Estimating and Mapping NDVI and NDMI Indexes by Remote Sensing of Olive Orchards in Different Tunisian Regions

Remote sensing information can be used to monitor water stress in olive orchards. The focus of this chapter is to estimate and to map vegetation and moisture indexes by remote sensing of olive trees groves in different regions of Tunisia. The experimental study was carried out on different experimental plots in Kairouan (rain-fed, semi-intensive and intensive) and in Jendouba (rain-fed and intensive). For the determination of the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Moisture Index (NDMI), satellite images were used from Sentinel 2. The calculations were based on cloudless images. The results obtained by remote sensing show that NDVI values, during the experimental period (2019–2020), depend on the study region, cropping system, vegetation cover, planting density and the growing season. The highest values are recorded at the level of the Kairouan Intensive plot (0.95) and Jandouba Rainfed plot (0.77). The low values correspond to those of Kairouan semi-intensive plot (0.16) and Kairouan rainfed plot (0.13). For NDMI, the highest values correspond to the plots of Jandouba Irrigated plot (0.39), Jandouba Rainfed plot (0.39) and Kairouan Intensive plot (0.37). The NDVI values are in agreement with the results of NDMI and the cultivation mode of olive groves. According to these results, we deduce that these plots are therefore characterized by a high canopy and a well-irrigated state of the olive groves. On the other hand, the values recorded at the level of semi-intensive and rain-fed plots in the Kairouan region show that these olive groves suffer from water stress. The analysis of the correlations between NDVI and NDMI confirms the close relationship between these two parameters with high R2 values (between 0.63 and 0.98).