding synchronous MERIS Full Resolution water vapor products. First of all, we analyze the quantitative relationship between the water vapor delay and the local elevation and find that there is no obvious linear correlation between water vapor and elevation. Then, we make a comparison between the InSAR measurements without water vapor correction and measurements with water vapor correction. The results indicate that the removal of the water vapor delay and the baseline refinement are coupled together. And at the same time, the influence of water vapor can lead to error of at least 10 mm.

High-coherent pixels detection and spatial coverage restriction are the key difficulties when applying the InSAR time series analysis in Altyn Tagh Fault (ATF) system based on stripmap SAR data. In this paper, a modified InSAR time series analysis method combining PS and DS is presented in order to increase the number of selected high-coherent pixels. Then a displacement velocities merging strategy by fitting least squares surfaces is proposed, which could decrease the velocities differences in overlap area between adjacent stripmap SAR tracks, so as to acquire the deformation results of the whole research area. Moreover, in order to avoid the merging problem caused by the inconsistent measurements between adjacent stripmap SAR tracks, processing strategies of ScanSAR PS-InSAR and ScanSAR SBAS are presented respectively. All of the methodology we proposed have been applied to the crustal movement measurement along the west section of ATF and reliable results have been acquired.

Rapidly obtaining building damage information after the earthquake is vitally important to earthquake rescue and decision making. In this paper, we propose a new framework of building collapse extraction by combining polarimetric information and azimuth time-frequency analysis. The proposed framework consists of two main steps, i.e. open area removal and intact building identification. In the first step, we introduce the Shannon entropy to polarimetric parameters derived from H/A/α decomposition to remove open areas. Since intact buildings with orientation angles present a similar scattering mechanism to collapsed buildings, it seriously hampers the building collapse extraction accuracy. To solve this problem, in the second step we try to use azimuth time-frequency analysis to eliminate this deficiency. In the azimuth direction, sub-aperture images are obtained by spectrum splitting, which corresponds to observe the targets from different azimuth look angles. The nonstationary discrimination method is used combined with the SPAN parameter to identify intact buildings including intact buildings with orientation angles. The feasibility of the second step has been demonstrated by using E-SAR PolSAR data. The potential advantage of the proposed framework when we apply it to the earthquake-induced building collapse extraction includes that only one post-earthquake polarimetric SAR (PolSAR) image is needed. Moreover, orientated intact buildings can be identified and the final accuracy of building collapse extraction can be probably improved as a result.

The research focuses on high precision airborne SAR geometric calibration (GC) and geolocation (GL) on the condition of long flight time. The experiment was conducted in Inner Mongolia, China, and based on image pixels' GL model, calibration parameters and procedure proposed in literature [1], two systematic parameters (near range R0and slant range resolution ρr) were calculated and validated. But, compared with the method in literature [1], improvements were mainly made on two aspects: firstly, Cubic spline rather than simple polynomial was used in this research to fit POS data so as to get a more accurate SAR antenna's position and velocity at zero Doppler time; secondly, through analysis of distribution of corner reflectors' GL errors, slant range (or near range) error was identified as main factor affecting GL, then an improved near range model was computed, validated and used to improve the accuracy of GL. Through the experiment in Inner Mongolia, the accuracy of GL in X and Y direction was 1m and 0.26m respectively, and after introducing the improved near range model, the accuracy of GL can be increased by about 10%.

Since the forming of sustainable business models of remote-sensing products and services will be an inevitable development trend, it is necessary to design the specific and rational pricing model for quantitative remote sensing products (QRSPs). Based on the production procedures, this paper presents a production cost pricing model of QRSPs, to achieve the conversion from abstract factors of production cost to the pricing parameters that can be operated in the actual cost pricing. The pricing model is devised as the addition model so that it can fulfill the diverse acquirements of customized production. The valuation of common products of China Remote Sensing Network indicated that the pricing model could be well-operated in theory.

A novel approach is proposed in this paper for earthquake-induced building collapse extraction based on the optimization of polarimetric contrast enhancement (OPCE). This method can realize a quick building damage assessment since the data it requires is one post-event fully polarimetric Synthetic Aperture Radar (PolSAR) image. In this method, collapsed building is recognized as clutter and the optimal polarization states are determined based on building samples with different orientation angles. For comparison, another contrast enhancement methodology, polarization synthesis technology is also utilized. We tested these two methods by using one Radasat-2 PolSAR image from Yushu earthquake in Qinghai province of China occurred in 2010. Results were validated by manual interpretation results of very high resolution (VHR) optical image. Experiments shows that collapsed building detection accuracy of OPCE method can be 66.53% in average, which is higher than that of polarization synthesis technology (42.7%) for the reason that building orientation is considered in the data processing of OPCE method.

Earthquake is one of the most catastrophic disasters to affect mankind especially in urban areas. Reliable and fast collapsed building detection is vitally important to timely rescue and scientific decision making. A modified detection method for collapsed buildings is proposed in this paper by jointly using interferometric information and polarimetric information. The method was tested on two single-polarimetric ALOS PALSAR images and one fully polarimetric Radarsat-2 image from Yushu earthquake in Qinghai province of China occurred in 2010. After compared with manual interpretation results of very high resolution (VHR) optical image, collapsed building detection accuracy can be 72.77%. The accuracy is improved by about 30% compared with that of only coherence based method.

In this paper, we propose a novel user-oriented information service model for the development trend of remote sensing information service industrialization. Traditional remote sensing information service model is often a typical product-oriented service model, which is unable to make the most use of the existing resource nowadays. From the perspective of information service model, this research analyzes the defects of traditional remote sensing service model and the technical development of remote sensing service, puts forward the new remote sensing information service model based on integrated platform, and notes its advantages than the traditional model. At last, this paper explores the possible technical difficulties for the implement of the new service model.

As a component of interferometric phase, atmospheric phase influences accuracy of millimetric land deformation measurement. Though Atmospheric Phase Screen (APS) can be estimated by Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technology, they are pseudo without consideration of actual atmospheric state and topography. This paper researches into ineffective separation of atmospheric phase in PS-InSAR methods when applied to extended cloudy area, and proposes an improved PS-InSAR processing flow by introducing Weather Research Forecast (WRF) simulations to remove atmospheric phase before interferometric phase analysis of PSI technique to obtain accurate land deformation velocity.

Many research institutes in China have reached the consensus that remote sensing resource sharing and application expanding can be achieved by means of extensive and sustainable cooperation and collaboration. Considering the current status of remote sensing in China and some existing systems in the world, Quantitative Remote Sensing Integrated Services Platform (QRSISP) is recently proposed and researched to promote remote sensing service for public users, facilitate the development of the remote sensing industry and improve the ability to deal with the national disasters. This paper designs the architecture, subsystems and interfaces of QRSISP and describes the major service workflows. Through combining to the ecommerce, QRSISP has tried to change the traditional mode of remote sensing applications and provide one-stop and on-demand integrated services.

Using conventional two-pass interferometry to generate DEM with high frequency SAR data may be confronted with the problem of poor coherence in areas covered by dense vegetation, while DEM generated from low frequency SAR data interferometry is less sensitive to the topographic relief. Therefore, this article aims at generating high quality DEM by fusing multi-frequency interferometric results obtained from two-pass interferometry by using Kalman filter. Meanwhile, a process of coregistration of multi-frequency SAR data which are of different pixel sizes and imaging geometries is proposed. And data from Envisat ASAR and TerraSAR-X are used for case study and the accuracy of fused DEM are verified by ASTER GDEM.

Scanning synthetic aperture radar (ScanSAR) interferometry using full-aperture approach has been used in the geophysical community when a standard ScanSAR interferometric processor is not available. Although interferograms can routinely be produced as well, some concerns about the full-aperture processing still remain. In this letter, we assess the quality of the interferogram produced by this approach. After theoretical analyses, we compare interferograms produced by the full-aperture approach and the standard burst-by-burst approach. Comparison results show that the difference between the final interferograms produced by the two approaches is small. For the data processed, the mean value and standard deviation of the difference phase are 8.36 ×10-4rad and 3.60 ×10-1rad, respectively. These results confirm the availability of full-aperture processing for most of the geophysical applications using ScanSAR interferometry.

Scanning synthetic aperture radar (ScanSAR) uses a burst technique to image very large swaths and is widely used in spaceborne SARs. Many algorithms have been proposed to focus ScanSAR burst with its phase preserved so that the focused burst can be used in interferometry to acquire large scale geophysical information, such as land deformation and digital elevation model. However, nearly all of the algorithms leave the focused burst with an additional quadratic phase term that will affect subsequent interferometric processing in the case of short burst. With this phase term, the spectrum of the focused burst is altered according to the principle of stationary phase. Therefore, some processing, such as bandpass filtering, cannot produce desired results if routinely performed. To avoid the effects of the phase term and the nonstationary azimuth spectrum of the burst, a phase compensation scheme is suggested, combining with current focusing algorithms. Simulation experiments are designed to show the effects of the phase term on bandpass filtering. These effects are further verified by a few experiments using real SAR data in unsynchronized signal removal that is frequently required in repeat-pass ScanSAR interferometry. The new phase compensation scheme is tested in real SAR data experiments and works well.

This paper presented a new strategy to improve the quality of interferograms filtered by the Goldstein filter. Two different patch sizes were applied to filtering one noisy interferogram, which resulted to two filtered interferograms. Noise of the interferogram was strongly reduced in low-coherence areas by using a larger patch size, while interferogram structures were preserved by using a smaller patch size. Then the two filtered interferograms were fused, weighted by the coherence map. Experiments with real datasets showed the satisfactory results.

The sensor calibration accuracy is an important indicator of SAR satellite system's performance and data quality. Towards geometric and radiometric calibration of Radarsat- 2 satellite (RS2), this paper researched the procedure and key techniques of space-borne SAR field calibration, including corner reflectors' (CRs) design, CRs' arrangement in the field, acquirement of CRs' peak RCS value and the surveying scheme. Besides, RS2's calibration accuracy was validated, giving reference for its quantitative application.

We have analyzed most of the commonly used burst-mode focusing algorithms and chose the one that can be easily combined with unsynchronized-signal removal. In order to remove the unsynchronized signal in scanning synthetic aperture radar (ScanSAR) interferometry, we calculate the burst synchronization using satellite state vectors at first. Then, based on the focusing algorithm chosen and the synchronization calculated, we propose a method to remove the unsynchronized signal. The method rejects the unsynchronized phase and keeps all of the magnitude information. It has been tested with simulated Envisat Advanced Synthetic Aperture Radar ScanSAR data, and the result demonstrated that the method could effectively remove the unsynchronized signal for ScanSAR interferometric processing.

Differential Interferometric Synthetic Aperture Radar (D-InSAR) has been widely used to study the co-seismic displacement field of earthquakes. With the development of D-InSAR technique, the removal of the atmospheric effect has been the main focus points of research to reduce the InSAR LOS displacement measurement error. Previous studies have shown that the MERIS water vapor product is one of the best choices for ASAR data to reduce the atmospheric effect in cloudless weather conditions. In this paper, we use the combination of the simulated results with WRF model and MERIS water vapor product to reduce the atmospheric effect in some cloudy weather condition.

An external calibration experiment was held for an airborne SAR. The paper describes the calibration experiment that uses a series of trihedral corner reflectors to calibrate the high-resolution SAR images, including antenna pattern correction and absolute radiometric calibration. In this paper, we specifically address the determination of vertical antenna pattern with multi-flight SAR imaging geometry, and discussion of the absolute calibration methods. First, three images acquired with variable off-nadir angle from 67.9~78.3, 70.9~78.4, and 72.5~79.8 degree respectively are combined to measure the antenna pattern with off-nadir angle from 67~80 degree. And then three images were relatively calibrated on the uniform standard based on the uniform antenna pattern. Secondly, the absolute calibration factor is inferred with two methods called average method and linear regression method, and the result is compared and analyzed. The experimental results show that our calibration method with several images together to acquire the large antenna pattern is feasible. And these images achieve a uniform relative calibration even though the different images have different imaging geometry and radiometric characteristics. After absolute calibration, the estimated RCS of each corner reflector basically reached agreement with the actual RCS, and the estimated error from the calibrated image for most of corner reflectors is less than 1.0dB.

In this work we analysis the relationship between the industrial structure and regional subsidence base on the research in past. We mapped the spatial and temporal patterns of the land subsidence near the city of Hangzhou, China by PSI analysis with more than 49 scenes of ERS-1/2 SAR images acquired from 1992 to 2006.[1] According to the PSI results, 13 subsidence centers (express by red dashed circle in fig 1) were found in the Xiaoshan (a district of Hangzhou, China) Economic and Technological Development Zone. Characteristics of each subsidence centers are different. I have found out 86 different enterprises belong to different industrial types (express by red pin tag in Fig 1) by field survey. The Zone was approved as a state-level development zone by the State Council in May, 1993. The structure of the Zone industry Includes 10 main types, Such as petrochemical, power industry, manufacturing and so on. Fig 2 shows the Percentage of different types of enterprises. The main reason of land subsidence in the Zone is groundwater exploitation, which is necessary for the rapid economic development.

It is necessary to calibrate interferometric system parameters in order to achieve high accuracy of DEM. The traditional calibration method use a lot of ground artificial calibrators as ground control points. However, the number of calibrators is limited and the distribution is difficult in some mountainous areas. The paper presents a calibration method based on an external DEM without any artificial calibrators. A simulated SAR image was generated with the aid of this reference DEM and a number of tie points were selected to be ground control points. This calibration method can improve the DEM accuracy, and this paper also illustrates its efficient application to airborne interferometric SAR data.

The research focuses on airborne SAR geometric calibration. Based on Range-Doppler (RD) model, mathematical model of airborne SAR image pixel direct geolocation was derived and objective calibration parameters were determined. A whole geometric calibration procedure was proposed, whose critical techniques had been studied. Through the experiment in Guizhou province, China, the calibration parameters were calculated and validated.

On May 12th, 2008, a destructive earthquake of magnitude 8.0 struck Wenchuan. The seismic region is located at the transition zone between Qinghai-Tibet Plateau and the Sichuan Basin, which has a complex geological tectonic background. In this paper, we intend to investigate the Wenchuan earthquake using the Differential Interferometric SAR(D-InSAR) technique. Due to the large scale of the crustal deformation affected by the disastrous earthquake, SCANSAR images show more advantages than conventional strip-map mode images. And taking account the vegetation conditions, the L band images are suitable than the C band images for our study. Therefore, we choose to use ALOS SCANSAR interferometric observations to obtain a preliminary co-seismic displacement filed of the Wenchuan earthquake.

A complete processing flow is proposed to implement burst mode to strip-map mode interferometry for ALOS PALSAR data. The processing flow is applied to an interferometric pair comprised of FBD (High Resolution mode [Dual polarization], belonging to strip-map mode) and WB1 (Wide observation mode, belonging to burst mode) mode of PALSAR. Interferometric products including differential interferometric phase and DEM are generated. The evaluation of these products shows satisfactory precision.

ScanSAR is a synthetic aperture radar (SAR), which has a very wide image swath. This provides a new option for interferometric applications. It makes the large scale deformation observation easier to implement. In this paper, we applied ScanSAR differential interferometry in Dangxiong, Tibet to observe the crust deformation there. However, the accuracy of ScanSAR interferometry is also affected by water vapour in the atmosphere. In our work, we tried to correct the wet delay using synchronous MERIS integrated water vapour products. In the end of this paper, the advantages and problems of ScanSAR interferometry are concluded.

Geophysical model function is the basis for the wind vector retrieval with scatterometer and a number of models have been developed to operationally retrieve the ocean surface wind in the past three decades. However, none of the operational models ever took the water surface temperature into account in its modeling, which is considered to have some effect on the ocean backscattering, and in turn on the model accuracy. Taking Sea Winds as an example, this paper attempts to develop new geophysical model functions with surface temperature to be taken into account by using its level 2A data and corresponding buoy data. For contrast, two independent models are established for the ocean water and fresh water respectively. The modeling results and analysis indicate that some effect of the surface temperature on backscatter were found for both types of water, but with a larger extent of the temperature effect for fresh water.

Geophysical model function(GMF) is the basis and prerequisite for the ocean surface wind vector retrieval with scatterometers. Among many operational models, the Qscat-1 model was specifically developed for SeaWinds scatterometer and is being applied to its operational wind retrieval. This paper is to validate the accuracy of the Qscat-1 model by using some SeaWinds Level 2 data and corresponding buoy data. First, a comparison between L2B and co-located buoy wind speed was made to analyze the systematic bias between them, and then a new geophysical model function was established using the match-ups of the L2A and Buoy data to further valuate the accuracy of the Qscat-1 model. The analytical and modeling results indicate that there may be some systematic error in the Qscat-1 model.

This paper presents a novel method for multispectral aerial image registration. Different bands of multispectral images taken by non-coaxial multispectral camera system usually cannot overlap accurately due to the non-coaxiality of the camera system and assembly error. Therefore, image registration is required. There are three problems in image registration of different bands. First, similarity between different bands is rather poor, which makes control points selection difficult. Second, polynomial transform model is lack of imaging geometry foundation. Third, there is translation between different bands, which also causes difficulties for control points selection. The method presented in this paper solves these three problems preliminarily. Finally, we validated this novel method using real multispectral images.

The water vapour in troposphere has been identified as one of the major errors in SAR interferograms, which can cause a spatial delay during two non-simultaneous acquisitions. The microwave-signal propagation path delay due to water vapour may reduce the reliability of deformation measurements. In this paper, it aims to assess the water vapour effect on interferograms, and apply synchronous MERIS data to reduce the effect on ASAR interferograms. Due to the co-existence of MERIS and ASAR on board of ENVISAT satellite, they can acquire data co-located in the same time and space. So it has a unique advantage to combine MERIS and ASAR data to reduce the tropospheric water vapour effect on ASAR interferograms. However, the method is not so well operational, and still existing some problems need to be further discussed, such as: how to deal with the cloud coverage over MERIS water vapour image; and how to register MERIS to ASAR from different reference systems, and so on. These will be discussed in this paper, and novel ideas are proposed to deal with them. The discussions are based on the application of the test site in the middle and lower reaches of Yangze River, southwest Hubei province, China.

Phase unwrapping is the most difficult and unavoidable problem in the interferometric synthetic aperture radar (InSAR) processing procedures. Intensive researches have been done and the methods proposed were summarized into two categories: path following and minimum norm. Unwrapping result by path following is congruent with wrapped phase and require less time and memory. While minimum norm method usually could not obtain congruent result directly and take more computing resource. Weighting could improve phase unwrapping result very much if the suspicious region could be correctively separated out by weighting function. However, common used weighting such as coherence or phase gradient could not serve this purpose very well. In this paper, we proposed a novel method to unwrap phase, which combined the advantages of both categories, and set weight based on phase unwrapping consistence. We demonstrated the method with real InSAR phase. The unwrapping result showed the novel method could recover the dynamic range of phase than least square method while keep correct trend.

Measuring soil moisture is very important for monitoring global water cycle. In past years for more than two decades, measuring soil moisture by passive and active microwave remote sensing has been intensively researched. The significant advancements has been made in measuring soil moisture in bare soil field or less vegetation covered region. To measure soil moisture with vegetation cover, vegetation emissivity and opacity have to be included as two parameters to character radiation in vegetation layer. In this paper, we review the phenomenological model to treat radiation transfer in media comprised of vegetation and underlying soil surface. And then simulation of vegetation emissivity and opacity based on radiation transfer theory and combined with input of geometrical parameters and water content measured in winter wheat field was presented. Finally, the relationships between them, in particular of different frequencies and polarization, were been dug out and examined.