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 pheno...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-12-01
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| Series: | Agronomy |
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| Online Access: | https://www.mdpi.com/2073-4395/12/1/90 |
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| author | Wissal Issaoui Dimitrios D. Alexakis Imen Hamdi Nasr Athanasios V. Argyriou Evangelos Alevizos Nikos Papadopoulos Mohamed Hédi Inoubli |
| author_facet | Wissal Issaoui Dimitrios D. Alexakis Imen Hamdi Nasr Athanasios V. Argyriou Evangelos Alevizos Nikos Papadopoulos Mohamed Hédi Inoubli |
| author_sort | Wissal Issaoui |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T03:06:28Z |
| format | Article |
| id | doaj.art-4d3cd8380fe6449681a5a3e8410499c7 |
| institution | Directory Open Access Journal |
| issn | 2073-4395 |
| language | English |
| last_indexed | 2024-03-10T03:06:28Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Agronomy |
| spelling | doaj.art-4d3cd8380fe6449681a5a3e8410499c72023-11-23T12:38:06ZengMDPI AGAgronomy2073-43952021-12-011219010.3390/agronomy12010090Monitoring Olive Oil Mill Wastewater Disposal Sites Using Sentinel-2 and PlanetScope Satellite Images: Case Studies in Tunisia and GreeceWissal Issaoui0Dimitrios D. Alexakis1Imen Hamdi Nasr2Athanasios V. Argyriou3Evangelos Alevizos4Nikos Papadopoulos5Mohamed Hédi Inoubli6Department of Earth Sciences, Faculty of Sciences of Bizerte, Carthage University, Jarzouna, Bizerte 7021, TunisiaLaboratory of Geophysical-Satellite Remote Sensing and Archaeoenvironment, Institute for Mediterranean Studies, Foundation for Research and Technology-Hellas (FORTH), 74100 Rethymno, GreeceDepartment of Earth Sciences, Faculty of Sciences of Bizerte, Carthage University, Jarzouna, Bizerte 7021, TunisiaLaboratory of Geophysical-Satellite Remote Sensing and Archaeoenvironment, Institute for Mediterranean Studies, Foundation for Research and Technology-Hellas (FORTH), 74100 Rethymno, GreeceLaboratory of Geophysical-Satellite Remote Sensing and Archaeoenvironment, Institute for Mediterranean Studies, Foundation for Research and Technology-Hellas (FORTH), 74100 Rethymno, GreeceLaboratory of Geophysical-Satellite Remote Sensing and Archaeoenvironment, Institute for Mediterranean Studies, Foundation for Research and Technology-Hellas (FORTH), 74100 Rethymno, GreeceUR-GAMM, Faculty of Sciences of Tunis, University of El Manar, Tunis 2092, TunisiaMediterranean 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.https://www.mdpi.com/2073-4395/12/1/90olive mill wastewater (OMW)disposal sitesremote sensingspectral signatureindicesclassification |
| spellingShingle | Wissal Issaoui Dimitrios D. Alexakis Imen Hamdi Nasr Athanasios V. Argyriou Evangelos Alevizos Nikos Papadopoulos Mohamed Hédi Inoubli Monitoring Olive Oil Mill Wastewater Disposal Sites Using Sentinel-2 and PlanetScope Satellite Images: Case Studies in Tunisia and Greece Agronomy olive mill wastewater (OMW) disposal sites remote sensing spectral signature indices classification |
| title | Monitoring Olive Oil Mill Wastewater Disposal Sites Using Sentinel-2 and PlanetScope Satellite Images: Case Studies in Tunisia and Greece |
| title_full | Monitoring Olive Oil Mill Wastewater Disposal Sites Using Sentinel-2 and PlanetScope Satellite Images: Case Studies in Tunisia and Greece |
| title_fullStr | Monitoring Olive Oil Mill Wastewater Disposal Sites Using Sentinel-2 and PlanetScope Satellite Images: Case Studies in Tunisia and Greece |
| title_full_unstemmed | Monitoring Olive Oil Mill Wastewater Disposal Sites Using Sentinel-2 and PlanetScope Satellite Images: Case Studies in Tunisia and Greece |
| title_short | Monitoring Olive Oil Mill Wastewater Disposal Sites Using Sentinel-2 and PlanetScope Satellite Images: Case Studies in Tunisia and Greece |
| title_sort | monitoring olive oil mill wastewater disposal sites using sentinel 2 and planetscope satellite images case studies in tunisia and greece |
| topic | olive mill wastewater (OMW) disposal sites remote sensing spectral signature indices classification |
| url | https://www.mdpi.com/2073-4395/12/1/90 |
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