Chisheng Wang

An Improved Method for Power-Line Reconstruction from Point Cloud Data

This paper presents a robust algorithm to reconstruct power-lines using ALS technology. Point cloud data are automatically classified into five target classes before reconstruction. In order to improve upon the defaults of only using the local shape properties of a single power-line span in traditional methods, the distribution properties of power-line group between two neighbor pylons and contextual information of related pylon objects are used to improve the reconstruction results. First, the distribution properties of power-line sets are detected using a similarity detection method. Based on the probability of neighbor points belonging to the same span, a RANSAC rule based algorithm is then introduced to reconstruct power-lines through two important advancements: reliable initial parameters fitting and efficient candidate sample detection. Our experiments indicate that the proposed method is effective for reconstruction of power-lines from complex scenarios.

InSAR Coherence Estimation for Small Data Sets and Its Impact on Temporal Decorrelation Extraction

A novel coherence estimation method for small data sets is presented for interferometric synthetic aperture radar (SAR) (InSAR) data processing and geoscience applications. The method selects homogeneous pixels in both the spatial and temporal spaces by means of local and nonlocal adaptive techniques. Reliable coherence estimation is carried out by using such pixels and by correcting the bias in the estimated coherence caused by the non-Gaussianity in high-resolution SAR scenes. As an example, the proposed method together with coherence decomposition is applied to extract the temporal decorrelation component over an area in Macao. The results show that the proposed algorithms work well over various types of land cover. Moreover, the coherence change with time can be more accurately detected compared to other conventional methods.

The Improvement for Baran Phase Filter Derived From Unbiased InSAR Coherence

We present an improvement for the adaptive Gold-stein phase filter guided by interferometric synthetic aperture radar (InSAR) coherence (Baran phase filter). The proposed method addresses the under-filtering over incoherent area where the filter parameter alpha is underestimated by the biased coherence estimation. Through correcting the overestimate of the sample coherence, the correct filter parameter alpha is derived and the performance of the filter is optimized. Experimental results from different data sets demonstrate the advantages of the approach.

Equation-Based InSAR Data Quadtree Downsampling for Earthquake Slip Distribution Inversion

Downsampling is a routine step before applying interferometric synthetic aperture radar (InSAR) data to earthquake inversion because of the high computational burden. In this letter, we make use of the matrix perturbation theory to describe the downsampling process, which is considered as matrix perturbation on inversion equation. First, we derive a formula to quantitatively assess the perturbation on the inversion solution caused by data downsampling. Next, we propose an equation-based InSAR data downsampling algorithm to better reduce the perturbation. The experiment with simulated data demonstrates that our new algorithm preserves the most details from full data inversion comparing with previous algorithms. Finally, we use our method to study the slip distribution of the 2008 Mw 6.3 Dangxiong earthquake.

Formation of the 2015 Shenzhen landslide as observed by SAR shape-from-shading

The time-series topography change of a landfill site before its failure has rarely been surveyed in detail. However, this information is important for both landfill management and early warning of landslides. Here, we take the 2015 Shenzhen landslide as an example, and we use the radar shape-from-shading (SFS) technique to retrieve time-series digital elevation models of the landfill. The results suggest that the total filling volume reached 4,074,300 m3 in the one and a half years before the landslide, while 2,817,400 m3 slid down in the accident. Meanwhile, the landfill rate in most areas exceeded 2 m/month, which is the empirical upper threshold in landfill engineering. Using topography captured on December 12, 2015, the slope safety analysis gives a factor of safety of 0.932, suggesting that this slope was already hazardous before the landslide. We conclude that the synthetic aperture radar (SAR) SFS technique has the potential to contribute to landfill failure monitoring.

A Stochastic Geometry Method for Pylon Reconstruction from Airborne LiDAR Data

Object detection and reconstruction from remotely sensed data are active research topic in photogrammetric and remote sensing communities. Power engineering device monitoring by detecting key objects is important for power safety. In this paper, we introduce a novel method for the reconstruction of self-supporting pylons widely used in high voltage power-line systems from airborne LiDAR data. Our work constructs pylons from a library of 3D parametric models, which are represented using polyhedrons based on stochastic geometry. Firstly, laser points of pylons are extracted from the dataset using an automatic classification method. An energy function made up of two terms is then defined: the first term measures the adequacy of the objects with respect to the data, and the second term has the ability to favor or penalize certain configurations based on prior knowledge. Finally, estimation is undertaken by minimizing the energy using simulated annealing. We use a Markov Chain Monte Carlo sampler, leading to an optimal configuration of objects. Two main contributions of this paper are: (1) building a framework for automatic pylon reconstruction; and (2) efficient global optimization. The pylons can be precisely reconstructed through energy optimization. Experiments producing convincing results validated the proposed method using a dataset of complex structure.

Mitigating Ionospheric Artifacts in Coseismic Interferogram Based on Offset Field Derived From ALOS-PALSAR Data

Ionospheric total electron content (TEC) disturbances can seriously influence the signal of low-frequency spaceborne synthetic aperture radar (SAR) systems, e.g., Advanced Land Observation Satellite (ALOS)-phased array-type L-band synthetic aperture radar (PALSAR). With regard to coseismic studies using interferometric synthetic aperture radar (InSAR), it is vital to mitigate the ionospheric artifacts in the contaminated coseismic interferogram. In this paper, we propose a new method for the integral constant calculation, and we then aim to improve the estimation of the ionospheric phase screen (IPS). The proposed method is based on both azimuth and range displacement field maps. At present, the azimuth displacement field can be generated by an offset-tracking procedure or multiple-aperture InSAR (MAI), but the range displacement field can only be estimated by an offset-tracking procedure. We applied ALOS-PALSAR data that were acquired before and after the 2008 Wenchuan earthquake and the 2010 Darfield earthquake to test the proposed method. This case study further showed that ionospheric azimuth streaks were clearly visible in the azimuth displacement field maps of these two cases, one of which was generated using the MAI algorithm and the other using an offset-tracking algorithm. The results confirmed that the long-wavelength ionospheric artifacts in the non-coseismic regions could be corrected by the use of the proposed method. The line-of-sight (LOS) displacement corrections of these two cases, Wenchuan and Darfield, were in the range of -35.9 to 21.0 cm and -6.6 to 10.0 cm along the LOS direction, respectively.

An Improved Quadrilateral Fitting Algorithm for the Water Column Contribution in Airborne Bathymetric Lidar Waveforms

In this paper, an improved method based on a mixture of Gaussian and quadrilateral functions is presented to process airborne bathymetric LiDAR waveforms. In the presented method, the LiDAR waveform is fitted to a combination of three functions: one Gaussian function for the water surface contribution, another Gaussian function for the water bottom contribution, and a new quadrilateral function to fit the water column contribution. The proposed method was tested on a simulated dataset and a real dataset, with the focus being mainly on the performance of retrieving bottom response and water depths. We also investigated the influence of the parameter settings on the accuracy of the bathymetry estimates. The results demonstrate that the improved quadrilateral fitting algorithm shows a superior performance in terms of low RMSE and a high detection rate in the water depth and magnitude retrieval. What’s more, compared with the use of a triangular function or the existing quadrilateral function to fit the water column contribution, the presented method retrieved the least noise and the least number of unidentified waveforms, showed the best performance in fitting the return waveforms, and had consistent fitting goodness for all different water depths.

A Triangular Prism Spatial Interpolation Method for Mapping Geological Property Fields

Abstract: The spatial interpolation of property fields in 3D, such as the temperature, salinity, and organic content of ocean water, is an active area of research in the applied geosciences. Conventional interpolation methods have not adequately addressed anisotropy in these data. Thus, in our research we considered two interpolation methods based on a triangular prism volume element, as a triangular prism structure best represents directivity, to express the anisotropy inherent in geological property fields. A linear triangular prism interpolation is proposed for layered stratum that achieves a complete continuity based on the volume coordinates of the triangular prism. A triangular prism quadric interpolation (a unit function of a triangular prism spline with 15 nodes) is designed for a smooth transition between adjacent triangular prisms with approximately continuity, expressing the continuity of the entire model. We designed a specific model which accounts for the different spatial correlations in three dimensions. We evaluated the accuracy of our proposed linear and triangular prism quadric interpolation methods with traditional inverse distance weighting (IDW) and kriging interpolation approaches in comparative experiments. The results show that, in 3D geological modeling, the linear and quadric triangular prism interpolations more accurately represent the changes in the property values of the layered strata than the IDW and kriging interpolation methods. Furthermore, the triangular prism quadric interpolation algorithm with 15 nodes outperforms the other methods. This study of triangular prism interpolation algorithms has implications for the expression of data fields with 3D properties. Moreover, our novel approach will contribute to spatial attribute prediction and representation and is applicable to all 3D geographic information; for example, in studies of atmospheric circulation, ocean circulation, water temperature, salinity, and three-dimensional pollutant diffusion.

Using an Integer Least Squares Estimator to Connect Isolated InSAR Fringes in Earthquake Slip Inversion

Coherence loss is a critical issue in interferometric synthetic aperture radar geodesy, particularly when short-wavelength radar images are used to monitor earthquake deformation, and it may result in isolated fringes in an interferogram. The conventional unwrapping algorithms may incompletely unwrap or wrongly estimate the integer jumps between isolated fringes. In this paper, we propose a novel method to connect the isolated fringes in earthquake slip inversion. We use multiple starting points to unwrap the interferogram and then solve the integer ambiguities among the starting points by a dislocation-model-based integer least squares estimator. This estimator allows us to provide a quantitative evaluation of the reliability of the integer solutions in terms of two indicators (the success rate and residual ratio). The algorithm is robust to a certain degree of data noise and fault geometry error, as tested. Simulated experiments and case studies demonstrate that the proposed method can give better unwrapping results than the conventional approaches such as the minimum-cost flow (MCF), statistical-cost network-flow algorithm for phase unwrapping (SNAPHU), and iterative forms of MCF and SNAPHU with the assistance of a slip model. The earthquake slip inversion therefore benefits from the more accurate unwrapping results.