Modelling the relationship between groundwater depth and NDVI using time series regression with Distributed Lag M

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 vegetation conditions influence the amount of current NDVI. It was also observed that first lags of groundwater depth and NDVI were significant predictors of NDVI in grassland. In addition, first and second lags of NDVI were consistently significant predictors of NDVI in shrubland. This shows the importance of vegetation type when modelling the relationship between groundwater depth and NDVI.Keywords: Groundwater depth; Landsat NDVI; Time-series analysis; Distributed Lag Model

High and medium resolution satellite imagery to evaluate late holocene human-environment interactions in arid lands: A case study from the Central Sahara.

We present preliminary results of an Earth observation approach for the study of past human occupation and landscape reconstruction in the Central Sahara. This region includes a variety of geomorphological features such as palaeo-oases, dried river beds, alluvial fans and upland plateaux whose geomorphological characteristics, in combination with climate changes, have influenced patterns of human dispersal and sociocultural activities during the late Holocene. In this paper, we discuss the use of medium- and high-resolution remotely sensed data for the mapping of anthropogenic features and paleo- and contemporary hydrology and vegetation. In the absence of field inspection in this inaccessible region, we use different remote sensing methods to first identify and classify archaeological features, and then explore the geomorphological factors that might have influenced their spatial distribution.EM201