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Modelling the relationship between groundwater depth and NDVI using time series regression with Distributed Lag M
2018
South African Journal of Geomatics
Groundwater plays a key role in hydrological processes, including in determining aboveground vegetal growth characteristics and species distribution. This study aimed at estimating time-series data of Normalized Difference Vegetation Index (NDVI) using groundwater depth as a predictor in two land cover types: grassland and shrubland. The study also investigated the significance of past (lagged) groundwater and NDVI in estimating the current NDVI. Results showed that lagged groundwater depth and
doi:10.4314/sajg.v7i2.4
fatcat:wm2fdqq7ireirgpdg4upr5yhka