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Combination of effective color information and machine learning for rapid prediction of soil water content

Journal of Rock Mechanics and Geotechnical Engineering 2023年第9期15卷 2441-2457页

作者： Guanshi Liu Shengkui Tian Guofang Xu Chengcheng Zhang Mingxuan Cai State Key Laboratory of Geomechanics and Geotechnical Engineering Institute of Rock and Soil MechanicsChinese Academy of SciencesWuhan430071China Guangxi Key Laboratory of Rock and soil Mechanics and Engineering Guilin University of TechnologyGuilin541004China

soil water content(SWC)is one of the critical indicators in various fields such as geotechnical engineering and *** avoid the time-consuming,destructive,and laborious drawbacks of conventional SWC measurements,the image-based SWC prediction is considered based on recent advances in quantitative soil color *** this study,a promising method based on the Gaussian-fitting gray histogram is proposed for extracting characteristic parameters by analyzing soil images,aiming to alleviate the interference of complex surface conditions with color information *** addition,an identity matrix consisting of 32 characteristic parameters from eight color spaces is constituted to describe the multi-dimensional information of the soil ***,a subset of 10 parameters is identified through three variable analytical ***,four machine learning models for SWC prediction based on partial least squares regression(PLSR),random forest(RF),support vector machines regression(SVMR),and Gaussian process regression(GPR),are established using 32 and 10 characteristic parameters,and their performance is *** results show that the characteristic parameters obtained by Gaussian-fitting can effectively reduce the interference from soil surface *** RGB,CIEXYZ,and CIELCH color spaces and lightness parameters,as the inputs,are more suitable for the SWC prediction ***,it is found that 10 parameters could also serve as optimal and generalizable predictors without considerably reducing prediction accuracy,and the GPR model has the best prediction performance(R^(2)≥0.95,RMSE≤2.01%,RPD≥4.95,and RPIQ≥6.37).The proposed image-based SWC predictive models combined with effective color information and machine learning can achieve a transient and highly precise SWC prediction,providing valuable insights for mapping soil moisture fields.

关键词： soil water content(SWC) Digital image soil color color space Machine learning

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The use of remote sensing to detect the consequences of erosion in gypsiferous soils

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International soil and Water Conservation Research 2020年第4期8卷 383-392页

作者： Maria Jose Marques Ana Alvarez Pilar Carral Blanca Sastre Ramón Bienes Geology and Geochemistry Department Autonomous University of MadridCalle Francisco Tomás y Valiente728040MadridSpain Department of Applied Research and Agrarian Extension IMIDRAFinca El Encín.Carretera A-2Km 38.8.Alcaláde Henares28800MadridSpain

Tillage practices on sloping ground often result in unsustainable soil losses impairing soil functions such as crop productivity,water and nutrients storage,and soil organic carbon(SOC)sequestration.A sloping olive grove(10%)was planted in shallow gypsiferous soils in *** was managed by minimum tillage;the most frequent management practice in central *** consequences of erosion were studied in soil samples(at 0-10,10-20,and 20-30 cm depths)by analyzing SOC,available water and gypsum content,and by detecting spectral signatures using an ASD FieldSpecPro(R)VIS/*** Brightness index(BI),Shape index(FI),and Normalized Difference Vegetation Index(NDVI)were derived from the ASD spectral signatures and from remote sensing(Sentinel-2 image)*** development of these young olive trees was estimated from the measured diameter of the trunks(17±18 cm diameter).In 20-30 cm of the soil,the carbon stock(38±18 Mg ha-1)as well as the available water content(12±6%)was scarce,affecting the productivity of the olive *** above-mentioned indices obtained from the laboratory samples and the pixels of the Sentinel-2 image were significantly(psoil degradation on the trees and the carbon *** spatialtemporal changes of the indices might help in tracking soil changes over time.

关键词： Tillage Erosion NDVI Gypsum Remote sensing soil color

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Study the Physical, Chemical, Mineralogical, and Geo-technical Properties of soils Used in Pottery Industries, Kurdistan-lraq

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Journal of Agricultural Science and Technology(A) 2013年第11期3卷 843-849页

作者： Ezzat Findi Yahya Mohammed Ali Fayyadh soil and Water Sciences Department Faculty of Agriculture and Forestry University of Duhok Duhok City 42001 Kurdistan Iraq

The study area is located in Duhok and Sulaimania province in Kurdistan region, lraq. Study soils developed from parent material that has derived from limestone. Randomize, composed and disturbed surface soil samples were collected. The bulk soils were air dried, crushed and passed through 2 mm sieve. Standard methods were used for chemical, physical, geotechnical and mineralogical analyses of soil samples. The results indicated that the study soils texture were clay to loam clay, this texture was considered as suitable for ceramic and pottery industries as a result of increasing clay contents that ranged between 301 g/kg and 676 g/kg. soil consistence depending on geotechnical properties increased the ability of study soils for resistance rapture and deformation. Existence the high amount of cementing agents in study soils such as organic matter, iron oxides and particularly total carbonate （247.2-308.8 g/kg） act to reduce the bad effect of the smectite minerals group （high shrinkage） in soils of study locations through increasing the resistance of these soils for rupture and deformation. The existing of Kaolinite, palygorskite and chlorite allows clay to be dried in ceramic and pottery industries without cracking from shrinkage. Study soils were different in their colors as a result of existence, different pigmentation materials that led to coloring soils with different colors in turn caused coloring of pottery and ceramic materials. Since, there are no available academic studies or researches about this subject in Kurdistan region in addition the clay pottery and ceramic sector still has a good market at the same time using this type of soils for arts, therefore, this study was conducted.

关键词： soil pottery industries clay minerals soil color cementing agents geo-technical properties.

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