Using multispectral images to determine the salinity of soils in Ingulets irrigation system in the justification of management measures for chemical reclamation

The publication presents the use of data from multispectral space images to substantiate management measures for chemical reclamation of saline soils of the Ukraine irrigation system. The study is to develop a method of using satellite data to remotely determine the salinity of soils to support the management measures on the chemical soil improvement by example some fields of Ingulets irrigation system. Landsat 8 OLI images were used to obtain NDVI, soil salinity assessment indices, namely VSSI, Salinity index and normalized soil salinity index (NDSI). The verification data on the spatial distribution of salinity are taken from the report on soil-salt survey of the Ingulets irrigated massif. Work with satellite images and calculation of indices was performed using ERDAS IMAGINE 2015. Quantitative analysis of pixels, their visualization using the color spectrum was carried out in ArcMap 10.8. Validation for the conditions of Ukraine on the southern chernozems of the salt indices (VSSI, NDSI, SI) showed the best suitability of NDSI. Using the calculated ranges of index that characterize the gradation of salinity, their area percentage has been determined for each experimental field of the pilot object. The salinity areas according to each gradation were obtained on the basis of NDSI. Quantitative values of the management measure, the dose of chemical ameliorants, differentially for each of the fields are obtained using calculation methods using the author’s information technology. The total amount of phosphogypsum for chemical reclamation is recommended. The results of the study show that Landsat 8 OLI images show a high potential for spatio-temporal monitoring of salinity of the upper soil layers. This study will be useful for planning agricultural activities by mapping the salinity of the soil with the calculation of doses of chemical ameliorants to reduce economic losses in climate change. The proposed norms of gypsum application can serve as a guide for the agricultural producer when making a decision on chemical reclamation of agricultural lands. Based on a combination of satellite monitoring data and calculations of chemical reclamation doses according to the author’s online calculator, the farmer will be able to assess the feasibility and economic efficiency of chemical land reclamation measures. An additional practical value of the method of remote determination of boundaries and area of salinity is the ability to plan the selection of soil samples from certain points of the field, optimizing the number of soil samples for their chemical analysis in the laboratory. Our proposed method, which estimates soil salinity using satellite images and suggests doses of chemical ameliorants using information technology, can be potentially useful as a rapid approach to detecting soil salinity in other regions of Ukraine and the world at low cost and high accuracy

Change on detection of vegetation cover and soil salinity using GIS technique in Diyala Governorate, Iraq

Soil salinity is one of the most important problems of land degradation, that threatening the environmental, economic and social system. The aim of this study to detect the changes in soil salinity and vegetation cover for Diyala Governorate over the period from 2005 to 2020, through the use of remote sensing techniques and geographic information system. The normalized difference vegetation index (NDVI) and salinity index (SI) were used, which were applied to four of the Landsat ETM+ and Landsat OLI satellite imagery. The results showed an increase in soil salinity from 7.27% in the period 2005–2010 to 27.03% in 2015–2020, as well as an increase in vegetation from 10% to 24% in the same period. Also the strong inverse correlation between the NDVI and the SI showed that vegetation is significantly affected and directly influenced by soil salinity changes

Dielectric Properties of Glass Beads with Talc as a Reference Material for Calibration and Verification of Dielectric Methods and Devices for Measuring Soil Moisture

This paper presents dielectric measurements of talc, glass beads, and their mixtures under different moisture and salinity levels. The measurements were conducted using a prototype seven-rod probe (15 mm long central rod) connected to a single port of vector network analyzer. The samples were moistened with distilled water and KCl solutions in order to obtain six different moisture content levels. The complex dielectric permittivity was determined from vector network analyzer reflection-coefficient measurements based on the open-water-liquid calibration procedure. Next, the fitting of volumetric water content–real part of dielectric permittivity calibration curves was performed for each material at selected frequencies, and the obtained relations were compared with well-known calibration equations. Additionally, a salinity index for the tested materials was calculated. It was concluded that pure talc is not an optimal material for the calibration and verification of dielectric methods. The calibration curves obtained for glass beads and the mixtures of glass beads with talc gave results close to well-known reference calibration functions. Additionally, the addition of talc caused the data points to be less scattered. Moreover, the values of the salinity index for the tested materials were in a good agreement with literature data for sand. The obtained results indicated that glass beads with the addition of talc can be used as a reference material for the calibration and verification of dielectric methods and devices for soil moisture measurement.

Soil salinity assessment using temporal series of Sentinel2 satellite images in irrigated paddy fields of Western Africa

<p>Salinization and alkalinization are worldwide among the soil degradation threats in irrigated schemes affecting soil productivity. Niger River basin irrigated schemes in the Sahel arid zone are no exception (ONAHA, 2011). The use of remote sensing for identifying and evaluating the level of these phenomena is an interesting tool. The launching of the Sentinel2 satellite constellation (2015) brings new perspectives with high spectral and temporal resolutions images. The aim of this study was to develop a methodology for detection of salt-affected soils in this climatic condition.</p><p>To achieve our goal, we used two types of data: remote sensing and ground truth data.</p><p>Two complementary approaches were used: one by observing salinity on bare soil by the use of salinity index (SI) and the other by observing the indirect effects of salinity on the vegetation during eight (8) rice growth phases  using vegetation index NDVI.</p><p>Remote sensing data were acquired from multi temporal sentinel2 images over 4 years (from 11/12/2015 to 30/11/2019). One hundred and fifty seven (157) images were downloaded (one image each 5 days) and corrected from atmospheric effects and some bands resampled to 5 m using python software. The salinity and vegetation indices were calculated. NDVI index was calculated and NDVI integral between NDVI curve and the threshold of 0.21 NDVI calculated for the eight growing cycles.</p><p>Ground truth data were collected in 2019 during the dry growing season (January – may 2019) from 24 calibration plots and 40 validation plots. One hundred and twenty (120) soil samples collected and analyzed for pH and electrical conductivity and finally forty six (46) biomass samples were collected, air dried and weighed for biomass yield and 46 grains samples collected for grain yield.</p><p>NDVI integral proved to be good indicator for yield variations and could distinguish crops behavior according to the growing period. It also makes it possible to distinguish plots which were not cultivated or with weak growth due to strong constraints of which the main one is salinity. It showed also that the effect of salinity on growth differs according to the growing season and the possibility of managing irrigation. Bare soil analysis distinguishes fields with different salinity indexes despite the low number of dates for which bare soil can be observed.</p><p>Ascending Hierarchical Classification (AHC) enabled to identify four classes of NDVI dynamics over time and bare soil salinity index. High saline soils according to direct soil measurements were related to the class characterized by high frequency of no-cultivation during the dry season and low NDVI integral during the wet season. Multi-temporal Sentinel2 images analysis enabled therefore to detect rice crop fields affected by salinity through its influence on crop behavior. This approach will be tested over the whole paddy schemes of the Niger River valley.</p>

Soil salinity assessment by using near-infrared channel and Vegetation Soil Salinity Index derived from Landsat 8 OLI data: a case study in the Tra Vinh Province, Mekong Delta, Vietnam

Salinity intrusion is a pressing issue in the coastal areas worldwide. It affects the natural environment and causes massive economic loss due to its impacts on the agricultural productivity and food safety. Here, we assessed the salinity intrusion in the Tra Vinh Province, in the Mekong Delta of Vietnam. Landsat 8 OLI image was utilized to derive indices for soil salinity estimate including the single bands, Vegetation Soil Salinity Index (VSSI), Soil Adjusted Vegetation Index (SAVI), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Salinity Index (NDSI). Statistical analysis between the electrical conductivity (EC1:5, dS/m) and the environmental indices derived from Landsat 8 OLI image was performed. Results indicated that spectral values of near-infrared (NIR) band and VSSI were better correlated with EC1:5 (r2 = 0.8 and r2 = 0.7, respectively) than the other indices. Comparative results show that soil salinity derived from Landsat 8 was consistent with in situ data with coefficient of determination, R2 = 0.89 and RMSE = 0.96 dS/m for NIR band and R2 = 0.77 and RMSE = 1.27 dS/m for VSSI index. Findings of this study demonstrate that Landsat 8 OLI images reveal a high potential for spatiotemporally monitoring the magnitude of soil salinity at the top soil layer. Outcomes of this study are useful for agricultural activities, planners, and farmers by mapping the soil salinity contamination for better selection of accomodating crop types to reduce economical loss in the context of climate change. Our proposed method that estimates soil salinity using satellite-derived variables can be potentially useful as a fast-approach to detect the soil salinity in the other regions with low cost and considerable accuracy.