Soil salinity assessment of a natural pasture using remote sensing techniques in central Anatolia, Turkey

Kiliç, Orhan; Budak, Mesut; Günal, Elif; Acır, Nurullah; Hälbac-Cotoară-Zamfir, Rareş; Al‐Farraj, Saleh A.; Ansari, Mohammad Javed

doi:10.1371/journal.pone.0266915

Cited by 11 publications

(4 citation statements)

References 45 publications

(63 reference statements)

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“…Soil salinity is a primary land degradation process that reduces biological production in arid and semi-arid climates, requiring comprehensive monitoring and management. Recent advances in remote sensing technology allowed soil salinity to be recognized and monitored reliably [1][2][3]. Soil salinity is known as a dynamic process, which arises as a result of natural processes and human activities, particularly in arid and semi-arid environments as a result of insufficient rainfall, an excessive evaporation of shallow groundwater, and a highly soluble concentration of salt [3,4].…”

Section: Introductionmentioning

confidence: 99%

“…Their primary method was mainly to create regression models between ground sample locations and remote sensing datasets. Three approaches have mainly been used to map the soil salinity: (1) model development between reflection values of spectral bands in satellite images and measured soil salinity values [37,40], (2) directly estimating soil salinity by calculating salinity indices [21,39,40], and (3) indirectly estimating soil salinity by calculating vegetation indices [21,41,42].…”

Section: Introductionmentioning

confidence: 99%

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Detecting and Mapping Salt-Affected Soil with Arid Integrated Indices in Feature Space Using Multi-Temporal Landsat Imagery

et al. 2022

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Salinity systems are well known as extreme environmental systems that occur either naturally or by certain human activities, in arid and semiarid regions, which may harm crop production. Soil salinity identification is essential for soil management and reclamation projects. Information derived from space data acquisition systems (e.g., Landsat, ASTER) is considered as one of the most rapid techniques in mapping Salt-Affected Soil (SAfSoil). The current study tested the previously proposed salinity indices on the northern Nile Delta region, Egypt. The results indicated that most of the indices were not suitable to detect the SAfSoil in the area, due to the interaction between the bare soils, salts, and urbanization. To resolve this issue, the current work suggested a new index for detecting and monitoring the SAfSoil in the Nile Delta region. The newly proposed index takes into consideration plant health, the salt crust at the surface of the soils, as well as urbanization. It facilitates the mapping processes of SAfSoil in the area compared to any other previously proposed index. In this respect, multi-temporal Landsat-7 and 8 satellite data, acquired in 2002, 2016, and 2021, were used. The new index was prepared using the 2002 data and verified using the 2016 and 2021 data. Field measurements and data collected during 2002, 2016, and 2021 were utilized as ground truth data to assess the accuracy of the results obtained from the proposed index. The evaluation of the results indicated that the accuracy assessment for 2002, 2016, and 2021 images was 94.58, 96.08, and 95.68%, respectively. Finally, the effectiveness of using remote sensing in detecting and mapping SAfSoil is outlined.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Detecting and Mapping Salt-Affected Soil with Arid Integrated Indices in Feature Space Using Multi-Temporal Landsat Imagery

et al. 2022

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“…A grid search-support vector machine (GS-SVR) regression model was then established to monitor the soil salt content in the Bosten Lake watershed by optimizing the spectral index. The specific research objectives were as follows: (1) to explore the universality of the optimal estimation parameters in previous studies in the arid Bosten Lake watershed, (2) to select the optimal estimation parameters and establish a GS-SVR regression model, and (3) to map soil salinity in the Bosten Lake watershed. The purpose of this study is to lay a foundation for soil salinization monitoring in arid areas and further provide a scientific basis for soil salinization monitoring in Central Asia.…”

Section: Plos Onementioning

confidence: 99%

“…Soil salinization has become an important research issue in the construction of an ecological civilization and the monitoring of global change [1][2][3]. The low fertility of saline soil affects crop growth and hinders sustainable development of the agricultural economy.…”

Section: Introductionmentioning

confidence: 99%

Estimation of soil salt content in the Bosten Lake watershed, Northwest China based on a support vector machine model and optimal spectral indices

Hou

Rusuli²

2023

PLoS ONE

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Low-cost and efficient dynamic monitoring of surface salinization information is critical in arid and semi-arid regions, we conducted a remote sensing inversion exercise for soil salinity in the Bosten Lake watershed in Xinjiang, Northwest China, with a total area of about 43,930 km2, a typical watershed in an arid area. Sentinel MSI and Landsat OLI data were combined with measured soil salinity data in July 2020, and optimal combination bands were selected based on characteristic bands to create a grid search-support vector machine (GS-SVM) inversion model of soil salt content. The maximum value of soil salt content in the Bosten Lake watershed was 11.8 g/kg. The minimum value was 0.41 g/kg, and the average value was 4.77 g/kg, soil salinization is serious. The results of previous studies were applied to the estimation of salt content in Bosten Lake watershed and could not meet the monitoring requirements of the study area, R2 < 0.3. The GS-SVM soil salinity monitoring model was established based on the optimal DI, RI, and NDI remote sensing indexes for the Bosten Lake watershed. After model verification, it was found that the optimal model of image data was the Landsat OLI first-derivative model with R2 of 0.64, RMSE of 3.12, and RPD of 1.64, indicating that the prediction ability of the model was high. We used the first-order derivative model of Landsat OLI data to map the soil salt content in the Bosten Lake watershed in arid area, and found that soil salt content in most of the study area was between 10 and 20 g/kg, indicating severe salinization. This study not only reveals the distribution characteristics of salinization in Bosten Lake watershed, but also provides a scientific basis for soil salinization monitoring in Central Asia to lay a foundation for further soil salinization monitoring in arid areas.

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Automated delineation of salt-affected lands and their progress in coastal India using Google Earth Engine and machine learning techniques

Kabiraj

Jayanthi

Samynathan

et al. 2023

Environ Monit Assess

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Soil salinity assessment of a natural pasture using remote sensing techniques in central Anatolia, Turkey

Cited by 11 publications

References 45 publications

Detecting and Mapping Salt-Affected Soil with Arid Integrated Indices in Feature Space Using Multi-Temporal Landsat Imagery

Detecting and Mapping Salt-Affected Soil with Arid Integrated Indices in Feature Space Using Multi-Temporal Landsat Imagery

Estimation of soil salt content in the Bosten Lake watershed, Northwest China based on a support vector machine model and optimal spectral indices

Automated delineation of salt-affected lands and their progress in coastal India using Google Earth Engine and machine learning techniques

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