Discriminant analysis of olive oil mill wastes using spectroradiometers in the visible and near infrared part of the spectrum

Abstract

This paper aims to introduce an index which is able to assist the recognition of Olive Oil Mill Wastes (OOMW) disposal areas using multispectral satellite images. For this purpose several ground spectroradiometric measurements in the range of 450 -900 nm have been collected at a variety of targets. The samples were initially resampled to the GeoEye-1 sensor using the appropriate Relative Spectral Response Filter (RSR) and then scatter plots and spectral signatures were projected. Then an evaluation of nine widely used vegetation indices was performed. This analysis indicated that, Perpendicular Vegetation Index (PVI), Transformed Soil Adjusted Vegetation Index (TSAVI) and Soil and Atmospherically Resistant Vegetation Index (SARVI) are the most efficient indices to enhance the detection of Olive Mill Waste disposal areas. Moreover, correlation as well as separability analysis have shown than blue and near infrared (NIR) spectral bands are the most suitable for interpretation purposes. The Olive Mill Waste index was applied also to GeoEye-1 in different cases studies in the island of Crete.

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

“…The application of different image analysis algorithms indicated that PCA analysis can be effectively used for mapping OMW ponds. Furthermore, the SVM classification algorithm showed optimum performance in differentiating and identifying OMW sites from neighbor areas, as it was proved by Agapiou et al [16]. It is noteworthy to mention that, within our research, Composite 3 was used with images acquired during the winter period (February 2020).…”

“…In this concept, several studies have employed satellite images for monitoring environmental parameters, especially water bodies, that are affected mainly by severe anthropogenic activities [14,15]. In the recent past, satellite remote sensing integrated with a compilation of in situ spectral signature libraries have been also utilized to identify and monitor OMW disposal sites [4,16].…”

Detection of olive oil mill waste (OOMW) disposal areas using high resolution GeoEye’s OrbView-3 and Google Earth images

“…Ground spectroradiometers and geophysical surveys can be also used for monitoring OOMW areas. Such ground technologies may be used so as to further optimize the system and the GIS procedures [15,31] and to examine underground pollution. The system will be able to record in a 4D space (X,Y,Z and time) the OOMW areas for the island of Crete.…”

“…In the literature, only a limited number of publications exist related to this topic [14][15][16]. This relative low number of publications should be linked to the local problem of OOMW disposal areas in the Mediterranean countries.…”

“…In contrast, the same study indicated that free distributed medium resolution Landsat 8 OLI images can be problematic for the detection of OOMW areas since they provide controversial results. Spectral regions and OOMW index suitable to enhance such sites have been also recently proposed [15], where it was found that spectral bands in the blue and VNIR part of the spectrum are the most appropriate for detection of OOMW using multispectral satellite datasets. The index and other image analysis techniques were applied also in very high resolution satellite data [16].…”