Haoyang Fu

Land Salinization Classification Method using Landsat TM in Western Jilin Province of China

In the study of land salinization classification, researchers are most concerned about the distribution, area and degree of salinization. Traditional classification methods of land salinization only manually extract the sample data from the study area, which cannot obtain the classification results for large area. With the development of remote sensing technology, remote sensing data is often used to extract and analyze the information of saline-alkali soil. At present, most classification methods of land salinization utilize the spectral information of remote sensing data based on supervised classification or unsupervised classification, which still have some errors in the classification results. Combining the sample data with Landsat TM images, the Western Jilin Province of China was selected as the study area in this paper. Through analyzing the relationship between the spectral characteristics and the content of soil salinity of the sample data extracted from different types of saline-alkali land, a land salinization classification method using the decision tree was proposed. The experimental results demonstrated that the proposed method can supply more accurate classification information of land salinization, and further effectively monitor soil salinization changes for the study area.

Super-resolution algorithm based on sparse representation and wavelet preprocessing for remote sensing imagery

Abstract. An effective super-resolution (SR) algorithm is proposed for actual spectral remote sensing images based on sparse representation and wavelet preprocessing. The proposed SR algorithm mainly consists of dictionary training and image reconstruction. Wavelet preprocessing is used to establish four subbands, i.e., low frequency, horizontal, vertical, and diagonal high frequency, for an input image. As compared to the traditional approaches involving the direct training of image patches, the proposed approach focuses on the training of features derived from these four subbands. The proposed algorithm is verified using different spectral remote sensing images, e.g., moderate-resolution imaging spectroradiometer (MODIS) images with different bands, and the latest Chinese Jilin-1 satellite images with high spatial resolution. According to the visual experimental results obtained from the MODIS remote sensing data, the SR images using the proposed SR algorithm are superior to those using a conventional bicubic interpolation algorithm or traditional SR algorithms without preprocessing. Fusion algorithms, e.g., standard intensity-hue-saturation, principal component analysis, wavelet transform, and the proposed SR algorithms are utilized to merge the multispectral and panchromatic images acquired by the Jilin-1 satellite. The effectiveness of the proposed SR algorithm is assessed by parameters such as peak signal-to-noise ratio, structural similarity index, correlation coefficient, root-mean-square error, relative dimensionless global error in synthesis, relative average spectral error, spectral angle mapper, and the quality index Q4, and its performance is better than that of the standard image fusion algorithms.

Influence of tailed-current on UXO prospecting

Time-domain electromagnetic method used in unexploded ordnance (UXO) detection has always faced the problem of the losing of early-time response due to tailed-current. In this article, the response of UXO like targets with different tailed-current are calculated and measured, and the influence of tailed-current on UXO prospecting is talked. The targets include a sphere, an iron pipe and a shell, and the tailed-current is set with switch-off time varies from 0μs to 230μs. According to magnetic surface modes(MSM), the step response of a compact steel target exhibits an early algebraic regime wherein the response transitions from t-1/2 to t-3/2 decay, followed by a late regime characterized by an exponentially decay. In fact, the transmitter current cannot be turned off immediately, especially for system with multiturn coil and large current. The switch-off process is decided by system parameters such as coil induction, coil resister, damping resister and maximum voltage across the coil. The response of the targets will be distorted dramatically by the tailed-current. The targets responses of tailed-current with different switch-off time are calculated through a convolution algorithm and measured with a specially designed system. The results show that the responses of UXO like targets are influenced by the tailed-current in two ways. Firstly, the primary response of the tailed-current will lead to signal saturation in the early times. Secondly, the off-time responses of UXO like targets are distorted by the tailed-current. All the influences will affect the system ability on detecting and discriminating the UXO like targets. An extra-fast switch-off system and deconvolution strategies are good advices to solve the problems.

Salinity and soil moisture retrieval algorithms in western Jilin Province of China using passive microwave remote sensing data

Researches on soil moisture and salinity are mainly concerned in the observation of soil salinization. Passive microwave remote sensing data can reflect the dielectric properties of different land surfaces. Meanwhile, soil dielectric properties have high sensitivity to changes of soil moisture and salinity. As a result, passive microwave remote sensing data can be used for retrieval of surface soil moisture and salinity. Western Jilin Province of China was selected as the study area in this paper. By the iteration between the rough surface reflectivity calculated based on satellite data and the rough surface reflectivity calculated based on land surface model, three parameters, including surface roughness parameter, soil moisture and salinity can be retrieved simultaneously. After comparing the retrieval results to the field measurement of salinity and FY satellite soil moisture product, the experimental results show that the surface roughness parameters of the study area were concentrated in the vicinity of 0.31. The error between the average of retrieved salinity and the average of the field measurement of salinity was about 10.52g/kg. The error between the average of retrieved soil moisture and the average of FY satellite soil moisture product was approximately 0.005cm3/cm3.

Noise characteristics research of Overhauser magnetometer sensor

Overhauser magnetometer, a kind of weak-magnetic measurement system based on the Overhauser effect, has been widely used in satellite magnetic survey, aeromagnetic survey and other engineering and environmental applications. Overhauser magnetometer plays an important role in the application of magnetic field measurement for its advantages of low power consumption and high accuracy. Weak field magnetic resonance is usually limited by the signal to noise ratio (SNR). In order to improve the SNR of Overhauser magnetometer, noise characteristics of Overhauser magnetometer sensor are investigated in this paper. A background noise model of Overhauser magnetometer sensor is presented. The calculated results indicate that the noise power spectral density shows a band-limited white noise characteristic. The maximum value of the noise power spectral density observed at the resonant frequency. The measured results coincide with the calculated results. The correlation between the SNR and the matched resistance is investigated by using the noise model. The calculated results demonstrate that large matched resistance is beneficial to improve the SNR of the sensor. When matched resistance is larger than 100kΩ, the SNR tends to be a constant. On the premise of stability, the sensor will achieve the optimal SNR when the matched resistance is around 100kΩ. This investigation is beneficial to improve noise performance of Overhauser magnetometer sensor.

An improved RF circuit for Overhauser magnetometer excitation

Overhauser magnetometer is a high-precision device for magnetostatic field measurement, which can be used in a wide variety of purposes: UXO detection, pipeline mapping and other engineering and environmental applications. Traditional proton magnetometer adopts DC polarization, suffering from low polarization efficiency, high power consumption and low signal noise ratio (SNR). Compared with the traditional proton magnetometer, nitroxide free radicals are used for dynamic nuclear polarization (DNP) to enhance nuclear magnetic resonance (NMR). RF excitation is very important for electron resonance in nitrogen oxygen free radical solution, and it is primarily significant for the obtention of high SNR signal and high sensitive field observation. Therefore, RF excitation source plays a crucial role in the development of Overhauser magnetometer. In this paper, an improved design of a RF circuit is discussed. The new RF excitation circuit consists of two parts: Quartz crystal oscillator circuit and RF power amplifier circuit. Simulation and optimization designs for power amplifier circuit based on software ADS are presented. Finally we achieve a continuous and stable sine wave of 60MHz with 1-2.5 W output power, and the second harmonic suppression is close to -20dBc. The improved RF circuit has many merits such as small size, low-power consumption and high efficiency, and it can be applied to Overhauser magnetometer to obtain high sensitive field observation.

An improved proton magnetometer for Earth's magnetic field observation

As a precision instrument to measure the earth magnetic field, proton magnetometer is widely used in different fields such as geological survey, buried objects detection and earth field variations. Due to poor signal to noise ratio (SNR) of the system, proton magnetometer suffers from low sensitivity which directly affects the performance. In order to increase the sensitivity, we present an improved proton magnetometer. First, the effect of matching resistance on Q value is discussed to enhance SNR, and high matching resistance has been chosen to improve the Q value of the resonant circuit. Second, noise induced by pre-amplifier is investigated in order to obtain low noise signal, and we adopt the JFET with noise figure less than 0.5dB as the pre-amplifier. Third, by using band-pass filter, low-noise output signal is obtained. Fourth, the method of period measurement based on CPLD is employed to measure frequency of the square wave shaped from the output sinusoidal signal. High precision temperature compensate crystal oscillator (TCXO) has been used to improve the frequency measurement accuracy. Last, experimental data is obtained through field measurements. By calculating the standard deviation, the sensitivity of the improved proton magnetometer is 0.15nT for Earth’s magnetic field observation. Experimental results show that the new magnetometer is sensitive to earth field measurement.