Assessment of the potential use of the Radar Vegetation Index (RVI) using Sentinel-1 imagery for monitoring vegetation cover: A case study in Thanh Hoa province, Vietnam

Abstract

Changes in the surface vegetation cover occur continuously over time as a result of the influence of anthropogenic activities, natural hazards, and the dynamics of vegetation development. The Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) are two examples of optical remote sensing indices that are routinely used to monitor vegetation cover at the present time. The optical indices, on the other hand, are frequently constrained by the weather conditions, which results in the collecting of data being interrupted. In order to overcome this constraint, the authors propose the utilization of the Radar Vegetation Index (RVI), which is produced from Synthetic Aperture Radar (SAR) data obtained from Sentinel-1A, for the purpose of monitoring landscape vegetation cover. The research findings show that RVI values follow a pattern of variation that corresponds to the stages of paddy rice growth. Additionally, the Pearson correlation coefficient (r) and p-value were employed to examine the correlation between the RVI (provided by Sentinel-1) and the NDVI (provided by Sentinel-2) for various vegetation categories. Perennial crops, industrial crops, and paddy rice demonstrated correlation coefficients of 0.675, 0.700, and 0.563, respectively, with p-values at or below 0.05. In particular for industrial and perennial crops, our results show that RVI often varies in correlation with NDVI. It is confirmed that the RVI is sensitive to the dynamics of vegetation, which is comparable to that of standard optical indices such as the NDVI. This study contributes to the enhancement of the usefulness of RVI in vegetation cover monitoring.