Assessing vegetation response to soil moisture fluctuation under extreme drought using sentinel-2

West, Harry; Quinn, Nevil; Horswell, Michael; White, Paul

Abstract

© 2018 by the authors. The aim of this study was to determine the extent to which Sentinel-2 Normalised Difference Vegetation Index (NDVI) reflects soil moisture conditions, and whether this product offers an improvement over Landsat-8. Based on drought exposure, cloud-free imagery availability, and measured soil moisture, five sites in the Southwestern United States were selected. These sites, normally dry to arid, were in various states of drought. A secondary focus was therefore the performance of the NDVI under extreme conditions. Following supervised classification, the NDVI values for one-kilometre radius areas were calculated. Sentinel-2 NDVI variants using Spectral Bands 8 (10 m spatial resolution), 5, 6, 7, and 8A (20 m spatial resolution) were calculated. Landsat-8 NDVI was calculated at 30 m spatial resolution. Pearson correlation analysis was undertaken for NDVI against moisture at various depths. To assess the difference in correlation strength, a principal component analysis was performed on the combination of all bands and the combination of the new red-edge bands. Performance of the red-edge NDVI against the standard near infrared (NIR) was then evaluated using a Steiger comparison. No significant correlations between Landsat-8 NDVI and soil moisture were found. Significant correlations at depths of less than 30 cm were present between Sentinel-2 NDVI and soil moisture at three sites. The remaining two sites were characterised by low vegetation cover, suggesting a cover threshold of approximately 30-40% is required for a correlation to be present. At all sites of significant positive moisture to NDVI correlation, the linear combination of the red-edge bands produced stronger correlations than the poorer spectral but higher spatial resolution band. NDVI calculated using the higher spectral resolution bands may therefore be of greater use in this context than the higher spatial resolution option. Results suggest potential for the application of Sentinel-2 NDVI in soil moisture monitoring, even in extreme environments. To the best of our knowledge, this paper represents the first study of this kind using Sentinel-2.

• Journal Article Type: Article
• Acceptance Date: Jun 21, 2018
• Online Publication Date: Jun 24, 2018
• Publication Date: Jul 1, 2018
• Deposit Date: Jun 25, 2018
• Publicly Available Date: Jun 25, 2018
• Journal: Water (Switzerland)
• Electronic ISSN: 2073-4441
• Publisher: MDPI
• Peer Reviewed: Peer Reviewed
• Volume: 10
• Issue: 7
• Article Number: 838
• DOI: https://doi.org/10.3390/w10070838
• Keywords: Sentinel-2, Landsat-8, Normalised Difference Vegetation Index, NDVI, soil moisture, extreme climates, remote sensing
• Public URL: https://uwe-repository.worktribe.com/output/866121
• Publisher URL: https://doi.org/10.3390/w10070838
• Contract Date: Jun 25, 2018