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| 1 | Modeling spatio-temporal distribution of soil moisture by deep learning-based cellular automata model显示文摘Soil moisture content (SMC) is a key hydrological parameter in agriculture,meteorology and climate change,and understanding of spatio-temporal distributions of SMC in farmlands is important to address the precise irrigation scheduling.However,the hybrid interaction of static and dynamic environmental parameters makes it particularly difficult to accurately and reliably model the distribution of SMC.At present,deep learning wins numerous contests in machine learning and hence deep belief network (DBN) ,a breakthrough in deep learning is trained to extract the transition functions for the simulation of the cell state changes.In this study,we used a novel macroscopic cellular automata (MCA) model by combining DBN to predict the SMC over an irrigated corn field (an area of 22 km^2) in the Zhangye oasis,Northwest China.Static and dynamic environmental variables were prepared with regard to the complex hydrological processes.The widely used neural network,multi-layer perceptron (MLP) ,was utilized for comparison to DBN.The hybrid models (MLP-MCA and DBN-MCA) were calibrated and validated on SMC data within four months,i.e.June to September 2012,which were automatically observed by a wireless sensor network (WSN) .Compared with MLP-MCA,the DBN-MCA model led to a decrease in root mean squared error (RMSE) by 18%.Thus,the differences of prediction errors increased due to the propagating errors of variables,difficulties of knowing soil properties and recording irrigation amount in practice.The sequential Gaussian simulation (s Gs) was performed to assess the uncertainty of soil moisture estimations.Calculated with a threshold of SMC for each grid cell,the local uncertainty of simulated results in the post processing suggested that the probability of SMC less than 25% will be difference in different areas at different time periods.The current results showed that the DBN-MCA model performs better than the MLP-MCA model,and the DBN-MCA model provides a powerful tool for predicting SMC in highly non-linear forms.Moreover,because modeling soil moisture by using environmental variables is gaining increasing popularity,DBN techniques could contribute a lot to enhancing the calibration of MCA-based SMC estimations and hence provide an alternative approach for SMC monitoring in irrigation systems on the basis of canals. | SONG Xiaodong ZHANG Ganlin LIU Feng LI Decheng ZHAO Yuguo YANG Jinling | 2016 | Journal of Arid Land2016，8，5： | 20 |
| 2 | Vertical distribution and storage of soil organic and inorganic carbon in a typical inland river basin,Northwest China显示文摘Knowledge of soil carbon(C) distribution and its relationship with the environment can improve our understanding of its biogeochemical cycling and help to establish sound regional models of C cycling. However, such knowledge is limited in environments with complex landscape configurations. In this study, we investigated the vertical distribution and storage of soil organic carbon(SOC) and soil inorganic carbon(SIC) in the 10 representative landscapes(alpine meadow, subalpine shrub and meadow, mountain grassland, mountain forest, typical steppe, desert steppe, Hexi Corridor oases cropland, Ruoshui River delta desert, Alxa Gobi desert, and sandy desert) with contrasting bioclimatic regimes in the Heihe River Basin, Northwest China. We also measured the 87 Sr/86 Sr ratio in soil carbonate to understand the sources of SIC because the ratio can be used as a proxy in calculating the contribution of pedogenic inorganic carbon(PIC) to total SIC. Our results showed that SOC contents generally decreased with increasing soil depth in all landscapes, while SIC contents exhibited more complicated variations along soil profiles in relation to pedogenic processes and parent materials at the various landscapes. There were significant differences of C stocks in the top meter among different landscapes, with SOC storage ranging from 0.82 kg C/m^2 in sandy desert to 50.48 kg C/m^2 in mountain forest and SIC storage ranging from 0.19 kg C/m^2 in alpine meadow to 21.91 kg C/m^2 in desert steppe. SIC contributed more than 75% of total C pool when SOC storage was lower than 10 kg C/m^2, and the proportion of PIC to SIC was greater than 70% as calculated from Sr isotopic ratio, suggesting the critical role of PIC in the C budget of this region. The considerable variations of SOC and SIC in different landscapes were attributed to different pedogenic environments resulted from contrasting climatic regimes, parent materials and vegetation types. This study provides an evidence for a general trade-off pattern between SOC and SIC, showing the compensatory effects of environmental conditions(especially climate) on SOC and SIC formation in these landscapes. This is largely attributed to the fact that the overall decrease in temperature and increase in precipitation from arid deserts to alpine mountains simultaneously facilitate the accumulation of SOC and depletion of SIC. | YANG Fan HUANG Laiming YANG Renmin YANG Fei LI Decheng ZHAO Yuguo YANG Jinling LIU Feng ZHANG Ganlin | 2018 | Journal of Arid Land2018，10，2： | 4 |
| 3 | Mapping Soil Texture Based on Field Soil Moisture Observations at a High Temporal Resolution in an Oasis Agricultural Area显示文摘Due to the almost homogeneous topography in low relief areas, it is usually difficult to make accurate predictions of soil properties using topographic covariates. In this study, we examined how time series of field soil moisture observations can be used to estimate soil texture in an oasis agricultural area with low relief in the semi-arid region of northwest China. Time series of field-observed soil moisture variations were recorded for 132 h beginning at the end of an irrigation event during which the surface soil was saturated.Spatial correlation between two time-adjacent soil moisture conditions was used to select the factors for fuzzy c-means clustering. In each of the ten generated clusters, soil texture of the soil sample with the maximum fuzzy membership value was taken as the cluster centroid. Finally, a linearly weighted average was used to predict soil texture from the centroids. The results showed that soil moisture increased with the increase of clay and silt contents, but decreased with the increase of sand content. The spatial patterns of soil moisture changed during the entire soil drying phase. We assumed that these changes were mainly caused by spatial heterogeneity of soil texture. A total of 64 independent samples were used to evaluate the prediction accuracy. The root mean square error(RMSE)values of clay, silt and sand were 1.63, 2.81 and 3.71, respectively. The mean relative error(RE) values were 9.57% for clay, 3.77% for silt and 12.83% for sand. It could be concluded that the method used in this study was effective for soil texture mapping in the low-relief oasis agricultural area and could be applicable in other similar irrigation agricultural areas. | YANG Renmin LIU Feng ZHANG Ganlin ZHAO Yuguo LI Decheng YANG Jinling YANG Fei YANG Fan | 2016 | Pedosphere2016，26，5： | 3 |
| 4 | Nanoparticles-modified polymer-based solar-reflective coating as a cooling overlay for asphalt pavement显示文摘The phenomenon of rutting is one of the most serious problems on asphalt pavements.Decreasing the surface temperature of the asphalt pavement is an effective method to solve the rutting problem on asphalt pavements.In this study,a nano-sized-particlesfilled polymer composite was developed as an overlay to reflect solar energy and decrease the surface temperature of asphalt pavements.The overlay was composed of acrylic or epoxy resin filled with nano TiO_(2) or nano TiNO_(2).The solar reflection of the nanoparticle-filled polymers was tested,and the results showed that solar reflection effectiveness of the TiO_(2)/acrylic composite reached the highest value.The results of outdoor temperature tests indicate that the solar-reflective overlay could decrease the surface temperature of asphalt pavements by about 10℃ when the pavement temperature is about 60℃. | He Wang Jing Zhong Decheng Feng Jing Meng Ning Xie | 2013 | International Journal of Smart and Nano Materials2013，4，2： | 3 |
| 5 | Mapping Soil Organic Carbon Stocks of Northeastern China Using Expert Knowledge and GIS-based Methods显示文摘The main aim of this paper was to calculate soil organic carbon stock(SOCS) with consideration of the pedogenetic horizons using expert knowledge and GIS-based methods in northeastern China.A novel prediction process was presented and was referred to as model-then-calculate with respect to the variable thicknesses of soil horizons(MCV).The model-then-calculate with fixed-thickness(MCF),soil profile statistics(SPS),pedological professional knowledge-based(PKB) and vegetation type-based(Veg) methods were carried out for comparison.With respect to the similar pedological information,nine common layers from topsoil to bedrock were grouped in the MCV.Validation results suggested that the MCV method generated better performance than the other methods considered.For the comparison of polygon based approaches,the Veg method generated better accuracy than both SPS and PKB,as limited soil data were incorporated.Additional prediction of the pedogenetic horizons within MCV benefitted the regional SOCS estimation and provided information for future soil classification and understanding of soil functions.The intermediate product,that is,horizon thickness maps were fluctuant enough and reflected many details in space.The linear mixed model indicated that mean annual air temperature(MAAT) was the most important predictor for the SOCS simulation.The minimal residual of the linear mixed models was achieved in the vegetation type-based model,whereas the maximal residual was fitted in the soil type-based model.About 95% of SOCS could be found in Argosols,Cambosols and Isohumosols.The largest SOCS was found in the croplands with vegetation of Triticum aestivum L.,Sorghum bicolor(L.) Moench,Glycine max(L.) Merr.,Zea mays L.and Setaria italica(L.) P.Beauv. | SONG Xiaodong LIU Feng JU Bing ZHI Junjun LI Decheng ZHAO Yuguo ZHANG Ganlin | 2017 | Chinese Geographical Science2017，27，4： | 2 |
| 6 | Field monitoring of differential frost heave in widened highway subgrade显示文摘In cold regions,the widened subgrade could produce uneven frost heave that is detrimental to the pavement.This study investigates the differential frost heave characteristics in a widened subgrade.The field monitoring system mainly consists of temperature,moisture,and displacement sensors and distributed optical fiber cables for strain measurement.The monitoring results show that the cooling period in the subgrade is longer than the warming period.Water content in the subgrade changes significantly within 0−2 m below the subgrade surface but stabilizes within 2−5 m.The maximum frost heave occurs from February to March.In comparison,the existing subgrade has a longer freezing period and larger heave value,caused by the higher density and water content inside.Water in the existing subgrade migrates into the new one after widening,leading to frost heave reduction in the existing subgrade.Simultaneously,the traffic loads result in the consolidation of the new subgrade,thus reducing the heave value in the second year.In the third year,the water supply from the existing subgrade facilitates the frost heave in the new subgrade.The tensile strain distributions obtained by the distributed optical fiber cables show that the maximum differential frost heave occurs at the joint between the existing and new subgrades.The differential frost heave gradually stabilizes after three years.Finally,an improved frost heave prediction model is developed based on the segregation potential concept and monitoring results. | XuFeng Lu Feng Zhang KangWei Tang DeCheng Feng | 2021 | Research in Cold and Arid Regions2021，13，5： | 1 |
| 7 | Mapping Soil Organic Carbon Using Local Terrain Attributes: AComparison of Different Polynomial Models显示文摘Local terrain attributes,which are derived directly from the digital elevation model,have been widely applied in digital soil mapping.This study aimed to evaluate the mapping accuracy of soil organic carbon(SOC) concentration in 2 zones of the Heihe River in China,by combining prediction methods with local terrain attributes derived from different polynomial models.The prediction accuracy was used as a benchmark for those who may be more concerned with how accurately the variability of soil properties is modeled in practice,rather than how morphometric variables and their geomorphologic interpretations are understood and calculated.In this study,2 neighborhood types(square and circular) and 6 representative algorithms(Evans-Young,Horn,Zevenbergen-Thorne,Shary,Shi,and Florinsky algorithms) were applied.In general,35 combinations of first-and second-order derivatives were produced as candidate predictors for soil mapping using two mapping methods(i.e.,kriging with an external drift and geographically weighted regression).The results showed that appropriate local terrain attribute algorithms could better capture the spatial variation of SOC concentration in a region where soil properties are strongly influenced by the topography.Among the different combinations of firstand second-order derivatives used,there was a best combination with a more accurate estimate.For different prediction methods,the relative improvement in the two zones varied between 0.30% and 9.68%.The SOC maps resulting from the higher-order algorithms(Zevenbergen-Thorne and Florinsky) yielded less interpolation errors.Therefore,it was concluded that the performance of predictive methods,which incorporated auxiliary variables,could be improved by attempting different terrain analysis algorithms. | SONG Xiaodong LIU Feng ZHANG Ganlin LI Decheng ZHAO Yuguo YANG Jinling | 2017 | Pedosphere2017，27，4： | 1 |
| 8 | Recent developments in asphalt-aggregate separation technology for reclaimed asphalt pavement显示文摘Reclaimed asphalt pavement(RAP)has significant recycling value because it contains nonrenewable resources including asphalt and aggregate.However,thus far,only a small part of RAP materials can be used in the con-struction of recycled asphalt pavement,and the usage is regarded as a low-value utilization in the underlying layers.One of the most important reasons for this shortcoming is the problem of false particle size and pseudo gradation of RAP materials.Therefore,identifying suitable asphalt-aggregate separation technology is essential for improving the utilization of RAP materials in recycled asphalt mixture and enhancing the construction quality of recycled asphalt pavement.To address this,the paper performed a systematic review of asphalt-aggregate separation technologies for processing RAP materials and their prospects.Firstly,based on the composition of the asphalt mixture and the characteristics of RAP materials after aging,the key RAP separation technologies were proposed.Then,the concept,principle,and implementation methods of physical,chemical,and biological sep-aration methods of RAP materials were comprehensively analyzed.Moreover,the advantages and disadvantages of various separation technologies were discussed by comparing them with the related technologies in the petrochemical industry.The application prospects of various asphalt-aggregate separation methods for RAP materials can provide a reference for upgrading and expanding solid waste recycling technology for asphalt pavement. | Decheng Feng Jiwei Cao Libo Gao Junyan Yi | 2022 | Journal of Road Engineering2022，2，4： | 1 |
| 9 | A nonlinear interface structural damage model between ice crystal and frozen clay soil显示文摘The shear properties of ice-frozen soil interface are important when studying the constitutive model of frozen soil and slope stability in cold regions. In this research, a series of cryogenic direct shear tests for ice-frozen clay soil interface were conducted. Based on experimental results, a nonlinear interface structural damage model is proposed to describe the shear properties of ice-frozen clay soil interface. Firstly, the cementation and friction structural properties of frozen soil materials were analyzed, and a structural parameter of the ice-frozen clay soil interface is proposed based on the cryogenic direct shear test results. Secondly, a structural coefficient ratio is proposed to describe the structural development degree of ice-frozen clay soil interface under load, which is able to normalize the shear stress of ice-frozen clay soil interface,and the normalized data can be described by the Duncan-Chang model. Finally, the tangent stiffness of ice-frozen clay soil interface is calculated, which can be applied to the mechanics analysis of frozen soil. Also, the shear stress of ice-frozen clay soil interface calculated by the proposed model is compared with test results. | Sheng Shi Feng Zhang KangWei Tang DeCheng Feng XuFeng Lu | 2021 | Research in Cold and Arid Regions2021，13，2： | 1 |
| 10 | Impact of salt and freeze-thaw cy- cles on performance of asphalt mixtures in coastal frozen re- gion of China显示文摘 | FENG Decheng YI Junyan | 2010 | Cold Regions Science and Technology2010，62，： | 1 |
| 11 | Impacl of salt and freeze-thaw cycles on performance of asphalt mixtures in coastal frozen region of China 显示文摘 | Decheng Feng Junyan Yi Dongsheng Wang el al | 2010 | Cold Regions Science and Technology2010，，6： | 1 |
| 12 | Numerical simulation of electroosmosis in unsaturated compacted clay显示文摘The moisture content of a road subgrade in cold regions will increase after freeze-thaw cycles,resulting in subgrade strength and stiffness losses.Electroosmosis is widely used in treating saturated soft soils to decrease the moisture content.The induced moisture migration during electroosmosis in unsaturated soil is much more complex than that of saturated soil because of a series of nonlinear changes in soil properties.This study first uses an exponential function to characterize the relationship between electroosmotic permeability and saturation degree.Then,a one-dimensional model is developed to simulate the electroosmosis-induced moisture migration in unsaturated soil.Simulation results show that electroosmosis reduces the saturation degree of the unsaturated soil,indicating that it can be applied to subgrade dewatering.Key parameters such as soil pore size distribution coefficient,air entry value,and effective voltage significantly affect moisture migration.Electroosmotic properties of unsaturated soils are extremely important to the efficiency of electroosmosis. | KangWei Tang Feng Zhang DeCheng Feng GuanFu Wang | 2021 | Research in Cold and Arid Regions2021，13，5： | 1 |
| 13 | Investigation on the properties of compacted silty clay subjected to electro-osmosis using bender element显示文摘The moisture content of subgrade soil in seasonally frozen regions is often higher than its optimum value,leading to a decline in mechanical properties and a reduction in subgrade bearing capacity.Electro-osmosis has shown promise as a technology for controlling subgrade moisture,but significant heterogeneity has also been observed in treated soil.This study investigates the impact of electro-osmosis on soil stiffness through a series of bender element tests of compacted clay.The effects of dry density and supply voltage on the performance of electroosmosis treatment and the layered structure and anisotropy of the soil were analyzed.The results show that electro-osmosis treatment increased the shear wave velocity of the soil by 140% compared to untreated saturated soil and by 70% compared to soil with optimum water content.It has also been found that layered compaction of soil resulted in a layered structure,with electro-osmosis having a more prominent impact on soil near the cathode,resulting in a more pronounced layered structure.Besides,electro-osmosis was found to enhance soil anisotropy,particularly near the anode.Increasing the dry density and voltage levels can help improve soil uniformity.These findings provide insights into the potential use of electro-osmosis in improving soil stiffness,which could benefit various engineering applications. | KangWei Tang Chuang Lin Hao Wang WeiJun Qin DeCheng Feng Feng Zhang | 2023 | Research in Cold and Arid Regions2023，15，6： | 0 |
| 14 | Multi-Scale Damage Model for Quasi-Brittle Composite Materials显示文摘In the present paper,a hierarchical multi-scale method is developed for the nonlinear analysis of composite materials undergoing heterogeneity and damage.Starting from the homogenization theory,the energy equivalence between scales is developed.Then accompanied with the energy based damage model,the multi-scale damage evolutions are resolved by homogenizing the energy scalar over the meso-cell.The macroscopic behaviors described by the multi-scale damage evolutions represent the mesoscopic heterogeneity and damage of the composites.A rather simple structure made from particle reinforced composite materials is developed as a numerical example.The agreement between the fullscale simulating results and the multi-scale simulating results demonstrates the capacity of the proposed model to simulate nonlinear behaviors of quasi-brittle composite materials within the multi-scale framework. | Decheng Feng | 2020 | Computer Modeling in Engineering & Sciences2020，，3： | 0 |
| 15 | Synthetic aperture metalens显示文摘Metalenses are ultrathin optical elements that can focus light using densely arranged subwavelength structures.Due to their minimal form factor,they have been considered promising for imaging applications that require extreme system size,weight,and power,such as in consumer electronics and remote sensing.However,as a major impediment prohibiting the wide adoption of the metalens technology,the aperture size,and consequently the imaging resolution,of a metalens are often limited by lithography processes that are not scalable.Here,we propose to adopt a synthetic aperture approach to alleviate the issue,and experimentally demonstrate that,assisted by computational reconstruction,a synthetic aperture metalens composed of multiple metalenses with relatively small aperture size can achieve an imaging resolution comparable to a conventional lens with an equivalent large aperture.We validate the concept via an outdoor imaging experiment performed with a synthetic aperture metalens-integrated near-infrared camera using natural sunlight for target illumination. | FENG ZHAO ZICHENG SHEN DECHENG WANG BIJIE XU XIANGNING CHEN YUANMU YANG | 2021 | Photonics Research2021，9，12： | 0 |
| 16 | A Review and Reflection of Value Account of Forest Resources显示文摘 | Li Zhongkui Chen Shaozhi Zhang Decheng Zhao Xiaodi Feng Qiya Wang Yu | 2016 | Journal of Environmental Science and Engineering(B)2016，5，11： | 0 |
| 17 | Numerical simulation of dynamic response of subgrade under moving heavy truck in cold regions显示文摘This paper reports on the dynamic response of highway subgrade under moving heavy truck in cold regions. Numerical simulations are performed in two stages. In the first stage, the moving heavy truck vibration, induced by road roughness, is calculated through a three-dimensional dynamic interaction model of heavy truck-pavement-subgrade, and the time-histories of nodal loads on the top of the base are calculated through this model. In the second stage, a two-dimensional dynamic finite element model of the base-subgrade-ground system is formulated, using the calculated nodal loads from the first stage as input. The dynamic response of the subgrade is validated by field measurements, and the effects of truck type, axle loading, running speed, and road roughness on the vertical dynamic stress in the unfrozen period and the spring thawing period are analyzed and discussed. | Feng Zhang DeCheng Feng XianZhang Ling QiongLin Li | 2013 | Research in Cold and Arid Regions2013，5，4： | 0 |
| 18 | An Insight into Machine Learning Algorithms to Map the Occurrence of the Soil Mattic Horizon in the Northeastern Qinghai-Tibetan Plateau显示文摘Soil diagnostic horizons, which each have a set of quantified properties, play a key role in soil classification. However, they are difficult to predict, and few attempts have been made to map their spatial occurrence. We evaluated and compared four machine learning algorithms, namely, the classification and regression tree(CART), random forest(RF), boosted regression trees(BRT), and support vector machine(SVM), to map the occurrence of the soil mattic horizon in the northeastern Qinghai-Tibetan Plateau using readily available ancillary data. The mechanisms of resampling and ensemble techniques significantly improved prediction accuracies(measured based on area under the receiver operator characteristic curve score(AUC)) and produced more stable results for the BRT(AUC of 0.921 ± 0.012, mean ± standard deviation) and RF(0.908 ± 0.013) algorithms compared to the CART algorithm(0.784 ± 0.012), which is the most commonly used machine learning method. Although the SVM algorithm yielded a comparable AUC value(0.906 ± 0.006) to the RF and BRT algorithms, it is sensitive to parameter settings, which are extremely time-consuming.Therefore, we consider it inadequate for occurrence-distribution modeling. Considering the obvious advantages of high prediction accuracy, robustness to parameter settings, the ability to estimate uncertainty in prediction, and easy interpretation of predictor variables, BRT seems to be the most desirable method. These results provide an insight into the use of machine learning algorithms to map the mattic horizon and potentially other soil diagnostic horizons. | ZHI Junjun ZHANG Ganlin YANG Renmin YANG Fei JIN Chengwei LIU Feng SONG Xiaodong ZHAO Yuguo LI Decheng | 2018 | Pedosphere2018，28，5： | 0 |
| 19 | Determination of allowable subgrade frost heave with the pavement roughness index in numerical analysis显示文摘Frost heave is an upward swelling of soil during cryogenic conditions in cold regions. It is caused by the accumulation of ice crystals in subgrade soil, which grow upwards when freezing temperatures penetrate into the subgrade. This study establishes the allowable soil subgrade frost heave based on the roughness standard of asphalt pavement in China, and aims to balance the pavement design and frost heave resistance of subgrades in cold regions. We formulated a mechanical model of pavement supported by the boundary conditions of differential frost heave, based on the elastic layered system theory. The differential soil subgrade frost heave was modeled as a sinusoidal function, and the allowable frost heave and the roughness index were modeled as the displacement boundaries for the top and bottom of the pavement structure. Then the allowable frost heave was back-calculated according to the roughness standard. Numerical results show that the allowable frost heave depends on the pavement structure, material properties, the highway grade, and other factors. In order to ensure that the actual soil subgrade frost heave is lower than the allowable frost heave, pavement structures and materials need to be selected and designed carefully. The numerical method proposed here can be applied to establish the frost heave resistance of subgrade when the pavement structure and materials are determined. | HongYan Ma Feng Zhang DeCheng Feng Bo Lin | 2015 | Research in Cold and Arid Regions2015，7，5： | 0 |
| 20 | An unsupervised heterogeneous change detection method based on image translation network and post-processing algorithm显示文摘The change detection(CD)of heterogeneous remote sensing images is an important but challenging task.The difficulty is to obtain the change information by directly comparing the different statistical characteristics of the images acquired by different sensors.This paper proposes an unsupervised method for heterogeneous image CD based on an image domain transfer network.First,an attention mechanism is added to the Cycle-generative adversarial networks(Cycle-GANs)to obtain a more consistent feature expression by transferring bi-temporal heterogeneous images to the common domain.The Euclidean distance of the corresponding pixels is calculated in the common domain to form a difference map,and a threshold algorithm is applied to get a rough change map.Finally,the proposed adaptive Discrete Cosine Transform(DCT)algorithm reduces the noise introduced by false detection,and the final change map is obtained.The proposed method is verified on three real heterogeneous CD datasets and compared with the current state-of-the-art methods.The results show that the proposed method is accurate and robust for performing heterogeneous CD tasks. | Decheng Wang Feng Zhao Hui Yi Yinan Li Xiangning Chen | 2022 | International Journal of Digital Earth2022，15，1： | 0 |
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