scispace - formally typeset
Search or ask a question
Author

Amine Jellouli

Bio: Amine Jellouli is an academic researcher. The author has contributed to research in topics: Advanced Spaceborne Thermal Emission and Reflection Radiometer & Geology. The author has an hindex of 5, co-authored 10 publications receiving 146 citations.

Papers
More filters
Journal ArticleDOI
TL;DR: In this article, the authors compared the performance of ASTER, Landsat-8 and Sentinel 1 data sensors in automatic lineament extraction using a fully automatic approach consisting of a combination of edge detection algorithm and line-linking algorithm.

114 citations

Journal ArticleDOI
TL;DR: In this article, the authors exploited the multispectral Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Landsat 8 Operational Land Imager (OLI) data in order to map lithological units in the Bas Drâa inlier, at the Moroccan Anti Atlas.
Abstract: Lithological mapping is a fundamental step in various mineral prospecting studies because it forms the basis of the interpretation and validation of retrieved results. Therefore, this study exploited the multispectral Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Landsat 8 Operational Land Imager (OLI) data in order to map lithological units in the Bas Drâa inlier, at the Moroccan Anti Atlas. This task was completed by using principal component analysis (PCA), band ratios (BR), and support vector machine (SVM) classification. Overall accuracy and the kappa coefficient of SVM based on ground truth in addition to the results of PCA and BR show an excellent correlation with the existing geological map of the study area. Consequently, the methodology proposed demonstrates a high potential of ASTER and Landsat 8 OLI data in lithological units discrimination.

59 citations

Journal ArticleDOI
TL;DR: In this article, the authors provide a comprehensive review of the use of the Landsat-8 and Sentinel-2 multispectral sensors in mineral exploration and conclude that Landsat8 is by far the more popular sensor in mining applications.

41 citations

Journal ArticleDOI
TL;DR: The massif of Saghro in Moroccan Anti-Atlas is known for several important economic deposits, including the Bouskour mine as mentioned in this paper, which has high potential in terms of production.
Abstract: The massif of Saghro in Moroccan Anti-Atlas is known for several important economic deposits. Thanks to its high potential in terms of production, the deposit of Bouskour is considered among the mo...

12 citations

Journal ArticleDOI
TL;DR: In this paper, the Line of PCI Geomatica software was applied on PC1 OLI, PC3 ASTER and HH and HV polarization images to automatically extract geological lineaments.

12 citations


Cited by
More filters
Journal ArticleDOI
TL;DR: In this article, the authors compared the performance of ASTER, Landsat-8 and Sentinel 1 data sensors in automatic lineament extraction using a fully automatic approach consisting of a combination of edge detection algorithm and line-linking algorithm.

114 citations

Journal ArticleDOI
TL;DR: In this paper, the authors identified and located the groundwater potential zones of Megech watershed using geographic information system (GIS) and remote sensing data and validated the results with an independent set of groundwater inventory data to validate the results.

79 citations

Journal ArticleDOI
TL;DR: Analysis of the host structures assessed by the remote sensing results denotes vein formation spanning the time–space from early transpression to late orogen collapse during the protracted tectonic evolution of the belt.
Abstract: Multi-sensor satellite imagery data promote fast, cost-efficient regional geological mapping that constantly forms a criterion for successful gold exploration programs in harsh and inaccessible regions. The Barramiya–Mueilha sector in the Central Eastern Desert of Egypt contains several occurrences of shear/fault-associated gold-bearing quartz veins with consistently simple mineralogy and narrow hydrothermal alteration haloes. Gold-quartz veins and zones of carbonate alteration and listvenitization are widespread along the ENE–WSW Barramiya–Um Salatit and Dungash–Mueilha shear belts. These belts are characterized by heterogeneous shear fabrics and asymmetrical or overturned folds. Sentinel-1, Phased Array type L-band Synthetic Aperture Radar (PALSAR), Advanced Space borne Thermal Emission and Reflection Radiometer (ASTER), and Sentinel-2 are used herein to explicate the regional structural control of gold mineralization in the Barramiya–Mueilha sector. Feature-oriented Principal Components Selection (FPCS) applied to polarized backscatter ratio images of Sentinel-1 and PALSAR datasets show appreciable capability in tracing along the strike of regional structures and identification of potential dilation loci. The principal component analysis (PCA), band combination and band ratioing techniques are applied to the multispectral ASTER and Sentinel-2 datasets for lithological and hydrothermal alteration mapping. Ophiolites, island arc rocks, and Fe-oxides/hydroxides (ferrugination) and carbonate alteration zones are discriminated by using the PCA technique. Results of the band ratioing technique showed gossan, carbonate, and hydroxyl mineral assemblages in ductile shear zones, whereas irregular ferrugination zones are locally identified in the brittle shear zones. Gold occurrences are confined to major zones of fold superimposition and transpression along flexural planes in the foliated ophiolite-island arc belts. In the granitoid-gabbroid terranes, gold-quartz veins are rather controlled by fault and brittle shear zones. The uneven distribution of gold occurrences coupled with the variable recrystallization of the auriferous quartz veins suggests multistage gold mineralization in the area. Analysis of the host structures assessed by the remote sensing results denotes vein formation spanning the time–space from early transpression to late orogen collapse during the protracted tectonic evolution of the belt.

58 citations

Journal ArticleDOI
TL;DR: The objective of this work was to obtain a normalized different vegetation index (NDVI) cloudless product (NDVInc) by modeling Sentinel 2 NDVI using different regression techniques and the Sentinel 1 radar backscatter as input, observing that the data derived from Sentinel 1 allowed it to model, with great reliability, the NDVI of agricultural crops throughout the phenological cycle.
Abstract: Monitoring agricultural crops is necessary for decision-making in the field. However, it is known that in some regions and periods, cloud cover makes this activity difficult to carry out in a systematic way throughout the phenological cycle of crops. This circumstance opens up opportunities for techniques involving radar sensors, resulting in images that are free of cloud effects. In this context, the objective of this work was to obtain a normalized different vegetation index (NDVI) cloudless product (NDVInc) by modeling Sentinel 2 NDVI using different regression techniques and the Sentinel 1 radar backscatter as input. To do this, we used four pairs of Sentinel 2 and Sentinel 1 images on coincident days, aiming to achieve the greatest range of NDVI values for agricultural crops (soybean and maize). These coincident pairs were the only ones in which the percentage of clouds was not equal to 100% for 33 central pivot areas in western Bahia, Brazil. The dataset used for NDVInc modeling was divided into two subsets: training and validation. The training and validation datasets were from the period from 24 June 2017 to 19 July 2018 (four pairs of images). The best performing model was used in a temporal analysis from 02 October 2017 to 08 August 2018, totaling 55 Sentinel 2 images and 25 Sentinel 1 images. The selection of the best regression algorithm was based on two validation methodologies: K-fold cross-validation (k = 10) and holdout. We tested four modeling approaches with eight regression algorithms. The random forest was the algorithm that presented the best statistical metrics, regardless of the validation methodology and the approach used. Therefore, this model was applied to a time series of Sentinel 1 images in order to demonstrate the robustness and applicability of the model created. We observed that the data derived from Sentinel 1 allowed us to model, with great reliability, the NDVI of agricultural crops throughout the phenological cycle, making the methodology developed in this work a relevant solution for the monitoring of various regions, regardless of cloud cover.

58 citations

Journal ArticleDOI
TL;DR: The remote sensing techniques have become a guiding and promising tool for mineral exploration and mapping of lithological units as mentioned in this paper, and they have been used extensively in the field of mineral exploration.
Abstract: The remote sensing (RS) techniques have become a guiding and promising tool for mineral exploration and mapping of lithological units. The RS for mineral exploration begins with Landsat multispectr...

55 citations