Xiaojie Li

Evaluation and Improvement of SMOS and SMAP Soil Moisture Products for Soils with High Organic Matter over a Forested Area in Northeast China

Soil moisture (SM) retrieval from SMOS (the Soil Moisture and Ocean Salinity mission) and SMAP (the Soil Moisture Active/Passive mission) passive microwave data over forested areas with required accuracy is of great significance and poses some challenges. In this paper, we used Ground Wireless Sensor Network (GWSN) SM measurements from 9 September to 5 November 2015 to validate SMOS and SMAP Level 3 (L3) SM products over forested areas in northeastern China. Our results found that neither SMOS nor SMAP L3 SM products were ideal, with respective RMSE (root mean square error) values of 0.31 cm3/cm3 and 0.17 cm3/cm3. Nevertheless, some improvements in SM retrieval might be achievable through refinements of the soil dielectric model with respect to high percentage of soil organic matter (SOM) in the forested area. To that end, the potential of the semi-empirical soil dielectric model proposed by Jun Liu (Liu’s model) in improving SM retrieval results over forested areas was investigated. Introducing Liu’s model into the retrieval algorithms of both SMOS and SMAP missions produced promising results. For SMAP, the RMSE of L3 SM products improved from 0.16 cm3/cm3 to 0.07 cm3/cm3 for AM (local solar time around 06:00 am) data, and from 0.17 cm3/cm3 to 0.05 cm3/cm3 for PM (local solar time around 06:00 pm) data. For SMOS ascending orbit products, the accuracy was improved by 56%, while descending orbit products improved by 45%.

Quantitative analysis of relationships between crack characteristics and properties of soda-saline soils in Songnen Plain, China

The Songnen Plain has a typical soda-saline soil, which often shrinks and cracks under natural conditions during water evaporation. This study aims to analyze the relationships between the crack characteristics and the soil properties of soda-saline soils quantitatively, and attempts to establish prediction models for the main soil properties of soda-saline soils based on the results. In order to achieve these objectives, a desiccation cracking test was conducted using 17 soil specimens with different salinity levels under controlled laboratory conditions. Correlation analysis was then performed between the crack characteristics and the soil properties. The results indicate that the crack characteristics can well represent the surface appearances of cracked soils, they also can well distinguish the salinity levels of soda-saline soils while the clay contents and mineralogical compositions of soils are stable. Among the crack characteristics, crack length has the best relationships with the salinity levels of soda-saline soils. Specifically, the crack length has high correlation (R2 > 0.87) with the electrical conductivity (EC), Na+, CO32– and the salinity, it also has reasonable relationship (R2 > 0.68) with HCO3–, this indicates crack length can be well used for the prediction of these properties of soda-saline soils.

Massively Parallel GPU Design of Automatic Target Generation Process in Hyperspectral Imagery

A popular algorithm for hyperspectral image interpretation is the automatic target generation process (ATGP). ATGP creates a set of targets from image data in an unsupervised fashion without prior knowledge. It can be used to search a specific target in unknown scenes and when a targets size is smaller than a single pixel. Its application has been demonstrated in many fields including geology, agriculture, and intelligence. However, the algorithm requires long time to process due to the massive amount of data. To expedite the process, the graphics processing units (GPUs) are an attractive alternative in comparison with traditional CPU architectures. In this paper, we propose a GPU-based massively parallel version of ATGP, which provides real-time performance for the first time in the literature. The HYDICE image data (307 * 307 pixels and 210 spectral bands) are used for benchmark. Our optimization efforts on the GPU-based ATGP algorithm using one NVIDIA Tesla K20 GPU with I/O transfer can achieve a speedup of 362× with respect to its single-threaded CPU counterpart. We also tested the algorithm on Airborne Visible/InfraRed Imaging Spectrometer (AVIRIS) WTC dataset (512 * 614 * 224 of 224 bands) and Cuprite dataset (35 * 350 * 188 of 188 bands), the speedup was 416× and 320×, respectively, when the target number was 15.

Fast computation of bare soil surface roughness on a Fermi GPU

Surface roughness is an important factor in bare soil microwave radiation for the observation of the Earth. Correlation length and standard deviation of surface height are the two statistical parameters that describe surface roughness. However, when the number of data points is large, the calculation of surface roughness parameters becomes time-consuming. Therefore, it is desired to have a high-performance computing facility to execute this task. A Graphics Processing Unit (GPU) provides hundreds of computing cores along with a high memory bandwidth. To carry out a parallel implementation of the algorithms, Compute Unified Device Architecture (CUDA) provides researchers with an easy way to execute multiple threads in parallel on GPUs. In this paper, we propose a GPU-based parallel computing method for 2D surface roughness estimation. We use an NVIDIA GeForce GTX 590 graphics card to run the CUDA implementation. The experimental input data is collected by our in-house surface roughness tester which is designed based on the laser triangulation principle, giving sample data points of up to 52,040. According to the experimental results, the serial CPU version of the implementation takes 5422s whereas our GPU implementation takes only 47s, resulting a significant 115× speedup. A parallel computing method for 2D surface roughness was implemented by CUDA GPU API.The experimental input data is collected by our in-house surface roughness tester.A significant 115x speedup was achieved for the GPU implementation compare with CPU.

Massive Parallelization of the WRF GCE Model Toward a GPU-Based End-to-End Satellite Data Simulator Unit

Modern weather satellites provide more detailed observations of cloud and precipitation processes. To harness these observations for better satellite data assimilations, a cloud-resolving model, known as the Goddard Cumulus Ensemble (GCE) model, was developed and used by the Goddard Satellite Data Simulator Unit (G-SDSU). The GCE model has also been incorporated as part of the widely used weather research and forecasting (WRF) model. The computation of the cloud-resolving GCE model is time-consuming. This paper details our massively parallel design of GPU-based WRF GCE scheme. With one NVIDIA Tesla K40 GPU, the GPU-based GCE scheme achieves a speedup of 361× as compared to its original Fortran counterpart running on one CPU core, whereas the speedup for one CPU socket (four cores) with respect to one CPU core is only 3.9×.

Auto-calibration of a Laser 3D Color Digitization System

A typical 3D color digitization system is composed of 3D sensors to obtain 3D information, and color sensors to obtain color information. Sensor calibration plays a key role in determining the correctness and accuracy of the 3D color digitization data. In order to carry out the calibration quickly and accurately, this paper introduces an automated calibration process which utilizes 3D dynamic precision fiducials, with which calibration dot pairs are extracted automatically, and as the corresponding data are processed via a calibration algorithm. This automated was experimentally verified to be fast and effective. Both the 3D information and color information are extracted such that the 3D sensors and the color sensors are calibrated with one automated calibration process. We believe it is the first such calibration process for a 3D color digitization system.

A vehicle-borne and line-structure laser based two-dimensional surface roughness measurement instrument

Surface roughness is the description of surface irregularity and micro topographic randomness. It is an important factor affecting soil microwave radiation. Since both the microwave radiometer and radar detector measure a plane, using 3D data to calculate the 2D surface roughness will get better results. In this paper, we present a line-structure laser based vehicle-borne 2D surface roughness measurement instrument which can measure a much bigger size and thus bring higher accuracy and greater capability. Meanwhile, the portability is not affected since it is carried around by a vehicle. The precision test and field test showed that the maximum average relative error is only 1.3%. We also implemented a graphics processing unit version of the data processing program, which reduced the runtime to 540 seconds from 45,393 seconds on central processing unit.

Correction of World Coordinate Error in the Three-Dimensional Laser Scanning System of Human Body

This paper studies three-dimensional laser scanning system of human body, and make adjustments according to the world coordinate error correction based on the point cloud obtained. This paper also analyzed the cause and characteristics of three-dimensional laser scanning system’s world coordinates error, and established the world coordinate correction model on the condition that vertical column coordinate error is not included in the calibration plane and the error is minimum relative to other highly cross-section. With a standard rectangular timber as the scan objects, correction factor is fitted and the effectiveness of this method is proved through experiments in which point cloud’s world coordinate error is significantly reduced.

Size measurement of standing and sitting position based on human animation

A method of measuring the key sizes of a human 3D mesh model was presented. In the proposed method, human model postures were adjusted according to the measuring reference plane, measuring direction and measuring points. Then the skeleton of the model was extracted through the gradient rapid descent algorithm of the radial base function. What follows was to locate the joints and set their freedom and active ranges. Then, the surface peaks were bonded to the joints through flexible models to implement human animation. In this way, the standing and sitting poses were obtained. After automatic means of body characteristic points location had been studied, the points and plane were extracted to locate the measuring points precisely. Experiments were carried out on a man respectively and their key sizes were shown.

Low-density microporous polymeric foams measurement with digital microscopic image plane holography

A method for the measurement of low-density microporous polymeric foams with digital microscopic image plane holography is studied. An image plane hologram of microporous foam is recorded in an optical system of a Mach-Zender interferometer by CCD sensor, and the magnified image, which contains the quantitative information of the intensity and the phase of the microporous foam, is reconstructed numerically from the captured single interference pattern by twice fast Fourier transform and digital filter processing of frequency spectrum. And the morphometry and the pore diameter of the microporous foam under test can be obtained. A theoretical analysis has been performed and experimental results of the polymeric foam are also given. The experimental results show that the method presented in this paper is feasible, easy in data processing.