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

Abstract

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 × 3 m) and medium (Sentinel-2, 10 × 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.

Twenty Years of Remote Sensing Applications Targeting Landscape Analysis and Environmental Issues in Olive Growing: A Review

“…GeoEye, WorldView-2, and -3 images were used to detect OOMW disposal areas [57] and monitor olive trees' health status using VIs [96,97]. Another important commercial source of data, albeit limitedly used RS research in olive growing [41,98,99], is the Planetscope constellation launched in the middle of the past decade. PlanetScope constellation is composed of many small nano-satellites, 3U CubeSats, also called "Doves" and equipped with MS sensors providing up to 3 m spatial resolution with a one-day revisiting time [100,101].…”

“…As for the term "NDVI", the most widely used of indices with the largest number of researches in which it was used, and "vegetation indices", we have indicated in Table 1 the main indices used in the researches analyzed. [40,41] Greenness index GI R554/R677 * [45] Green Normalized Vegetation Index [46] GNDVI [38,40,47,48] Green Ratio Vegetation Index [49] GRVI NIR Green [42] Inverse Ratio Vegetation Index [39] IRVI…”

“…Red NIR [38,42,43] (2NIR+1) 2 −(6NIR−5 √ Red )−0.5 [45] Modified Simple Ratio [51] MSR [40,47] Modified Soil Adjusted Vegetation Index [38,40,41,45,47] Modified triangular vegetation index…”

“…Normalized Ratio Vegetation Index [55] NRVI (RVI − 1)/(RVI + 1) [42,43] Normalized Difference Vegetation Index [56]] NDVI [38,40,42,43,45,47,48,[57][58][59][60][61][62][63][64][65][66] Optimized Soil Adjusted Vegetation Index [67] OSAVI 1.16 [40,41,43,45,47] Renormalized Difference Vegetation Index [68] RDVI…”

“…Simple Ratio [69] SR NIR Red [40][41][42]47] Soil Adjuted Vegetation Index [70] SAVI Difference Vegetation Index…”