Sentinel-2 Satellite Imagery-Based Assessment of Soil Salinity in Irrigated Rice Fields in Portugal

Romeu Gerardo and Isabel P. de Lima ()
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Romeu Gerardo: Department of Civil Engineering, Faculty of Sciences and Technology, University of Coimbra, Rua Luís Reis Santos, 3030-788 Coimbra, Portugal
Isabel P. de Lima: Department of Civil Engineering, Faculty of Sciences and Technology, University of Coimbra, Rua Luís Reis Santos, 3030-788 Coimbra, Portugal

Agriculture, 2022, vol. 12, issue 9, 1-20

Abstract: Salinization is a major soil degradation threat in irrigated lands worldwide. In Portugal, it affects several pockets of irrigated agricultural areas, but the spatial distribution and intensity of soil salinity are not well known. Unlike conventional approaches to appraise soil salinity, remote sensing multispectral data have great potential for detecting, monitoring, and investigating soil salinity problems in agricultural areas. This study explores the assessment of soil salinity in irrigated rice cultivation fields using two types of multispectral-based indices calculated from Sentinel-2 satellite imagery: (i) vegetation indices (Normalized Difference Vegetation Index, Green Normalized Difference Vegetation Index, Generalized Difference Vegetation Index and Soil Adjusted Vegetation Index), to monitor the indirect effect of salinity on rice growth; and (ii) salinity indicators, namely those based on visible and near-infrared bands (Normalized Difference Salinity Index) and on shortwave infrared bands (Salinity Index ASTER). The data are for the Lower Mondego Valley (Central Portugal) and the period 2017–2018. Results revealed that salinity indices can be used for mapping soil salinity and constitute a valuable soil salinity assessment tool in rice cultivation areas affected by salinity issues. As there is less reported inventorying of spatial extent of such degradation in irrigated agricultural areas of Portugal, this innovative approach allowed by remote sensing technology can add to understanding the spatial extent of such areas and undertaking more such studies spatially and temporally.

Keywords: remote sensing; multispectral satellite data; agriculture; vegetation indices; salinity indices (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2022
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