Abstract
Soil salinity undermines global agriculture by reducing crop yield and impairing soil quality. Irrigation management can help control salinity levels within the soil root-zone. To best manage water and soil resources, accurate regional-scale inventories of soil salinity are needed. The past decade has seen several successful applications of soil salinity remote sensing. Two salinity remote sensing approaches exist: direct assessment based on analysis of surface soil reflectance (the most popular approach), and indirect assessment of root-zone (e.g., 0-1 m) soil salinity based on analysis of crop canopy reflectance. In this perspective paper, we call on researchers and funding agencies to pay greater attention to the indirect approach because it is better suited for surveying agriculturally important lands. A joint effort between agricultural producers, irrigation specialists, environmental scientists, and policy makers is needed to better manage saline agricultural soils, especially because of projected future water scarcity in arid and semi-arid irrigated areas. The remote sensing community should focus on providing the best tools for mapping and monitoring salinity in such areas, which are of vital relevance to global food production.
Highlights
Soil salinity is a major threat to crop production and sustainable agriculture (FAO and ITPS, 2015)
This paper provides an overview of the surface salinity and root-zone salinity assessment approaches, a short review of milestone papers on root-zone salinity assessment, a description of the limitations of each approach, and suggests directions for future opportunities
The sustainability of irrigation practices must be preserved in such areas because of the expected future increases in food demand
Summary
Soil salinity is a major threat to crop production and sustainable agriculture (FAO and ITPS, 2015). Wu et al (2014) used multi-year maxima of vegetation indices to map soil salinity in Iraq They used a multi-scale platform consisting of MODIS and Landsat 7 (USGS and NASA, USA) imagery because MODIS data alone would provide estimations too coarse for agricultural applications. Spatial and temporal extrapolations should always be minimized Vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), can be used to map salinity, but are generally not stress specific: they measure plant status. To increase the extent of surveyed land in a cost-effective manner, local salinity maps can be created using near-ground electromagnetic surveys and apparent soil electrical conductivity directed soil sampling (Corwin et al, 2012), as done by Lobell et al (2010), Wu et al (2014), and Scudiero et al (2015). This can be done through (spatiallyindependent) resampling (e.g., cross validation) and/or by independent validation
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