Azizan, FA; Astuti, IS; Aditya, MI; Febbiyanti, TR; Williams, A; Young, A; Aziz, AA (2021). Using Multi-Temporal Satellite Data to Analyse Phenological Responses of Rubber (Hevea brasiliensis) to Climatic Variations in South Sumatra, Indonesia. REMOTE SENSING, 13(15), 2932.
Abstract
Land surface phenology derived from satellite data provides insights into vegetation responses to climate change. This method has overcome laborious and time-consuming manual ground observation methods. In this study, we assessed the influence of climate on phenological metrics of rubber (Hevea brasiliensis) in South Sumatra, Indonesia, between 2010 and 2019. We modelled rubber growth through the normalised difference vegetation index (NDVI), using eight-day surface reflectance images at 250 m spatial resolution, sourced from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua satellites. The asymmetric Gaussian (AG) smoothing function was applied on the model in TIMESAT to extract three phenological metrics for each growing season: start of season (SOS), end of season (EOS), and length of season (LOS). We then analysed the effect of rainfall and temperature, which revealed that fluctuations in SOS and EOS are highly related to disturbances such as extreme rainfall and elevated temperature. Additionally, we observed inter-annual variations of SOS and EOS associated with rubber tree age and clonal variability within plantations. The 10-year monthly climate data showed a significant downward and upward trend for rainfall and temperature data, respectively. Temperature was identified as a significant factor modulating rubber phenology, where an increase in temperature of 1 degrees C advanced SOS by similar to 25 days and EOS by similar to 14 days. These results demonstrate the capability of remote sensing observations to monitor the effects of climate change on rubber phenology. This information can be used to improve rubber management by helping to identify critical timing for implementation of agronomic interventions.
DOI:
10.3390/rs13152932
ISSN: