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Building collapse arising from destructive earthquakes is often the primary cause of casualties and economic loss. Building damage assessment is one of the top priorities in earthquake emergency work. Quad-polarimetric synthetic aperture radar (PolSAR) data not only have the advantages of radar imaging being neither exposed to sunlight nor blocked by clouds, but also contain the most abundant information of the four polarimetric channels. Only using conventional polarimetric decomposition methods may lead to overestimations of the number of collapsed buildings and the exaggeration of the degree of earthquake damage. We proposed a parameter called the sector texture feature of the Fourier amplitude spectrum (STFFAS) to describe frequency-domain texture features based on the Fourier amplitude spectrum in order to solve the overestimation of earthquake building damage. In addition, we proposed a scheme to recognize building earthquake damage using only a single post-earthquake PolSAR image combined with STFFAS and the improved Yamaguchi four-component decomposition method. The 4.14 Ms7.1 Yushu earthquake that occurred in Yushu County, China, in 2010 is taken as the experimental case. Compared with conventional polarimetric decomposition methods, this method successfully separated 70.18% of standing buildings from the ground objects mixed with collapsed buildings, thus significantly improving the extraction accuracy and reliability of building earthquake damage information. [ABSTRACT FROM AUTHOR]

The influence of soil properties on spatial yield variability of potato (Solanum tuberosum L.) can be employed as a foundation for site-specific soil management. It is challenging to understand the mechanism of crop yield spatial variation. In this study, a Fourier transform-based spatial variation analysis method is proposed for potato yield. The current work investigated the relationship of soil properties (including texture, moisture, and nitrate-nitrogen) to the variability of potato yield on 28 ha center-pivot irrigated fields located in northwest China from 2015 to 2017. Statistics and geostatistics are applied to evaluate the spatial variability of potato yield and soil properties; correlation analysis, partial least squares regression (PLSR) and the Fourier transform-based spatial variation analysis method are applied to explore the driving factors of the spatial variability of potato yield. Compared with other soil factors, soil moisture content and potato yield had more similar spatial structure, with similar semi-variance model and parameters. A negative correlation between soil moisture content and yield has been found in the first two years. According to partial least squares regression (PLSR), soil properties can only explain 24%, 25%, and 3% of the potato yield variation in 2015, 2016, and 2017. However, the Fourier transform-based spatial variation analysis method indicated that about 80% of potato yield variation has been explained by soil texture (49%), soil moisture (30%), soil nitrate-nitrogen (10%), and other factors (10%). The contribution of multiple factors to yield spatial variation has been decomposed by the method based on Fourier transform. This method can be considered a new approach for studying spatial variation and a theoretical basis for precise field management. [ABSTRACT FROM AUTHOR]

The surface air temperature seasonal cycle in China has clearly changed in response to global warming, but its future projection has yet to be studied. Here, we investigate the performance and projection of the temperature seasonal cycle in China in 32 global climate models participating in the Coupled Model Intercomparison Project 6 (CMIP6). The characteristics of the temperature seasonal cycle, as represented by the amplitude and phase, are measured by the Fourier transform. The results show that the CMIP6 models can reasonably capture the observed typical temperature seasonal cycle feature with clear north–south gradients both for amplitude and phase in China. In the twenty‐first century, the models robustly project a delay in the phase across the whole country and a reduction in the amplitude in most of China relative to the reference period. Those changes are similar in the two shared socioeconomic pathway (SSP) scenarios, with overall larger magnitudes in the SSP5‐8.5 scenario than in the SSP2‐4.5 scenario. Projected amplitude changes are mainly linked to surface energy flux changes, especially latent heat flux changes. In response to future global warming, larger increases in the latent heat flux and thus stronger surface evaporative cooling lead to weaker surface warming in summer than in winter, contributing to a decrease in the amplitude of the temperature seasonal cycle in most regions of China. [ABSTRACT FROM AUTHOR]

Northern China is vigorously promoting cogeneration and clean heating technologies. The accurate prediction of building energy consumption is the basis for heating regulation. In this paper, the daily, weekly, and annual periods of building energy consumption are determined by Fourier transformation. Accordingly, a period-based neural network (PBNN) is proposed to predict building energy consumption. The main innovation of PBNN is the introduction of a new data structure, which is a time-discontinuous sliding window. The sliding window consists of the past 24 h, 24 h for the same period last week, and 24 h for the same period the previous year. When predicting the building energy consumption for the next 1 h, 12 h, and 24 h, the prediction errors of the PBNN are 2.30%, 3.47%, and 3.66% lower than those of the traditional sliding window PBNN (TSW-PBNN), respectively. The training time of PBNN is approximately half that of TSW-PBNN. The time-discontinuous sliding window reduces the energy consumption prediction error and neural network model training time. [ABSTRACT FROM AUTHOR]

The annual temperature cycle affects atmospheric circulation, biomass cycling, and human life. Its variation is influenced by surface solar radiation, which plays a key role in surface energy budgets. In this study, the Fourier transform method is used to analyse the spatial distribution and long‐term variations in temperature phase, amplitude, and baseline terms between 1960 and 2016 in China. Mean surface air temperature has a north–south gradient for phase, amplitude, and baseline. The regional mean phase values of the maximum, minimum, and mean temperatures in South China are larger than in North China, indicating that the timing of the annual cycle in Southern China is several days later than in Northern China. At the national scale, the annual maximum, minimum, and mean surface air temperature cycles are advancing, decreasing in range, and have a rising baseline. Linear regression is used to quantify the effect of surface solar radiation on temperature by removing its contribution on the raw maximum and mean temperatures. The surface solar radiation increases the phase of maximum and mean daily air temperatures, but reduces the amplitude and baseline. The surface solar radiation effect on maximum temperature is especially significant on the Yunnan‐Guizhou Plateau located in the south‐southwest. The phase of maximum temperature adjusted for solar radiation for the Plateau is similar to South China at the same latitude and later than the raw maximum temperature. [ABSTRACT FROM AUTHOR]

Terraces are important objects of soil and water conservation and land use surveys in the Loess Plateau and considerably impact soil erosion and agricultural production. Obtaining the spatial distribution of terraces has great significance for soil and water conservation research and government policy-making. A new method of terrace extraction was proposed in this study based on remote sensing images and digital elevation model (DEM) used as experimental data. The extraction method combines Fourier transform and digital terrain analysis. First, by analyzing the spatial and frequency domain characteristics of the terraced image, we determined the analysis window to be 50 × 50, whereas the area having a direction maximum energy value greater than 0.25 and image standard deviation greater than 2000 was considered as the terraced candidate. Then, the positive terrain was automatically extracted from the DEM based on the regional growth method, and the terraces on the positive terrain were obtained. After a series of morphological image processing methods were conducted, the final terraces were extracted. The results showed that the accuracy of drawing and user accuracy of terrace extraction were 79.0% and 73.5%, respectively. Compared with the object-oriented method, it was found that the proposed method was more reliable and accurate. This method developed in this study has the characteristics of simple operation, strong universality, and high precision and can be applied to soil and water conservation monitoring and land use surveys in the Loess Plateau. [ABSTRACT FROM AUTHOR]

The HJ-1A satellite was successfully launched on September 6, 2008. The inclusion of a HyperSpectral Imager (HSI) as one of the payloads of the HJ-1A Satellite is a major milestone in the field of the remote sensing in China. It is also the first Fourier transform imaging spectrometer routinely used to acquire scientific data from a satellite orbiting Earth. This paper briefly introduces the basic imaging theories of the spatially modulated Fourier transform imaging spectrometer, and then discusses the theoretical analysis and algorithms of spectrum reconstruction. Results of the operational spectrum reconstruction for the raw data of the HJ-1A satellite Fourier transform HSI are presented. At present, the algorithms and processing flow have been used successfully in the Ground Data Processing System (GDPS) built by the China Center for Resource Satellite Data and Applications (CRESDA). [ABSTRACT FROM AUTHOR]

Abstract: Crop identification is the basis of crop monitoring using remote sensing. Remote sensing the extent and distribution of individual crop types has proven useful to a wide range of users, including policy-makers, farmers, and scientists. Northern China is not merely the political, economic, and cultural centre of China, but also an important base for grain production. Its main grains are wheat, maize, and cotton. By employing the Fourier analysis method, we studied crop planting patterns in the Northern China plain. Then, using time-series EOS-MODIS NDVI data, we extracted the key parameters to discriminate crop types. The results showed that the estimated area and the statistics were correlated well at the county-level. Furthermore, there was little difference between the crop area estimated by the MODIS data and the statistics at province-level. Our study shows that the method we designed is promising for use in regional spatial scale crop mapping in Northern China using the MODIS NDVI time-series. [Copyright &y& Elsevier]

The 30° slanted axial-flow pump device is widely used in agricultural irrigation and urban drainage in plains areas of China. However, during the actual operation process, the 30° slanted axial-flow pump device is prone to vibration, noise, cracks in the blades, and other phenomena that affect the safe and stable operation of the pump device. In order to analyze the flow pressure pulsation characteristics of the 30° slanted axial-flow pump device under different flow conditions, the time–frequency domain analysis method was used to analyze the pressure pulsation of each flow structure of the 30° slanted axial-flow pump device. The results showed that the internal pulsation law of the elbow oblique inlet flow channel is similar. At the 1.2 Qbep condition, the amplitude fluctuation of the pressure pulsation was small, and the main frequency is 4 times the rotating frequency. The monitoring points at the outlet of the elbow oblique inlet flow channel were affected by the impeller rotation, and the pressure pulsation amplitude was larger than that inside the elbow oblique inlet flow channel. The pressure fluctuation of each monitoring point at the inlet surface of the impeller was affected by the number of blades. There were four peaks and four valleys, and the main frequency was 4 times the rotating frequency. The amplitude of pressure fluctuation increased gradually from the hub to the rim. The main frequency of pressure fluctuation at each monitoring point of the impeller outlet surface was 4 times of the rotating frequency, and the low frequency was rich. The amplitude of pressure fluctuation was significantly lower than that of the impeller inlet. With the increase of flow rate, the peak fluctuation of pressure coefficient decreased gradually, and the amplitude of pressure fluctuation tended to be stable. Under 0.8 Qbep and 1.0 Qbep conditions, the large fluctuation of the pressure fluctuation amplitude on the outlet surface of the guide vane was mainly affected by the low-frequency fluctuation. Under the 1.2 Qbep condition, the pressure fluctuation amplitude changed periodically. [ABSTRACT FROM AUTHOR]

Background: In this previous work, we investigated the secondary structure changes of stretched yak hairs by deconvolution, secondary derivation, and curve fitting and determined the number of bands and their positions in order to resolve the protein spectrum of Raman spectroscopy., Objectives: The secondary structure estimation and properties analysis of stretched Asian and Caucasian hair were investigated by Fourier transform infrared spectroscopy, tensile curves, and measurement of density., Methods: The hairs were stretched, dried, and baked at ratios 20%, 40%, 60%, 80% and 100%., Results: The analysis of the amide I band indicated that the transformation from α-helix to β-pleated structure occurred during the stretching process, which could be verified from the tensile analysis. The cysteine oxide in S-O vibration area exhibited that stretching led to the breakage of the disulfide bonds. When the stretching ratio of Caucasian hair was more than a certain ratio, the fiber macromolecular structure was destroyed because Caucasian hair had finer diameter and less medulla than Asian hair. The β turn was easier to retract compared with other conformations, resulted in the content increase. The density measurements revealed that the structure of Caucasian hair was indeed more destroyed than that of Asian hair. The cuticles characterization indicated the length of scales was stretched longer and the thickness became thinner. Caucasian hair tended to collapse to form small fragments at the early stage of stretching. With the increase in stretching ratio, the scales of Caucasian hair lifted up, then flaked off and the scale interval increased accordingly. Asian hair was more easily peeled off than Caucasian hair cuticles with the increase in stretching ratio., Conclusions: The secondary structure of Caucasian hair was destroyed more easily than that of Asian hair., (© 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

The high burden of syphilis in China presents a unique opportunity to examine temporal trends. This study used wavelet transformation and Fourier analysis to assess the presence of temporal oscillations in the incidence of syphilis among adults, gonorrhea, and congenital syphilis over 11 years in China's largest province. This study found a significant annual oscillation trend in the incidence of adult syphilis, consistent with a peak during July-September, which was 4-fold higher than the trough, which occurred during January-March. A similar but dampened trend was observed in the incidence of gonorrhea, and no trend was observed for the incidence of congenital syphilis. Further research on the temporal oscillation of the incidence of syphilis is needed.