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Multispectral and Microwave Remote Sensing Models to Survey Soil Moisture and Salinity
Author(s) -
Periasamy Shoba,
Shanmugam Ramakrishnan S.
Publication year - 2017
Publication title -
land degradation and development
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.403
H-Index - 81
eISSN - 1099-145X
pISSN - 1085-3278
DOI - 10.1002/ldr.2661
Subject(s) - environmental science , water content , multispectral image , salinity , soil salinity , thematic mapper , vegetation (pathology) , remote sensing , soil water , multispectral pattern recognition , soil science , hydrology (agriculture) , satellite imagery , geology , oceanography , geotechnical engineering , medicine , pathology
Soil moisture stress and salinity are considered as a major form of land degradation in rain‐fed agricultural regions. The study has been carried out for four distinct periods such as 2001, 2005, 2010, and 2015 that was selected according to the climatic variations that occurred more than a decade. The multispectral remote sensing‐based empirical models were employed on Enhanced Thematic Mapper Plus and Operational Land Imager imageries to estimate the rate of soil moisture stress and salinity from 2001–2015. The rate of soil moisture stress has been magnified to 143%, and salinity was increased by 70% particularly from 2005–2010 when the drought period occurred. The reliability of identifying the saline‐affected soils from the multispectral remote sensing models was significantly affected ( R 2 = 0.39) because of the extensive distribution of Nerium oleander plants and water logging state in the study region. The modified microwave water cloud model revealed the three‐layer information such as N. oleander , soil, and vegetation such that an imaginary part of the dielectric constant derived from simplified Hallikainen empirical model has got good correlation ( R 2 = 0.73) with ground electrical conductivity measurements. Copyright © 2016 John Wiley & Sons, Ltd.