Monitoring Grass Phenology and Hydrological Dynamics of an Oak–Grass Savanna Ecosystem Using Sentinel-2 and Terrestrial Photography

• Published in: Remote sensing (Basel, Switzerland) Vol. 12; no. 4; p. 600
• Main Authors: Gómez-Giráldez, Pedro J., Pérez-Palazón, María J., Polo, María J., González-Dugo, María P.
• Format: Journal Article
• Language: English
• Published: MDPI AG 01-02-2020
• Subjects: hydrology; oak-grass savanna; phenology; sentinel-2; vegetation indices
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs12040600

Annual grasslands are an essential component of oak savanna ecosystems as the primary source of fodder for livestock and wildlife. Drought resistance adaptation has led them to complete their life cycle before serious soil and plant water deficits develop, resulting in a close link between grass phenology and soil water dynamics. In this work, these links were explored using a combination of terrestrial photography, satellite imagery and hydrological ground measurements. We obtained key phenological parameters of the grass cycle from terrestrial camera data using the Green Chromatic Coordinate (GCCc) index. These parameters were compared with those provided by time-series of vegetation indices (VI) obtained from Sentinel-2 (S2) satellites and time-series of abiotic variables, which defined the hydrology of the system. The results showed that the phenological parameters estimated by the S2 Normalized Difference Vegetation Index (NDVI) (r = 0.83, p < 0.001) and soil moisture (SM) (r = 0.75, p < 0.001) presented the best agreement with ground-derived observations compared to those provided by other vegetation indices and abiotic variables. The study of NDVI and SM dynamics, that was extended over four growing seasons (July 2015–May 2019), showed that the seasonality of both variables was highly synchronized, with the best agreements at the beginning and at the end of the dry seasons. However, stage changes were estimated first by SM, followed by NDVI, with a delay of between 3 and 10 days. These results support the use of a multi-approach method to monitor the phenology and the influence of the soil moisture dynamic under the study conditions.