Thermography for soil salinity assessment

Increased soil salinity is a significant agricultural problem that decreases yields for common crops. It is quite dynamic in time, which makes timely soil salinity data a crucial point in agricultural management. Remote sensing can provide the necessary spatial and temporal resolution, but widely accepted methods and techniques for soil salinity monitoring using remote sensing are not present yet. Canopy temperature change is one of the stress indicators in plants. Its behaviour in response to salt stress on individual plant level is well studied, but its potential for field or landscape scale studies is not investigated yet. In this study, potential of satellite and UAV thermography for plot, regional and global scale soil salinity assessment was investigated. The results demonstrated that using thermography for soil salinity monitoring is a valuable approach. It proved to be more universal, compared with previously used approaches, like vegetation indices. The universality has been reflected both in the diverse soil and vegetation conditions, under which the thermography approach was tested.</p

Digitalization as a tool for solving control problems

The article is devoted to the consideration of “digitalization” concept as a tool for solving control problems. The problems of digital twins formation are discussed and two directions for digital models creation are presented. The necessity of using a natural-model approach, methods of natural-mathematical modeling, similarity theory for building digital models is noted

Satellite thermography for soil salinity assessment of cropped areas in Uzbekistan

A change of canopy temperature can indicate stress in vegetation. Use of canopy temperature to assess salt stress in specific plant species has been well studied in laboratory and greenhouse experiments, but its potential for use in landscape-level studies using remote sensing techniques has not yet been explored. Our study investigated the application of satellite thermography to assess soil salinity of cropped areas at the landscape level. The study region was Syrdarya Province, a salt-affected, irrigated semi-arid province of Uzbekistan planted mainly to cotton and wheat. We used moderate-resolution imaging spectroradiometer satellite images as an indicator for canopy temperature and the provincial soil salinity map as a ground truth dataset. Using analysis of variance, we examined relations among the soil salinity map and canopy temperature, normalized difference vegetation index, enhanced vegetation index, and digital elevation model. The results showed significant correlations between soil salinity and canopy temperature, but the strength of the relation varied over the year. The strongest relation was observed for cotton in September. The calculated F values were higher for canopy temperature than for the other indicators investigated. Our results suggest that satellite thermography is a valuable landscape-level approach for detecting soil salinity in areas under agricultural crops

Global mapping of soil salinity change

Soil salinity increase is a serious and global threat to agricultural production. The only database that currently provides soil salinity data with global coverage is the Harmonized World Soil Database, but it has several limitations when it comes to soil salinity assessment. Therefore, a new assessment is required. We hypothesized that combining soil properties maps with thermal infrared imagery and a large set of field observations within a machine learning framework will yield a global soil salinity map. The thermal infrared imagery acts as a dynamic variable and allows us to characterize the soil salinity change. For this purpose we used Google Earth Engine computational environment. The random forest classifier was trained using 7 soil properties maps, thermal infrared imagery and the ECe point data from the WoSIS database. In total, six maps were produced for 1986, 2000, 2002, 2005, 2009, 2016. The validation accuracy of the resulting maps was in the range of 67–70%. The total area of salt affected lands by our assessment is around 1 billion hectares, with a clear increasing trend. Comparison with 3 studies investigating local trends of soil salinity change showed that our assessment was in correspondence with 2 of these studies. The global map of soil salinity change between 1986 and 2016 was produced to characterize the spatial distribution of the change. We conclude that combining soil properties maps and thermal infrared imagery allows mapping of soil salinity development in space and time on a global scale

Soil salinity assessment through satellite thermography for different irrigated and rainfed crops

The use of canopy thermography is an innovative approach for salinity stress detection in plants. But its applicability for landscape scale studies using satellite sensors is still not well investigated. The aim of this research is to test the satellite thermography soil salinity assessment approach on a study area with different crops, grown both in irrigated and rainfed conditions, to evaluate whether the approach has general applicability. Four study areas in four different states of Australia were selected to give broad representation of different crops cultivated under irrigated and rainfed conditions. The soil salinity map was prepared by the staff of Geoscience Australia and CSIRO Land and Water and it is based on thorough soil sampling together with environmental modelling. Remote sensing data was captured by the Landsat 5 TM satellite. In the analysis we used vegetation indices and brightness temperature as an indicator for canopy temperature. Applying analysis of variance and time series we have investigated the applicability of satellite remote sensing of canopy temperature as an approach of soil salinity assessment for different crops grown under irrigated and rainfed conditions. We concluded that in all cases average canopy temperatures were significantly correlated with soil salinity of the area. This relation is valid for all investigated crops, grown both irrigated and rainfed. Nevertheless, crop type does influence the strength of the relations. In our case cotton shows only minor temperature difference compared to other vegetation classes. The strongest relations between canopy temperature and soil salinity were observed at the moment of a maximum green biomass of the crops which is thus considered to be the best time for application of the approach

UAV based soil salinity assessment of cropland

Increased soil salinity is a significant agricultural problem that decreases yields for common agricultural crops. Its dynamics require cost and labour effective measurement techniques and widely acknowledged methods are not present yet. We investigated the potential of Unmanned Aerial Vehicle (UAV) remote sensing to measure salt stress in quinoa plants. Three different UAV sensors were used: a WIRIS thermal camera, a Rikola hyperspectral camera and a Riegl VUX-SYS Light Detection and Ranging (LiDAR) scanner. Several vegetation indices, canopy temperature and LiDAR measured plant height were derived from the remote sensing data and their relation with ground measured parameters like salt treatment, stomatal conductance and actual plant height is analysed. The results show that widely used multispectral vegetation indices are not efficient in discriminating between salt affected and control quinoa plants. The hyperspectral Physiological Reflectance Index (PRI) performed best and showed a clear distinction between salt affected and treated plants. This distinction is also visible for LiDAR measured plant height, where salt treated plants were on average 10 cm shorter than control plants. Canopy temperature was significantly affected, though detection of this required an additional step in analysis – Normalised Difference Vegetation Index (NDVI) clustering. This step assured temperature comparison for equally vegetated pixels. Data combination of all three sensors in a Multiple Linear Regression model increased the prediction power and for the whole dataset R2 reached 0.46, with some subgroups reaching an R2 of 0.64. We conclude that UAV borne remote sensing is useful for measuring salt stress in plants and a combination of multiple measurement techniques is advised to increase the accuracy.</p