Combining laboratory measurements and proximal soil sensing data in digital soil mapping approaches

Zare, Sanaz; Abtahi, A.; Shamsi, Seyed Rashid Fallah; Lagacherie, Philippe

doi:10.1016/j.catena.2021.105702

Cited by 9 publications

(8 citation statements)

References 112 publications

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“…In view of the results, which clearly show the impossibility of obtaining an exhaustive estimate of the SAWC due to particular situations that model inversion cannot consider, the prospects for using SAWC estimates by model inversion clearly lie in the second way. The introduction of these new data can therefore be considered as "soft data" in co-kriging procedures, as already done with hyperspectral data (Walker et al, 2017) and with Field EM38 measurements (Zare et al, 2021). It should be noted that such approaches require only that the "soft data" should be well-correlated with the target soil property, and are unsensitive to large biases as those observed in our results.…”

Section: Implications For Digital Soil Mappingmentioning

confidence: 69%

Estimating soil available water capacity within a Mediterranean vineyard watershed using satellite imagery and crop model inversion

et al. 2022

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Section: Implications For Digital Soil Mappingmentioning

confidence: 69%

Estimating soil available water capacity within a Mediterranean vineyard watershed using satellite imagery and crop model inversion

et al. 2022

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“…Conducting ECa surveys in fields where soil water content levels are less than those of field capacity and reportedly under 50% [51] can lead to unreliable and biased results. Likewise, ECa measurements in shallow and moderately deep soils above bedrock should be avoided [30,52].…”

Section: Considerations In the Em38 And Emk2 Applicationsmentioning

confidence: 99%

“…Lately, a new modeling approach has been introduced for characterizing and quantifying the spatial variations and depth distribution of soil salinity with data from EM38 and MK2 devices. This encompasses the integration of ECa measurements, remote sensing data, and environmental variables with machine-learning (ML) technology to generate digital soil maps (DSMs) of ECe in large arid zones [4,52,149,150]. According to this approach, the prediction and mapping of salt-affected areas can be substantially improved when proximal sensed data and multi-spectral information from remote sensing imagery are incorporated [54], and advanced machine-learning algorithms are utilized to assess and model the relationship of ECe with these multiple variables [4,150].…”

Section: Machine-learning-based Modelsmentioning

confidence: 99%

“…In an attempt to explore methods for integrating new sources of soil data as inputs in DSMs, Zare et al [52] compared three approaches using MK2 measurements and ECe data collected from a region near the saline Maharlu Lake in Iran. They concluded that the approach involving the combination of machine learning, quantile random forest model, and regression co-kriging on the residuals, with R 2 values up to 0.79, can be effectively used for the prediction of ECe.…”

Section: Hybrid Modelsmentioning

confidence: 99%

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Assessment and Mapping of Soil Salinity Using the EM38 and EM38MK2 Sensors: A Focus on the Modeling Approaches

Petsetidi,

Kargas

2023

Land

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Soil salinization and its detrimental agricultural, environmental, and socioeconomic impact over extended regions represent a major global concern that needs to be addressed. The sustainability of agricultural lands and the development of proper mitigation strategies require effective monitoring and mapping of the saline areas of the world. Therefore, robust modeling techniques and efficient sensors that assess and monitor the spatial and temporal variations in soil salinity within an area, promptly and accurately, are essential. The aim of this paper is to provide a comprehensive and up-to-date review of the modeling approaches for the assessment and mapping of saline soils using data collected by the EM38 and EM38MK2 (MK2) sensors at different scales. By examining the current and latest approaches and highlighting the most noteworthy considerations related to their accuracy and reliability, the intention of this review is to elucidate and underline the role of the EM38 and the MK2 type in the recent needs of detecting and interpreting soil salinity. Another aim is to assist researchers and users in selecting the optimal approach for future surveys and making well-informed decisions for the implementation of precise management practices. The study’s findings revealed that the integration of the EM38 and MK2 sensors with remote sensing data and advanced methods like machine learning and inversion is a promising approach to the accurate prediction and mapping of the spatiotemporal variations in soil salinity. Therefore, future research focused on validating and expanding such sophisticated modeling applications to regional and global scales should be increased.

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“…These comparisons would bring farmers closer to the multifunctional use of land described by [22], without neglecting the primary productivity. The acquisition of data on soil salinity is being made increasingly affordable through the use of proximal sensors [23][24][25], the combined measurement of water and salt contents in the soil [26], and wireless monitoring [27].…”

Section: Introductionmentioning

confidence: 99%

A Heritage Agronomic Study as a Database for Monitoring the Soil Salinity of an Irrigated District in NE Spain

2022

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This article presents and reviews the soil salinity data provided by a rescued vintage agronomic report on an irrigated area of 35,875 ha located in the center of the Ebro River basin, in the NE of mainland Spain. These data come from a soil sampling campaign conducted from May to the first half of July 1975 for the purpose of delineating saline and non-saline soils. The agronomic report was produced in response to demands from farmers to combat soil salinity, and represents the state of the art in those years for salinity studies. Our paper presents the scrubbed soil salinity data for this year, checking their consistency and locating the study sites. The main finding is the unearthing of this heritage report and the discussion of its soil salinity data. We show that the report supplies an assessment and a baseline for further soil salinity tracking by conducting new measurements either by direct soil sampling or by nondestructive techniques, providing an estimate of soil salinity at different locations. This task is feasible, as shown in our previously published articles involving nearby areas. A comparison of the salt amount in the soil over the years would provide a means to evaluate irrigation methods for sustainable land management. This comparison can be conducted simultaneously with analysis of other agricultural features described in the report for the irrigation district in 1975.

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Combining laboratory measurements and proximal soil sensing data in digital soil mapping approaches

Cited by 9 publications

References 112 publications

Estimating soil available water capacity within a Mediterranean vineyard watershed using satellite imagery and crop model inversion

Estimating soil available water capacity within a Mediterranean vineyard watershed using satellite imagery and crop model inversion

Assessment and Mapping of Soil Salinity Using the EM38 and EM38MK2 Sensors: A Focus on the Modeling Approaches

A Heritage Agronomic Study as a Database for Monitoring the Soil Salinity of an Irrigated District in NE Spain

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