Estimation of the moisture content of tropical soils using colour images and artificial neural networks

Zanetti, Sandra Aparecida Serra; Cecílio, Roberto Avelino; Alves, Estevão Giacomin; Silva, Vitor Heringer; Sousa, Elias Fernandes de

doi:10.1016/j.catena.2015.07.015

Cited by 42 publications

(23 citation statements)

References 44 publications

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“…ture, interruption by clouds and foliage, and considerable signal interruption by the atmosphere. Compared with the above-mentioned methods, the image-based met soil moisture estimation is considered as promising because it has the advantages practical, fast, non-destructive, relatively low cost, and enables real-time continuou urement in the field [33]. Nevertheless, there are few studies on the application of th analysis method to evaluate loess moisture, and no calibration relationship between or and moisture content has ever been reported for loess.…”

Section: Loess Soilmentioning

confidence: 99%

“…Drawing upon the principle of the remote sensing technique, the image-based methods have been proposed and increasingly applied to measure soil moisture content [ 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 ].The image-based technique commonly employs an ordinary digital camera to capture soil sample, and the moisture content is derived from soil color using the pre-established calibration curve. It is obvious that the calibration relationship between soil moisture content and its color is the key for employing the image-based technique.…”

Section: Introductionmentioning

confidence: 99%

“…The remote sensing technique for estimating soil moisture is suitable for large areas having uniform coverage; however, it is considered as a complex and expensive technique, and its accuracy is restricted by uncertainties associated with the lighting, temperature, interruption by clouds and foliage, and considerable signal interruption by the Earth’s atmosphere. Compared with the above-mentioned methods, the image-based method for soil moisture estimation is considered as promising because it has the advantages of being practical, fast, non-destructive, relatively low cost, and enables real-time continuous measurement in the field [ 33 ]. Nevertheless, there are few studies on the application of the image analysis method to evaluate loess moisture, and no calibration relationship between soil color and moisture content has ever been reported for loess.…”

Section: Introductionmentioning

confidence: 99%

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Characterization of the Relationship between the Loess Moisture and Image Grayscale Value

Liu

Wang

Zheng

et al. 2021

Sensors

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This paper presents a model for estimating the moisture of loess from an image grayscale value. A series of well-controlled air-dry tests were performed on saturated Malan loess, and the moisture content of the loess sample during the desiccation process was automatically recorded while the soil images were continually captured using a photogrammetric device equipped with a CMOS image sensor. By converting the red, green, and blue (RGB) image into a grayscale one, the relationship between the water content and grayscale value, referred to as the water content–gray value characteristic curve (WGCC), was obtained; the impacts of dry density, particle size distribution, and illuminance on WGCC were investigated. It is shown that the grayscale value increases as the water content decreases; based on the rate of increase of grayscale value, the WGCC can be segmented into three stages: slow-rise, rapid-rise, and asymptotically stable stages. The influences that dry density and particle size distribution have on WGCC are dependent on light reflection and transmission, and this dependence is closely related to soil water types and their relative proportion. Besides, the WGCC for a given soil sample is unique if normalized with illuminance. The mechanism behind the three stages of WGCC is discussed in terms of visible light reflection. A mathematical model was proposed to describe WGCC, and the physical meaning of the model parameters was interpreted. The proposed model is validated independently using another six different types of loess samples and is shown to match well the experimental data. The results of this study can provide a reference for the development of non-contact soil moisture monitoring methods as well as relevant sensors and instruments.

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Section: Loess Soilmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Characterization of the Relationship between the Loess Moisture and Image Grayscale Value

Liu

Wang

Zheng

et al. 2021

Sensors

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“…The rationale for this is to determine whether the resulting device, with appropriate data preprocessing, can still provide useful information while doing so cheaply and rapidly and with a minimum of support equipment (i.e., handheld and with no artificial lighting). Existing examples of research using visible light alone (e.g., [ 37 , 38 ]) indicate that, certainly for soil, estimates for certain variables could be achieved and that colour information captured using digital cameras can be of sufficiently good quality to achieve this.…”

Section: Introductionmentioning

confidence: 99%

PHYLIS: A Low-Cost Portable Visible Range Spectrometer for Soil and Plants

Gaskin

Lafouge

Hawes

2017

Sensors

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Monitoring soil and crop condition is vital for the sustainable management of agricultural systems. Often, land management decision-making requires rapid assessment of conditions, which is difficult if samples need to be taken and sent elsewhere for analysis. In recent years, advances in field-based spectroscopy have led to improvements in real-time monitoring; however, the cost of equipment and user training still makes it inaccessible for most land managers. At the James Hutton Institute, we have developed a low-cost visible wavelength hyperspectral device intended to provide rapid field-based assessment of soil and plant conditions. This device has been tested at the Institute’s research farm at Balruddery, linking field observations with existing sample analysis and crop type information. We show that it is possible to rapidly and easily acquire spectral information that enables site characteristics to be estimated. Improvements to the sensor and its potential uses are discussed.

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“…In view of the heterogeneity of the water profile and the irregularity of the boundary in the actual seepage process, traditional seepage theory research is mostly confined to the layered soil, which requires the installation of at least one moisture probe in each representative soil layer to achieve significant changes in water measurement [37,40] as well as to construct calibration curves associated with each type of soil. In contrast, this photometric method has a stronger adaptability to the nonuniform transient effect of the above unsaturated seepage process, which provides a new perspective for the verification of the numerical model in the laboratory seepage test.…”

mentioning

confidence: 99%

An Improved Method for Quantifying Liquid Saturation Using Transparent Soil

Wang

Liu

Chen

et al. 2019

Advances in Civil Engineering

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Transparent porous media combined with digital image processing technology can be used to quantify the saturation of local fluids. In this regard, the calibration relationship between the pixel intensity of the image and the saturation of the wetting liquid is the crucial premise for whether this technique can be promoted and applied, and it is also a bottleneck that limits whether this technique can be rapidly and extensively developed. However, owing to gravity-driven effects, wetting liquid in a residual state usually exhibits an irregular boundary caused by the phenomenon of saturation overshoot, which makes it very difficult to use the previous overflow method to obtain the data pair of saturation-pixel intensity accurately. To this end, we have made some improvements to the specific testing method for wetting liquid saturation in the residual state and proposed a local centrifugal sampling method, which considerably improved the accuracy of this method. The results show that the relationship between the pixel intensity and saturation of the transparent soil obtained through this method is generally consistent with the regularity of the previous calibration method but shows better correlation. The results of this study will drive further potential application of transparent soil in the flow of partially saturated porous media.

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Estimation of the moisture content of tropical soils using colour images and artificial neural networks

Cited by 42 publications

References 44 publications

Characterization of the Relationship between the Loess Moisture and Image Grayscale Value

Characterization of the Relationship between the Loess Moisture and Image Grayscale Value

PHYLIS: A Low-Cost Portable Visible Range Spectrometer for Soil and Plants

An Improved Method for Quantifying Liquid Saturation Using Transparent Soil

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