Bangsen Tian

Large-Area Landslides Monitoring Using Advanced Multi-Temporal InSAR Technique over the Giant Panda Habitat, Sichuan, China

The region near Dujiangyan City and Wenchuan County, Sichuan China, including significant giant panda habitats, was severely impacted by the Wenchuan earthquake. Large-area landslides occurred and seriously threatened the lives of people and giant pandas. In this paper, we report the development of an enhanced multi-temporal interferometric synthetic aperture radar (MTInSAR) methodology to monitor potential post-seismic landslides by analyzing coherent scatterers (CS) and distributed scatterers (DS) points extracted from multi-temporal l-band ALOS/PALSAR data in an integrated manner. Through the integration of phase optimization and mitigation of the orbit and topography-related phase errors, surface deformations in the study area were derived: the rates in the line of sight (LOS) direction ranged from −7 to 1.5 cm/a. Dozens of potential landslides, distributed mainly along the Minjiang River, Longmenshan Fault, and in other the high-altitude areas were detected. These findings matched the distribution of previous landslides. InSAR-derived results demonstrated that some previous landslides were still active; many unstable slopes have developed, and there are significant probabilities of future massive failures. The impact of landslides on the giant panda habitat, however ranged from low to moderate, would continue to be a concern for conservationists for some time in the future.

Polarimetric analysis of multi-temporal RADARSAT-2 SAR images for wheat monitoring and mapping

A full understanding of the polarimetric characteristics of wheat fields is necessary for the development of a robust methodology for the monitoring and mapping of wheat using quad-polarimetric SAR images. In this study, the polarimetric characteristics and temporal variations of wheat were analysed using a multi-temporal RADARSAT-2 quad-polarimetric dataset from a wheat-growing region of the North China Plain. The backscattering coefficient, the Freeman–Durden decomposition, and the H/A/ decomposition were evaluated as functions of the growth stage and then used for classification. With each wheat growth stage, the volume scattering component ratio increased, whereas the surface scattering component ratio generally decreased. The experimental results indicate that the Freeman–Durden decomposition parameters are sensitive to the wheat growth stage. Moreover, the proposed method for mapping wheat, which combines the backscattering coefficients, polarization decompositions, and the support vector machine (hereafter referred to as BP-SVM), is able to discriminate wheat effectively, with an accuracy of up to 92.92%. This indicates that quad-polarimetric imagery from just one date is sufficient for wheat mapping. The results of this study demonstrate that quad-polarimetric RADARSAT-2 SAR imagery has great potential for the monitoring and mapping of wheat.

The backscattering characteristics of wetland vegetation and water-level changes detection using multi-mode SAR: A case study

Abstract A full understanding of the backscattering characteristics of wetlands is necessary for the analysis of the hydrological conditions. In this study, a temporal set of synthetic aperture radar (SAR) imagery, acquired at different frequencies, polarizations and incidence angles over the coastal wetlands of the Liaohe River Delta, China, were used to characterize seasonal variations in radar backscattering coefficient for reed marshes and rice fields. The combination of SAR backscattering intensity and an optical-based normalized difference vegetation index (NDVI) for long time series can provide additional insight into vegetation structural and its hydrological states. After identifying the factors that induce the backscattering and scattering mechanism changes, detailed analysis of L-band ALOS PALSAR interferometric SAR (InSAR) imagery was conducted to study water-level changes under different environmental conditions. In addition, ENVISAT altimetry was used to validate the accuracy of the water-level changes estimated using the InSAR technique—this is an effective tool instead of sparsely distributed gauge stations for the validation. Our study demonstrates that L-band SAR data with horizontal polarization is particularly suitable for the extraction of water-level changes in the study area; however, vertically-polarized C-band data may also be useful where the density of herbaceous vegetation is low at the initial stage. It is also shown that integrated analysis of the backscattering mechanism and interferometric characteristics using multi-mode SAR can considerably enhance the reliability of the water-level retrieval scheme and better capture the spatial distribution of hydrological patterns.

Glacier Snow Line Detection on a Polarimetric SAR Image

Synthetic aperture radar (SAR) can be used to distinguish areas of contrasting backscatter on glaciers and relate these areas to glacier facies. In the ablation season, there are two typical facies on temperate mountain glaciers: wet snow and ice. The boundary of wet snow and ice is defined as the transient snow line (TSL), which is an important concept in glaciology. In this letter, a new TSL detection method is proposed, in which the polarimetric SAR image is classified into three classes (wet snow, ice, and others) using support vector machines, and the boundary between wet snow and ice on the classification map is considered the TSL. The method is efficient and accurate and enables large-scale TSL observation. In our work, the TSL is extracted and analyzed on the long-observed Dongkemadi glacier using the proposed method. In addition, the method is applied on other neighboring glaciers to estimate their snow line altitude. On a regional scale, the TSL of the glacier group shows interesting phenomenon in the study area: The TSL altitude correlates closely with the orientation of the glaciers.

Mapping Thermokarst Lakes on the Qinghai–Tibet Plateau Using Nonlocal Active Contours in Chinese GaoFen-2 Multispectral Imagery

In order to monitor the response of thermokarst lakes on the Qinghai–Tibet Plateau (QTP) to rapid climatic changes and human activities, an automated method for extracting shorelines from Chinese GaoFen-2 (GF-2) imagery is proposed. First, the water index (WI) images and the potential lake areas are calculated from the preprocessed multispectral imagery and digital elevation model data, respectively. Second, the initial segmentation obtained by global thresholding of the WI images and masking in the potential lake areas are used to implement the contour initialization of active contours models efficiently. Finally, the nonlocal active contours (NLAC) approach is applied to refine the initial segmentation of the WI images, and the final shoreline vector files are produced by some simple and automatic postprocessing steps. Experiments on the GF-2 imagery demonstrate that 1) by exploiting the capability of WI to locate the approximate shoreline effectively around the evolving contour, the processing time of the proposed method can be saved significantly; 2) the NLAC approach can efficiently identify the shoreline by integrating the nonlocal interactions between pairs of patches inside and outside the lake; and 3) the proposed method can conveniently adapt to the multitemporal and multifeature image analysis. Using the manual digitized shorelines as the reference data, an average error of less than one pixel with standard deviation of 0.1320 can be obtained. These results prove that the proposed method is feasible for the identification and monitoring of thermokarst lakes on the QTP.

Permafrost environment monitoring on the Qinghai-Tibet Plateau using time series ASAR images

The permafrost in Qinghai-Tibet Plateau (QTP) has long been the focus of many researchers. In this study, we first use the method that integrates synthetic aperture radar (SAR) intensity and phase information to monitor permafrost environment in the Beiluhe Region, using time series advanced SAR images. The backscattering coefficients (σ0) and deformation were extracted for the main features, and the influences of meteorological conditions to them were also quantified. The results show that both the change in σ0 and surface deformation are closely related to the active layer, and the deformation is also affected by the permafrost table. First, over meadow and sparse vegetation regions, σ0 rose about 6.9 and 4 dB from the freezing to thawing period, respectively, which can be mainly attributed to the thaw of the active layer and increased precipitation. Second, seasonal deformation, derived from the freeze-thaw cycle of the active layer, was characteristic of frost heave and thaw settlement and exhibited a negative correlation with air temperature. Its magnitude was larger than 1 cm in a seasonal cycle. Last, significant secular settlement was observed, with rates ranging from –16 to 2 mm/a, and it was primarily due to the thaw of the permafrost table caused by climate warming.

Glacier Thickness Change Mapping Using InSAR Methodology

This letter presents a novel method for high-precision estimation of mountain glacier thickness change from the conventional interferometric synthetic aperture radar (InSAR) interferograms and multiaperture InSAR measurements. The method exploits the two components of displacement along the line of sight of radar beam and along track for deriving the glacier thickness change. To demonstrate the method, we estimate the glacier thickness change for the Dongkemadi Glacier in Tibet Plateau, China. The performance of this method is validated by field survey data. The results obtained with three InSAR pairs covering the Dongkemadi Glacier in the same seasons of three years show considerable spatial variability. The results in this study are, to our knowledge, the first ones with such a method, and they demonstrate the feasibility of the approach to obtain and analyze the mountain glacier thickness change.

A new SAR superresolution imaging algorithm based on adaptive sidelobe reduction

The paper provides an efficient extrapolation algorithm to enhance resolution as well as reduce sidelobes, which is based on ASR. The processing of algorithm is simple to operate. Simulation experiments show the validity of the algorithm. Comparing to the Fourier method, the proposed algorithm obtains better results.

A level set method for segmentation of high-resolution polarimetric SAR images using a heterogeneous clutter model

To overcome the problem of strong speckle and texture in high-resolution polarimetric synthetic aperture radar (PolSAR) images, a novel level set segmentation method that uses a heterogeneous clutter model is proposed in this article. Because the KummerU distribution has the capability to describe the statistics of PolSAR imagery in both homogeneous and heterogeneous scenes, it is used to replace the traditional Wishart distribution as the statistical model that defines the energy function for PolSAR images in order to improve the accuracy of the segmentation. Moreover, in order to reduce the computation intensity, an enhanced distance-regularized level set evolution (DRLSE-E) term is applied to improve the computational efficiency. The experimental results obtained using synthetic and real PolSAR images show that the method described has an accuracy 10% better than level set methods based on Wishart distributions. It is also shown that adding the DRLSE-E term reduces the computation time by about a third, thus demonstrating the effectiveness of our method.

Hemispheric-scale comparison of monthly passive microwave snow water equivalent products

Abstract The snow water equivalent (SWE) products from passive microwave remote sensing are useful in global climate change studies due to the long-time and all-weather imaging capabilities of passive microwave radiometry at the hemisphere scale. Northern Hemisphere SWE products, including products from the National Snow and Ice Data Center (NSIDC) and GlobSnow from the European Space Agency (ESA), have been providing long-time series information since 1979. However, the different algorithms used to produce the NSIDC and GlobSnow products lead to discrepancies in the data. To determine which product might be superior, this paper assesses their hemisphere-scale quality for the time period 1979−2010. By comparing the data with historical snow depth measurements obtained from 7388 meteorological stations in the Northern Hemisphere, the accuracies of the different SWE products are analyzed for the period and for different snow types. The results show that for SWEs above 30 mm but below 200 mm, GlobSnow estimates maintain a better linear relation with the ground measurements. NSIDC products are more influenced by microwave “saturation,” producing obvious underestimations for SWEs over 120 mm. However, for shallow snow (SWE less than 30 mm), the slight overestimate produced by GlobSnow is more obvious than that of the other NSIDC products.