Monitoring Olive Oil Mill Wastewater Disposal Sites Using Sentinel-2 and PlanetScope Satellite Images: Case Studies in Tunisia and Greece

Mediterranean countries are known worldwide for their significant contribution to olive oil production, which generates large amounts of olive mill wastewater (OMW) that degrades land and water environments near the disposal sites. OMW consists of organic substances with high concentrations of phenolic compounds along with inorganic particles. The aim of this study is to assess the effectiveness of satellite image analysis techniques using multispectral satellite data with high (PlanetScope, 3 x 3 m) and medium (Sentinel-2, 10 x 10 m) spatial resolution to detect Olive Mill Wastewater (OMW) disposal sites, both in the SidiBouzid region (Tunisia) and in the broader Rethymno region on the island of Crete, (Greece). Documentation of the sites was carried out by collecting spectral signatures of OMW at temporal periods. The study integrates the application of a variety of spectral vegetation indices (VIs), such as the Normalized Difference Vegetation Index (NDVI), in order to evaluate their efficiency in detecting OMW disposal areas. Furthermore, a set of image-processing methods was applied on satellite images to improve the monitoring of OMW ponds including the false-color composites (FCC), the Principal Component Analysis (PCA), and image fusion. Finally, different classification algorithms, such as the ISODATA, the maximum likelihood (ML), and the Support Vector Machine (SVM) were applied to both satellite images in order to assist in the overall approach to effectively detect the sites. The results obtained from different approaches were compared, evaluating the efficiency of Sentinel-2 and PlanetScope images to detect and monitor OMW disposal areas under different morphological environments.

Automated summary

This study aims to assess the effectiveness of satellite image analysis techniques in detecting Olive Mill Wastewater (OMW) disposal sites in Mediterranean countries. The study collected spectral signatures of OMW and applied various spectral vegetation indices and image processing methods, as well as different classification algorithms, to detect and monitor these sites. The results show that Sentinel-2 and PlanetScope images have high efficiency in detecting and monitoring OMW disposal areas under different morphological environments.