Leveraging Gradient-Based Optimizer and Deep Learning for Automated Soil Classification Model

Soil classification is one of the emanating topics and major concerns in many countries.As the population has been increasing at a rapid pace,the demand for food also increases dynamically.Common approaches used by agriculturalists are inadequate to satisfy the rising demand,and thus they have hindered soil cultivation.There comes a demand for computer-related soil classification methods to support agriculturalists.This study introduces a Gradient-Based Optimizer and Deep Learning(DL)for Automated Soil Clas-sification(GBODL-ASC)technique.The presented GBODL-ASC technique identifies various kinds of soil using DL and computer vision approaches.In the presented GBODL-ASC technique,three major processes are involved.At the initial stage,the presented GBODL-ASC technique applies the GBO algorithm with the EfficientNet prototype to generate feature vectors.For soil categorization,the GBODL-ASC procedure uses an arithmetic optimization algorithm(AOA)with a Back Propagation Neural Network(BPNN)model.The design of GBO and AOA algorithms assist in the proper selection of parameter values for the EfficientNet and BPNN models,respectively.To demonstrate the significant soil classification outcomes of the GBODL-ASC methodology,a wide-ranging simulation analysis is performed on a soil dataset comprising 156 images and five classes.The simulation values show the betterment of the GBODL-ASC model through other models with maximum precision of 95.64%.

Classification of Ferrallitic Soils in Chinese Soil Taxonomy

The development of the classification of ferrallitic soils in China is reviewed and the classification ofFerralisols and Ferrisols in Chinese Soil Taxonomy is introduced in order to discuss the correlation betweenthe ferrallitic soil classification in the Chinese Soil Taxonomy and those of the other soil classification systems.In the former soil classification systems of China, the ferrallitic soils were classified into the soil groups ofLatosols, Latosolic red soils, Red soils, Yellow soils and Dry red soils, according to the combination of soilforming conditions, soil-forming processes, soil features and soil properties. In the Chinese Soil Taxonomy,most of ferrallitic soils are classified into the soil orders of Ferralisols and Ferrisols based on the diagnostichorizons and/or diagnostic characteristics with quantitatively defined properties. Ferralisols are the soilsthat have ferralic horizon, and they are merely subdivided into one suborder and two soil groups. Ferrisolsare the soils that have LAC-ferric horizon but do not have ferralic horizon, and they are subdivided intothree suborders and eleven soil groups. Ferralisols may correspond to part of Latosols and Latosolic red soils.Ferrisols may either correspond to part of Red soils, Yellow soils and Dry red soils, or correspond to part ofLatosols and Latosolic red soils.

National Scale Analysis of Soil Organic Carbon Storage in China Based on Chinese Soil Taxonomy

Patterns of soil organic carbon (SOC) storage and density in various soil types or locations are the foundation for examining the role of soil in the global carbon cycle. An assessment of SOC storage and density patterns in China based on soil types as defined by Chinese Soil Taxonomy (CST) and the recently compiled digital 1:1000000 Soil Database of China was conducted to generate a rigorous database for the future study of SOC storage. First, SOC densities of 7 292 soil profiles were calculated and linked by soil type to polygons of a digital soil map using geographic information system resulting in a 1:1 000 000 SOC density distribution map of China. Further results showed that soils in China covered 9 281×103 km2 with a total SOC storage of 89.14 Gt and a mean SOC density 96.0 t ha-1. Among the 14 CST orders, Cambosols and Argosols constituted high percentage of China's total SOC storage, while Andosols, Vertosols, and Spodsols had a low percentage. As for SOC density, Histosols were the highest, while Primosols were the lowest. Specific patterns of SOC storage of various soil types at the CST suborder, group, and subgroup levels were also described. Results obtained from the study of SOC storage and density of all CST soil types would be not only useful for international comparative research, but also for more accurately estimating and monitoring of changes of SOC storage in China.

THE DISTRIBUTION REGULARITY OF HIGHER CATEGORIES IN CHINESE SOIL TAXONOMY

The regularity of the distribution of higher categories in Chinese Soil Taxonmy(CST)were studied through analyzing the diagnostic horizons and characteristics and the variation of soil forming factors in China. The results indicate that the distribution regularity of higher categories in CsT is different for that in the past zonal classification, which is inferred on the basis of typical profiles and bioclimatic conditions. Among the 14 soil orders available in CST, 6 belong to the basic types, which shaw the regularly continuous distribution, and can be deduced into three larger groups: aridic, ustic and udic. The other 8 soil orders belong to the special types with the band-shaped, spot-shaped, chessboard-shaped, patch-shaped distributions and so on. Moreover, there is the regularity of vertical distribution in mountains.

Predicting Base Saturation Percentage by pH—A Case Study of Red Soil Series in South China

pH and base saturation percentage (BSP) are two basic indexes in identifying soil types in Chinese Soil Taxonomy. Some studies proved that there is significant correlation between BSP and pH, thus it could save the cost of laboratory work if we can infer BSP directly from pH. In this study, the measured values of BSP and pH of 162 and 232 horizon samples from 48 and 55 red soil series surveyed from 2009 to 2011 in Fujian and Guangdong respectively were adopted from Soil Series Database to set up the optimal correlation model between BSP and pH. The results showed that: 1) BSP ranged from 2.30% to 94.02% with a mean of 25.07%, while pH from 3.42 to 6.91 with a mean of 4.98 for the total soil samples. 2) There were significant differences in pH between different soil types (R2 were 0.624 for Ferralosols, 0.507 for Ferrosols, 0.515 for Argosols, and 0.456 for Cambosols, p 2 were 0.580 for Quaternary red clay, 0.434 for granite, 0.642 for sandstone, and 0.712 for basalt, p 2 were 0.623 for dryland, and 0.404 for forest land, p 0), their probability density curves were mainly in flat or normal curves (y = 6.84x2 &#8722;45.86x + 81.52, R2 = 0.494, p < 0.01).

Applications of Soil Series in Sustainable Land Use of Oasis Farmlands

The issue of agricultural land sustainability is important to every part of the world, especially in the developing countries. Based on the data collected by field investigation and laboratory analysis as well as soil classification theory, the authors discuss the applications of soil series in the arid northwestern China. On the one hand, the application in the layout of rational agricultural of oasis farmlands: (1) two soil series,namely,Lanjiabao (main) and Nijiaxiaying, belong to the moderate and extremely arid region in the study area; accordingly, the layout of crops is the spring wheat and maize (main) and winter wheat;(2) Nijiaxiaying (main) and Lanjiabao, however, fall into the warm-cold and extremely arid region, where the winter wheat (main) and spring wheat grow; and (3) the Shangfusi is part of the warm chilly-arid region, which is used as seasonal pastureland. On the other hand, the application on the soil quality of oasis farmlands, the results indicating that among all soil series, the content of N is very low, however, the content of K is abundant, and the content of P is greatly scarce.

A case study on the soil classification of the Yellow River Delta based on piezocone penetration test

Piezocone penetration test(CPTu),the preferred in-situ tool for submarine investigation,is significant for soil classification and soil depth profile prediction,which can be used to predict soil types and states.However,the accuracy of these methods needs to be validated for local conditions.To distinguish and evaluate the properties of the shallow surface sediments in Chengdao area of the Yellow River Delta,seabed CPTu tests were carried out at ten stations in this area.Nine soil classification methods based on CPTu data are applied for soil classification.The results of classification are compared with the in-situ sampling to determine whether the method can provide sufficient resolution.The methods presented by Robertson(based on soil behavior type index Ic),Olsen and Mitchell are the more consistent and compatible ones compared with other methods.Considering that silt soils have potential to liquefy under storm tide or other adverse conditions,this paper is able to screen soil classification methods suitable for the Chengdao area and help identify the areas where liquefaction or submarine landslide may occur through CPTu investigation.

Indigenous Knowledge on Soil Classification of Ethnic Groups in Luang Prabang Province of the Lao PDR

The objectives of this study were to demonstrate ethno-scientific elicitation techniques in retrieving indigenous knowledge at village-level, and to document the indigenous soil classification systems of different ethnic groups in Luang Prabang province in the Lao PDR. The study area comprised three villages – Nambo, Huaymaha and Thapo, in the Phonxay district of Luang Prabang province. Three ethnic groups were covered by the study – Hmong, Khmu and Lao Loum. All three ethnic groups used soil color as main criteria for soil classification. However, even within the same ethnic group, sometimes different villages have differences in the way they classify soils; this was apparent for the Hmong ethnic group in the villages of Huaymaha and Nambo. A significant difference of the Lao Loum ethnic group from the other two, was the emphasis used in classifying soil types according to their water holding capabilities. In contrast, the Khmu and Hmong classified many soil types in relation to their rock content (‘with rock’ or ‘pure rock’ sometimesbeing used). The results of the study suggest that the ethnic groups classify the soils in relation to their potential for different types of agricultural production.

Chinese Soil Taxonomy:A Milestone of Soil Classification in China

1 Background Taxonomy is the branch of science dedicated to discovering,characterizing,naming,and classifying objects or organisms so as to understand relationships between them and the factors of their formation.

Study on strength properties and soil behaviour type classification of Huanghe River Delta silts based on variable rate piezocone penetration test

Fine-grained silt is widely distributed in the Huanghe River Delta(HRD)in China,and the sedimentary structure is complex,meaning that the clay content in the silt is variable.The piezocone penetration test(CPTu)is the most widely approved in situ test method.It can be used to invert soil properties and interpret soil behavior.To analyse the strength properties of surface sediments in the HRD,this paper evaluated the friction angle and its inversion formula through the CPTu penetration test and monotonic simple shear test and other soil unit experiments.The evaluation showed that the empirical formula proposed by Kulhawy and Mayne had better prediction and inversion effect.The HRD silts with clay contents of 9.2%,21.4%and 30.3%were selected as samples for the CPTu variable rate penetration test.The results show as follows.(1)The effects of the clay content on the tip resistance and the pore pressure of silt under different penetration rates were summarized.The tip resistance Q_t is strongly dependent on the clay content of the silt,the B_(q)value of the silt tends to 0 and is not significantly affected by the change of the CPTu penetration rate.(2)Five soil behavior type classification charts and three soil behavior type indexes based on CPTu data were evaluated.The results show that the soil behavior type classification chart based on soil behavior type index ISBT,the Robertson 2010 behavior type classification chart are more suitable for the silty soil in the HRD.

Groutability classification of granular soils with cement grouts

This research aims to develop a methodology for applying the geostatistical method to generate a groutability classification for granular soils.To ensure the precision of the suggested technique,a total of 103 data samples were used.Predicting the groutability of granular soils has always been difficult because of many soil characteristics.As a result,a new two-dimensional graph,the groutability classification of granular soil(GCS)chart,was developed.GCS establishment was based on data analysis of the grain size of soil and cement-based grouts(N1 and N2),relative density(Dr)and fines content of the soil(FC),water/cement ratio of grout mixture(w/c),and grouting pressure(P),all of which have a direct impact on the groutability of soil media.The geostatistical method was used to develop and compile the GCS graph based on the aforementioned parameters with the use of coefficient S,which is a coefficient of the scoring set of parameters including P,w/c,Dr,and FC.The validation process was carried out hierarchically,with an additional set of 30 data.The proposed method has a prediction accuracy of roughly 96.7%,demonstrating a helpful tool.The proposed approach can be easily implemented in practical engineering situations because it has a comparable syntax to commonly used formulae.It should be noted that the proposed formula was only tested using the data samples collected,and the applicability of the produced procedure to other situations requires more examination.

Site observations of weathered granitic soils subjected to cementation and partial drainage using SCPTU

Because of the cementation inherited from the parent rock,weathered granitic soil is usually susceptible to disturbance,which poses considerable challenges for laboratory characterization.The cone penetration test with pore pressure measurements has long been known for its reliability in site investigations and stratigraphic profiling.However,although extensive piezocone test results and experience are available for sedimentary soil,similar advances are yet to be made for weathered granitic soil.Moreover,the experience from sedimentary soil may not be directly applicable to weathered profiles because of the essentially different natures of the two types of geomaterials.This study performs seismic piezocone tests in a weathered granitic profile comprising residual granitic soil,completely weathered granite,and highly weathered granite.Pore pressure is measured at both the cone mid-face and the shoulder,and the effects of penetrometer size and penetration rate are considered.A series of updated soil behavior type charts is proposed to interpret the test results,thereby allowing the effect of weathering to be evaluated.This paper offers an important extension to the sparse data on the in situ responses of weathered materials.

Geotechnical Identification and Classification of Soils as Flexible Pavement Subgrade of the Section Fongo Tongo-Melong

The present study is inscribed within the framework of the geotechnical characterization of the soils of the Santchou plain, their classification for employment as pavement subgrade, various identification tests were carried out on the samples. The results obtained showed that with a wide range of different grain sizes, the studied soils showed low content in clay grains and dominance of either sand grains or silt grains, this can be explaining how most of these soil are poorly graded. According to the USDA textural classification, the grain size distribution of these soils makes them to be classified as Silty Loam types to Sandy Loam types. Despite of their organic matter content which is less than 10%, according to their respective methylene blue values, the soils studied along the section should be mainly loamy soil of medium plasticity to clayed soil, therefore showing a sensibility of its behavior to variation of water content. That last one is confirmed by the consistency parameters of these soils which show intermediate plasticity to highly plastic. Also, the bearing capacity proposed by these soils at their respective optimum dry densities is relatively small, although most of these experimental CBR values of the studied soils are more important than the ones prescribed by the AASHTO Classification system for A5, A6, and A7 types, and the French Highway Earthworks Manual Classifications system (GTR) for the corresponding A2 and A3 types.

Predicting and delineating soil temperature regimes of China using pedotransfer function

Soil temperature regime(STR)is important for soil classification and land use.Generally,STR is delineated by estimating the mean annual soil temperature at a depth of 50 cm(MAST50)according to the Chinese Soil Taxonomy(CST).However,delineating the STR of China remains a challenge due to the difficulties in accurately estimating MAST50.The objectives of this study were to explore environmental factors that influence the spatial variation of MAST50 and generate an STR map for China.Soil temperature measurements at 40 and 80 cm depth were collected from 386 National Meteorological Stations in China during 1971–2000.The MAST50 was calculated as the average mean annual soil temperature(MAST)from 1971–2000 between 40 and 80 cm depths.In addition,2048 mean annual air temperature(MAAT)measurements from 1971 to 2000 were collected from the National Meteorological Stations across China.A zonal pedotransfer function(PTF)was developed based on the ensemble linear regression kriging model to predict the MAST50 in three topographic steps of China.The results showed that MAAT was the most important variable related to the variation of MAST50.The zonal PTF was evaluated with a 10%validation dataset with a mean absolute error(MAE)of 0.66°C and root mean square error(RMSE)of 0.78°C,which were smaller than the unified model with MAE of 0.83°C and RMSE of 0.96°C,respectively.This study demonstrated that the zonal PTF helped improve the accuracy of the predicted MAST50 map.Based on the prediction results,an STR map across China was generated to provide a consistent scientific base for the improvement and application of CST and land use support.

Improved Soil Quality Prediction Model Using Deep Learning for Smart Agriculture Systems

Soil is the major source of infinite lives on Earth and the quality of soil plays significant role on Agriculture practices all around.Hence,the evaluation of soil quality is very important for determining the amount of nutrients that the soil require for proper yield.In present decade,the application of deep learning models in many fields of research has created greater impact.The increasing soil data availability of soil data there is a greater demand for the remotely avail open source model,leads to the incorporation of deep learning method to predict the soil quality.With that concern,this paper proposes a novel model called Improved Soil Quality Prediction Model using Deep Learning(ISQP-DL).The work considers the chemical,physical and biological factors of soil in particular area to estimate the soil quality.Firstly,pH rating of soil samples has been collected from the soil testing laboratory from which the acidic range has been categorized through soil test and the same data has been taken as input to the Deep Neural Network Regression(DNNR)model.Secondly,soil nutrient data has been given as second input to the DNNR model.By utilizing this data set,the DNNR method is used to evaluate the fertility rate by which the soil quality has been estimated.For training and testing,the model uses Deep Neural Network Regression(DNNR),by utilizing the dataset.The results show that the proposed model is effective for SQP(Soil Quality Prediction Model)with efficient good fitting and generality is enhanced with input features with higher rate of classification accuracy.The results show that the proposed model achieves 96.7%of accuracy rate compared with existing models.

GIS-Based Red Soil Resources Classification andEvaluation

INTRODUCTIONCoveringabout2.18millionkmZor22.7%ofChina'slandterritory,redsoilresources(RSR)areextremelyimportantfortheregionofSouthChina,wherethereareadiversityofsoilswith58.7%(1.28millionkm')ofthembeingcategorizedtoredsoils(RS)(Huetal.,1999).Withboun...

Micromorphological Features of Diagnostic Horizons in Several soils in Southwest China: Implication for Soil Taxonomic Classification

The comparative studies on micromorphological features in diagnostic horizons of Stagnic Anthrosols, Ustic Ferrosols and Ustic Vertosols in southwestern China were conducted to underpin the rationale for Chinese Soil Taxonomy. The following findings were explored: (1) Stagnic Anthrosols had the specific micromorphological features, e.g., the humic formation in anthrostagnic epipedon, the platy structures in plow subhorizon, the secondary formation of ferromanganese and the weakly optical-orientation clay domains in hydragric horizon, etc.: (2) The groundmasses of ferric horizon in Ustic Ferrosols appeared in hue of 2.5YR or redder, and had pellicular grain structure; (3) Ustic Vertosols had a crust horizon (Acr), and crack structure dominated in Acr and angular blocky structure in disturbed horizon; (4) Because of the distinct differences in micromorphological features among these three soils, the specific micromorphological features might be employed as diagnostic horizons to differentiate soils while the quantifiable micromorphological features might potentially be selected as diagnostic indices for Chinese soil taxonomic classification.

Effects of environmental factors on classification of loessderived soils and clay minerals variations, northern Iran

Land-use type under different topographic conditions and human activities affects soil development. We investigated the effects of land-use,topography and human activity on soil classification changes in the Toshan watershed in northern Iran.Seven representative pedons derived from loess parent materials were studied on different land-uses and topographic positions. The studied pedons in forest(FO) on backslopes and footslope were classified as Calcic Haploxeralfs and Typic Haploxeralfs, respectively. The soils in abandoned lands(AB) and orchards(OR), where formerly under natural forests, located on the shoulder and backslopes positions were classified as Calcic Haploxeralfs and Vertic Haploxeralfs, respectively.Well-developed argillic horizons as indicators for higher degrees of soil evolution were observed in more-stable areas under the natural forest or less disturbed areas. Clay lessivage through these soil profiles have led to formation of Typic or Calcic Haploxeralfs, while under croplands(CP) were classified as Typic Calcixerepts. Conversion of sloping deforested areas to CP along with inappropriate management have accelerated soil erosion, resulting in unstable conditions in which decalcification and formation of developed soils cannot occur. Paddy cultivation in flat areas has caused to reduced conditions and formation of Typic Haplaquepts.Because of unfavorable conditions for chemical weathering(e.g. lower water retention compared to more-stable areas) no vermiculite was detected in the CP. The results showed that evolution and classification of the studied soils were strongly affected by land-use type, topography and management.

ECOLOGICAL SERIES OF SOIL ANIMALS IN DARLIDAI MOUNTAIN

The ecological series of soil animals under the broad-leaved and pine mix ed forest in Darlidai Mountain was studied.Seven sample plots were selected according to different altitude gradients,which belong to dif ferent vegeta-tion types.By investigating and analyzing soil animals in every sample p lot it is found that there are 45group s and 1956individuals,which are involved in 3phylums,7classes,16orders,respectively.The altitude is a key factor which af-fects ecological series of soil anim als.Both the groups and individuals of soil animals increase with altitu de increasing under certain conditions,which con trastes with ordinary cases,resulting from special micro-climate in studied area.The groups and individuls of soil animals are the most under the broad-leaved and pine forest on the top of the mount ain,and the least under Picea-Abies forest in the foot of the mountain.

Soil Taxonomy and Distribution Characteristics of the Permafrost Region in the Qinghai-Tibet Plateau, China

Understanding the soil taxonomy and distribution characteristics of the permafrost region in the Qinghai-Tibet Plateau(QTP) is very important. On the basis of extensive field surveys and experimental analysis, this study carries out soil taxonomic classification of the permafrost region in the QTP. According to Chinese Soil Taxonomy, the soil of the permafrost region in the QTP can be divided into 6 Orders(Histosols, Aridosols, Gleyosols, Isohumosols, Cambosols, Primosols), 11 Suborders, 19 Groups and 24 Subgroups. Cambosols are the dominant soil type in the permafrost region, followed by Aridosols. From the east to the west of the permafrost region in the QTP, the soil type gradually changes from Cambosols to Aridosols, showing a meridional zonality. The eastern region is dominated by Cambosols, with no obvious latitudinal zonality. From the south to the northwest of the western region, the dominance of Aridosols and Cambosols gradually transited to Aridosols, presenting a latitudinal zonality. The soil in the western region shows a poor vertical zonality, while the distribution of suborders of Cambosols in the eastern region shows a more obvious vertical zonality. The result indicates that precipitation and vegetation are the main factors that influence the zonal distribution of soil. The permafrost in the east has some effect on the vertical soil zonality, but the effect is weakened in the west.