A PLSR model to predict soil salinity using Sentinel-2 MSI data

A model to predict the sequential behavior of healthy blood donors using data mining

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Modeling and Mapping of Soil Salinity with Reflectance Spectroscopy and Landsat Data Using Two Quantitative Methods (PLSR and MARS)

The monitoring of soil salinity levels is necessary for the prevention and mitigation of land degradation in arid environments. To assess the potential of remote sensing in estimating and mapping soil salinity in the El-Tina Plain, Sinai, Egypt, two predictive models were constructed based on the measured soil electrical conductivity (ECe) and laboratory soil reflectance spectra resampled to La...

Soil salinity detection using RS data

Soil salinity refers to the state of accumulation of soluble salts in the root zone to adversely affect the growth of most crops. It is a severe environmental degradation that impedes crop growth and production [1]. The conventional processes for the detection, monitoring and mapping of salt-affected soil are known to be difficult and dynamic.(206khan). Remote Sensing has the ability to predict...

Developing a Fuzzy Logic Model to Predict Asphaltene Precipitation during Natural Depletion based on Experimental Data

Volumetric soil moisture estimation using Sentinel 1 and 2 satellite images

Surface soil moisture is an important variable that plays a crucial role in the management of water and soil resources. Estimating this parameter is one of the important applications of remote sensing. One of the remote sensing techniques for precise estimation of this parameter is data-driven models. In this study, volumetric soil moisture content was estimated using data-driven models, suppor...