A Study of the Relationships between Depths of Soil Constraints and Remote Sensing Data from Different Stages of the Growing Season

• Published in: Remote sensing (Basel, Switzerland) Switzerland), 2023-07, Vol.15 (14), p.3527
• Main Authors: Ulfa, Fathiyya, Orton, Thomas G., Dang, Yash P., Menzies, Neal W.
• Format: Article
• Language: English
• Subjects: Agricultural production; Crop growth; Crop yield; Crops; Environmental aspects; EVI; Growing season; Growth; Hypotheses; Measurement; Plant roots; R&D; Remote sensing; Research & development; Root development; Root zone; Roots; Salinity; Satellites; Sodium; soil constraints; soil constraints severity; Soil depth; Soil investigations; Soils; Soils, Salts in; Spatial variations; subsoil; Subsoils; Topsoil; Vegetation; Vegetation index; vegetation index consistency
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs15143527

The presence of salinity and sodicity in the root zone can limit root development and impact crop yield. Topsoil constraints are likely to have the greatest impact on crop growth early in the growing season, when plant roots are still shallow. Later in the growing season, subsoil constraints may have a greater impact as roots reach deeper into the soil. This study investigated whether different patterns of spatial variation in crop growth would be evident in remote sensing data captured from different stages of the growing season, with the aim of providing a means of indicating whether soil constraints in the topsoil and in the subsoil might be impacting crop growth. If a topsoil constraint is impacting growth, we might expect its effects to show through a negative correlation between the soil constraint and the early-season vegetation index. However, we would not expect to observe the impact of a subsoil constraint until later in the season (when roots have reached the constraint). To test the results from the analysis of remote sensing data, we used soil data from five fields from across Australia’s northern grains-growing region. We used these data to assess soil constraint severity and correlations between the soil constraints and enhanced vegetation index (EVI). The results of the study were inconclusive, and it was difficult to identify a dominant soil constraint with a clear relationship to crop growth. The soil data were also insufficient to draw conclusions about the depths of any dominant soil constraints. Furthermore, there was a lot of subjectivity in the interpretations of the correlations between remote sensing and soil data. The study also investigated the consistency of the spatial variation in EVI over multiple years, but the results were still inconclusive. In conclusion, this study highlights the challenges of using remote sensing data to diagnose soil constraints in agricultural settings. While remote sensing can provide useful insights into crop growth, interpreting these data and drawing meaningful conclusions about soil constraints requires further research and development.