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Soil Atterberg Limits and Consistency Indices as Influenced by Land Use and Slope Position in Western Iran 被引量:2
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作者 Zahra ZOLFAGHARI Mohamamd Reza MOSADDEGHI +1 位作者 Shamsollah AYOUBI Hamid KELISHADI 《Journal of Mountain Science》 SCIE CSCD 2015年第6期1471-1483,共13页
Atterberg limits and consistency indices are used for classifications of cohesive(fine-grained) soils in relation with compaction and tillage practices. They also provide information for interpreting several soil mech... Atterberg limits and consistency indices are used for classifications of cohesive(fine-grained) soils in relation with compaction and tillage practices. They also provide information for interpreting several soil mechanical and physical properties such as shear strength, compressibility, shrinkage and swelling potentials. Although, several studies have been conducted regarding the land use effects on various soil mechanical properties, little is known about the effects of land use and slope positions on Atterberg limits and consistency indices. This study was conducted to investigate the effects of land use and slope position on selected soil physical and chemical properties, Atterberg limits and consistency indices in hilly region of western Iran. Three land uses including dryland farming, irrigated farming and pasture and four slope positions(i.e., shoulder, backslope, footslope, and toeslope) were used for soil samplings. One hundred eleven soil samples were collected from the surface soil(0-10 cm). Selected physical and chemical properties, liquid limit(LL), plastic limit(PL) and shrinkage limit(SL) were measured using the standard methods; and consistency indices including plastic index(PI), friability index(FI), shrinkage index(SI) and soil activity(A=PI/clay) were calculated. The results showed that irrigated farming significantly increased organic matter content(OM) and OM/clay ratio, and decreased bulk density(ρb) and relative bulk density(ρb-rel) as a result of higher biomass production and plant residues added to the soil compared to other land uses. Except for sand content, OM, ρb, cation exchange capacity(CEC) and calcium carbonate equivalent(CCE), slope position significantly affected soil physical and chemical properties. The highest values of silt, OM/clay and CEC/clay were found in the toeslope position, predominantly induced by soil redistribution within the landscape. The use of complexed(COC)- noncomplexed organic carbon(NCOC) concept indicated that majority of the studied soils were located below the saturation line and the OM in the soils was mainly in the COC form. The LL, PI, FI and A showed significant differences among the land uses; the highest values belonged to the irrigated farming due to high biomass production and plant residues returned to the soils. Furthermore, slope position significantly affected the Atterberg limits and consistency indices except for SL. The highest values of LL, PI, SI and A were observed in the toeslope position probably because of higher OM and CEC/clay due to greater amount of expandable phyllosilicate clays. Overall, soils on the toeslope under irrigated farming with high LL and SI and low values of FI need careful tillage management to avoid soil compaction. 展开更多
关键词 Land use Slope position Atterberg limits Soil consistency Relative bulk density Complexed organic carbon
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Spoil characterisation using UAV-based optical remote sensing in coal mine dumps
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作者 Sureka Thiruchittampalam Sarvesh Kumar Singh +2 位作者 Bikram Pratap Banerjee Nancy F.Glenn Simit Raval 《International Journal of Coal Science & Technology》 EI CAS CSCD 2023年第5期72-86,共15页
The structural integrity of mine dumps is crucial for mining operations to avoid adverse impacts on the triple bottom-line.Routine temporal assessments of coal mine dumps are a compliant requirement to ensure design r... The structural integrity of mine dumps is crucial for mining operations to avoid adverse impacts on the triple bottom-line.Routine temporal assessments of coal mine dumps are a compliant requirement to ensure design reconciliation as spoil off-loading continues over time.Generally,the conventional in-situ coal spoil characterisation is inefficient,laborious,hazardous,and prone to experts'observation biases.To this end,this study explores a novel approach to develop automated coal spoil characterisation using unmanned aerial vehicle(UAV)based optical remote sensing.The textural and spectral properties of the high-resolution UAV images were utilised to derive lithology and geotechnical parameters(i.e.,fabric structure and relative density/consistency)in the proposed workflow.The raw images were converted to an orthomosaic using structure from motion aided processing.Then,structural descriptors were computed per pixel to enhance feature modalities of the spoil materials.Finally,machine learning algorithms were employed with ground truth from experts as training and testing data to characterise spoil rapidly with minimal human intervention.The characterisation accuracies achieved from the proposed approach manifest a digital solution to address the limitations in the conventional characterisation approach. 展开更多
关键词 LITHOLOGY Fabric structure consistency/relative density Dimensionality reduction Supervised learning algorithms
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