An integrated approach to hydro-geological lineament mapping of a semi-arid region of West Africa using Radarsat-1 and GIS

Corgne, Samuel; Magagi, Ramata; Yergeau, Michel; Sylla, Daouda

doi:10.1016/j.rse.2010.03.004

Cited by 77 publications

(30 citation statements)

References 31 publications

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“…Generally we consider that small angles are more sensitive to ground surfaces [32,33] and higher/medium angles are more sensitive to vegetation roughness [34].…”

Section: Satellite Datamentioning

confidence: 99%

Detection and Characterization of Hedgerows Using TerraSAR-X Imagery

et al. 2014

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Whilst most hedgerow functions depend upon hedgerow structure and hedgerow network patterns, in many ecological studies information on the fragmentation of hedgerows network and canopy structure is often retrieved in the field in small areas using accurate ground surveys and estimated over landscapes in a semi-quantitative manner. This paper explores the use of radar SAR imagery to (i) detect hedgerow networks; and (ii) describe the hedgerow canopy heterogeneity using TerraSAR-X imagery. The extraction of hedgerow networks was achieved using an object-oriented method using two polarimetric parameters: the Single Bounce and the Shannon Entropy derived from one TerraSAR-X image. The hedgerow canopy heterogeneity estimated from field measurements was compared with two backscattering coefficients and three polarimetric parameters derived from the same image. The results show that the hedgerow network and its fragmentation can be identified with a very good accuracy (Kappa index: 0.92). This study also reveals the high correlation between one polarimetric parameter, the Shannon entropy, and the canopy fragmentation measured in the field. Therefore, VHSR radar images can OPEN ACCESSRemote Sens. 2014, 6 3753 both precisely detect the presence of wooded hedgerow networks and characterize their structure, which cannot be achieved with optical images.

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“…Generally we consider that small angles are more sensitive to ground surfaces [32,33] and higher/medium angles are more sensitive to vegetation roughness [34].…”

Section: Satellite Datamentioning

confidence: 99%

Detection and Characterization of Hedgerows Using TerraSAR-X Imagery

et al. 2014

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“…It is available free on the website of the European Space Agency ESA (https://scihub.esa.int/dhus/).The different processing and filtering of the Sentinel-1A radar image were performed using SNAP ESA Sentinel-1 toolbox (S1TBX). A set of processing and filtering operations were applied to the Sentinel-1 radar image (Fig.6) to reduce uncertainty of the data, mainly due to atmospheric disturbances, as well as the topographic effects of the target [64] and improve the possibility of the lineaments extraction [65,66,67].…”

Section: Sentinel-1a Processing and Analysismentioning

confidence: 99%

Contribution of gravity data and Sentinel-1 image for structural mapping. Case of Beni Mellal Atlas and Beni Moussa plain (Morocco).

et al. 2018

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Abstract. The present work is a combined study of gravity and Sentine-1 data for fracture mapping in the karstic massif of Beni Mellal Atlas and the adjacent plain of Beni Moussa. In order to locate the various faults that contribute to the study area structuring, the gravimetric contacts analysis method, based on the joint use of the horizontal gradient and the upward continuation at different altitudes, has been applied to the gravity data. To optimize the structural mapping in the study area, the gravimetric lineaments obtained were completed and correlated with the lineaments got from Sentinel-1 image. Four faults families of NE-SW; E-O; N-S and NW-SE directions have been highlighted. There fault families are perfectly combined with the studied area's surface water network, moreover, they corroborate with the previous geological and structural studies.

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“…It is available on the official website of European Space Agency ESA. The raw radar image has undergone preliminary processing that consists of radiometric, atmospheric and geometric correction to mitigate the atmospheric effects and topographic disturbances affecting the recorded information quality (Corgne et al, 2010). Thereafter, a "refined Lee" filter has been applied to the radar image to eliminate the flicker effect (speckle reduction) (Lee et al, 1999).…”

Section: Remote Sensing Data Processingmentioning

confidence: 99%

“…Numerous studies have been carried out using radar remote sensing tools in structural mapping (Mansour and Ait Brahim, 2005;Corgne et al, 2010). In Morocco, Adiri et al (2017) have made a comparison between remote sensing data multi-sources (optical and radar remote sensing) for automatic lineaments extraction in the region of Sidi Flah-Bouskour inlier, Anti-Atlas Morocco.…”

Section: Introductionmentioning

confidence: 99%

Geological Structures Mapping Using Aeromagnetic Prospecting and Remote Sensing Data in the Karstic Massif of Beni Mellal Atlas, Morocco.

Boutirame

Boukdir

Akhssas

et al. 2018

Bulletin of the Mineral Research and Exploration

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The current study exposes the results of aeromagnetic data interpretation and a combined analysis of 1-A sentinel radar image that cover the study area of Beni Mellal Atlas in order to describe the structural geometry and to understand its tectonic evolution.The map of the reduced to pole of residual magnetic field highlights various magnetic anomalies with high amplitudes that correspond to Jurassic-Cretaceous basaltic formations outcropping synclinal basins of Beni Mellal Atlas. The interpretation of magnetic data using tilt derivative (TDR), horizontal gradient technique coupled to upward continuation and Euler Deconvolution allows us to distinguish the fractures network that is affecting the study area. In order to complete this analysis, the Sentinel-A radar image is processed and filtered using SNAP ESA Sentinel-1 toolbox software to extract lineaments. The final structural map reveals four faults groups oriented respectively NE-SW, ENE-WSW to E-W, N-S and NW-SE Their depths estimated by the application of Euler deconvolution exceed 1500 m.Thoses faults have played a major role in structural evolution of Beni Mellal Atlas.

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An integrated approach to hydro-geological lineament mapping of a semi-arid region of West Africa using Radarsat-1 and GIS

Cited by 77 publications

References 31 publications

Detection and Characterization of Hedgerows Using TerraSAR-X Imagery

Detection and Characterization of Hedgerows Using TerraSAR-X Imagery

Contribution of gravity data and Sentinel-1 image for structural mapping. Case of Beni Mellal Atlas and Beni Moussa plain (Morocco).

Geological Structures Mapping Using Aeromagnetic Prospecting and Remote Sensing Data in the Karstic Massif of Beni Mellal Atlas, Morocco.

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