Multispectral satellite imagery to quantify in-field soil moisture variability

Abstract

As pressure on available water resources increases, the need to exploit technology in order to produce more food with less water becomes crucial.The technological hardware requisite for precise water delivery methods, such as variable rate irrigation, is commercially available. Despite that, techniques to formulate a timely, accurate prescription for those systems are inadequate. Spectral vegetation indices are often used to gauge crop vigor and related parameters (e.g., leaf nitrogen [N] content). However, research heretofore rarely addresses the influence of soil moisture on the indices.The objectives of this study were to determine (1) if vegetation indices derived from multispectral satellite imagery could assist in quantifying soil moisture variability in irrigated maize (Zea mays L.) production, and (2) the period of time that a single image is representative of soil moisture. A variable rate irrigation pivot was used to form six water treatment zones. Each was equipped with tensiometers installed in the center of the plots at 20, 45, and 75 cm depths to individually monitor conditions in the water treatment zones.Water was applied for each treatment as a percentage of the estimated evapotranspiration (ET) requirement: 40%, 60%, 80%, 100%, 120%, and 140%. Data collected from tensiometers was paired with the image pixels corresponding to its ground location. Statistical analysis was performed separately to assess whether vegetation indices are representative of soil moisture at several crop growth stages. Findings from this study indicate that Red Edge Normalized Difference Vegetation Index could quantify soil moisture tension variability atV6 (six leaf; r2 = 0.850, p = 0.009) andV9 (nine leaf; r2 = 0.913, p = 0.003) crop growth stages. Results suggest that satellite-derived vegetation indices may be useful for creating time-sensitive characterizations of soil moisture variability. Further study is necessary to investigate additional crop growth stages, more crops, and other sources of multispectral imagery.