The use of remote sensing, in this research, can be summarized in mapping and statistical studies of lineaments on the satellites images of the Jurassic outcrops in the Imilchil-Tounfite area, Central High Atlas of Morocco. This is to apply various manual techniques for extracting lineaments from Landsat TM image. Analytical techniques used in this work are: the principal component analysis (PCA) applied to selective bands of the visible and infrared, which allows creating new images with better visual interpretation. Directional filters N0°, N45°, N90°, and N135° with a 5×5 matrix were used to enhance lineaments in the corresponding perpendicular directions, and therefore to obtain a good discrimination of those structures. Preliminary results highlight a dominant geological fracturing trending ENE/WSW with 52% of the total lineaments, a second fracture trending is WNW/ESE at 23%, a third fracture series trending NE/SW with 20% and finally, a minor series of fractures trending NW/SE with 5% of the total lineaments. Distribution and statistical relationship, between fractures and the affected surface on the one hand and the fracture length on the other hand, shows a network of well-structured fractures. The final lineament map constitutes a contribution to complete the geology and assisting the mining and hydrogeological prospection, in the Imilchil-Tounfite area.
En este trabajo se han aplicado metódos estadísticos de datos obtenidos por teledetección, para la cartografía de lineamientos en afloramientos del Jurásico en la zona de Imilchil-Tounfite, Alto Atlas Central de Marruecos. Las técnicas analíticas utilizadas incluyen el análisis de componentes principales (PCA) aplicado a las bandas visible y infrarrojos, que permite crear nuevas imágenes con una mejor interpretación visual, y filtros direccionales N0°, N45°, N90° y N135° con una matriz de 5×5 para mejorar rasgos en las direcciones perpendiculares correspondientes y obtener una buena discriminación de esas estructuras.
Los resultados preliminares ponen de manifiesto una fractura geológica dominante de tendencia ENE-SW con un 52% del total de lineamientos, una segunda tendencia ONO-S (23%), una tercera serie de fracturas orientada NE-SW (20%) y, por último, una serie de menor importancia de fracturas tendencia NW-SE (5%). Las relaciones estadísticas entre las fracturas y la superficie afectada por un lado y la longitud de la fractura, por otra parte, muestra una red de fracturación bien estructurada. El mapa final de lineamientos constituye una contribución para completar la geología de la zona y como ayuda a las prospecciones mineras e hidrogeológicas en la zona de Imilchil-Tounfite.
The use of satellite imagery in the Imilchil-Tounfite area Central High Atlas is relatively recent. All the anterior research done in this area is a structural, sedimentary and petrography geology (Frizon de Lamotte et al.
The Imilchil-Tounfite area is located in the Central High Atlas of Morocco, between 5° and 6°W longitude and between 32° and 32° 30’N latitude (
Geological and location map of the Imilchil-Tounfite area.
The main material used in this study is the Landsat TM (Thematic Mapper) satellite image of L5201038_03820091111 scene, acquired on 12-31th-2009 (path 201; row 38) Free Download from
Satellite image TM Landsat of the Imilchil-Tounfite area; A: false color composite in RGB (R = 2, G = 4, B = 6); B: false color composite in RGB of the components principal analysis bands (R = PCA1, G = PCA2, B = PCA3).
The more conventional and most used methods in many studies for the lineaments extraction are the principal component analysis (PCA) as well as the enhancement by spatial filtering. (Amri
Principal components analysis or Hotelling transform is an image enhancement technique, based on a mathematical transformation, which reduces the dimensionality of data and segregates noise components (Singh & Harrison
Correlation matrix of Landsat TM bands image
Bands | 1 | 2 | 3 | 4 | 5 | 6 | 7 | Moyen | Ecart |
---|---|---|---|---|---|---|---|---|---|
1 | 1.00 | 0.93 | 0.96 | 0.79 | 0.80 | 0.71 | 0.83 | 40.06 | 30.77 |
2 | 0.93 | 1.00 | 0.98 | 0.88 | 0.92 | 0.72 | 0.94 | 29.62 | 25.41 |
3 | 0.96 | 0.98 | 1.00 | 0.86 | 0.88 | 0.72 | 0.90 | 22.32 | 18.02 |
4 | 0.79 | 0.88 | 0.86 | 1.00 | 0.93 | 0.71 | 0.90 | 33.24 | 27.56 |
5 | 0.80 | 0.92 | 0.88 | 0.93 | 1.00 | 0.67 | 0.98 | 58.80 | 51.39 |
6 | 0.71 | 0.72 | 0.72 | 0.71 | 0.67 | 1.00 | 0.68 | 85.95 | 64.74 |
7 | 0.83 | 0.94 | 0.90 | 0.90 | 0.98 | 0.68 | 1.00 | 34.98 | 30.83 |
In order to enhance fractures and faults on the image, directional filters are used for lineaments extracting. Different sizes of matrix filters are applied (3×3; 5×5 and 7×7). The obtained results indicate that those of 5×5 filter size was giving the best and really lineaments which most closely resembles the geological structures in the field. At the end, directional filters (5×5) at 0°N, 45°N, 90°N and 135°N were applied (on a new false color composed image from CPA bands as : PCA123 and PCA457) in this work. The 5×5 filter used in this processing image is an edge detection filter. The 5×5 weights of the directional filter for the direction 90°N is given in the
Matrix of weighting coefficients of the 5×5 directional filter for N90
−1 | −1 | −1 | −1 | −1 |
−1 | −1 | −1 | −1 | −1 |
0 | 0 | 0 | 0 | 0 |
1 | 1 | 1 | 1 | 1 |
1 | 1 | 1 | 1 | 1 |
The application of directional filter with 5×5 matrix size on the first bands of PCA123 and PCA457, which were used as input images, allows highlighting the lineaments in the study area. These filters provide images in grayscale, where the lineaments based on the selected direction appear brighter than other entities. The maps of discontinuities images were realized by manual extraction (
A: CPA1 of visible TM Landsat image; B: resulted image after NE directional filter treatment applied on CPA1.
A: Enlarged extract from NE directional filter image (see Fig. 3 B for location). B: interpreted fractures on the fig. 4 A image.
When applying the directional filter, directional gradients enhance all discontinuities images corresponding to any lithological discontinuity (contact between different lithological units) and/or structural discontinuity (fault, fracture and joint). In order to give significance to the structural lineaments extracted by remote sensing, the map of discontinuities images is confronted with auxiliary data (geological map, topographic map and field’s observations) in order to remove lithological discontinuities, the ridge and crest lines and the anthropogenic lineaments (bitumen road, railway…). The resulted map at the end of all those operations shows a maximum of the fracture and structural lineaments in the study area (
A: Fracture map of Imilchil-Tounfite area extracted from Landsat TM image in this work; B: fault map of the Imilchil-Tounfite area extracted from existing geological map. C: Directional rose of mapped faults in the existing geological map D: Directional rose of extracted lineaments by remote sensing methods in this work.
Some Fault field pictures corresponding to the lineaments detect by remote sensing. A: Fault NW-SE in the south of Ait Ali ou Ikkou ridge; B: Fault NS to NW-SE in the Bathonian red bed; C: Fault NW-SE in the north of Tassent ridge in the Upper Toarcian marls; D: Normal fault trough the Bajocian limestones in the south east of the Imilchil village (See Fig. 5 for location).
The fractures mapped by conventional methods on the geological map have been reproduced and analyzed (
Geostatistics is used for estimation and prediction of a spatially continuous phenomenon, using data obtained at a limited number of spatial locations (Diggle & Ribeiro,
The aim of geostatistical study, in this work, fits into a general problematic of characterization, interpretation and valuation of structural lineaments. We used this technic to characterize the spatial dispersion of trend and lengths of fractures in the Imilchil-Tounfite area, central high Atlas of Morocco.
The variograms of fractures distribution in Imilchil-Tounfite region were calculated from cumulative lengths by units of 200 km2 for each directional series of fractures and the regionalization parameters are determined using spherical and exponential theoretical models. A first analysis of different variograms shows that the fractures, of Imilchil-Tounfite area, are not randomly distributed in space, but have a degree of spatial correlation known as “structure”. This structure has range of influence up to 65 km (
Resulting graph from lineament geostatistical study on the Imilchil-Toufite area; A: Variogram fractures all azimuths adjusted by a Spherical model B: Variogram WNW/ESE trends lineaments adjusted by an exponential model. C: Variogram ENE/WSW trends lineaments adjusted by spherical model.
After extraction of the Imilchil-Tounfite fractures on satellite images, the resulting network is described by 10 properties (known as variables). Only implementation of the PCA statistical method will bring out the organization of the network in space. The variables used in PCA study are: 1) the latitude of the fractures and 2) longitude of fractures (Lambert coordinates X and Y positioning in space); 3) the ENE / WSW trend; 4) the WNW / ESE; 5) the NE / SW; 6) NW / SE; 7) the length of ENE / WSW fractures; 8) the length of WNW / ESE fractures; 9) the length of fractures trending NE / SW and 10) the length of fractures trending NW / SE.
The result of the lineaments network study, by the PCA, allowed to calculate 10 principal components with a great percentage of the variance estimated at 56,319 within the three first principal components (CPA1=21,39; CPA2=19,29; CPA3=15,63) (
Eigen values of the principal component analysis of the lineaments network in the Imilchil-Tounfite area
Component | Initial Eigen values | ||
---|---|---|---|
Sum | % variance | % cumulative | |
1 | 2,140 | 21,397 | |
2 | 1,929 | 19,290 | |
3 | 1,563 | 15,632 | 56,319 |
4 | 1,297 | 12,969 | 69,297 |
5 | 0,997 | 9,965 | 79,252 |
6 | 0,866 | 8,657 | 87,909 |
7 | 0,389 | 3,891 | 91,800 |
8 | 0,298 | 2,978 | 94,778 |
9 | 0,270 | 2,704 | 97,483 |
10 | 0,252 | 2,517 | 100,00 |
This study also allowed to extract the sum of the square of the selected factors in tow first components (CPA1=21,397 and CPA2=40.627) (
Extraction sum of the square of the selected factors of the lineaments network in the Imilchil-Tounfite area
Component | Eigenvalues % cumulative | extraction sum of the square of the selected factors | ||
---|---|---|---|---|
Sum | % variance | % cumulative | ||
1 | 21,397 | 2,140 | 21,397 | 21,397 |
2 | 40,687 | 1,929 | 19,290 | 40,627 |
Sum of the square of the selected factors for rotation of the lineaments network in the Imilchil-Tounfite area
Component | sum of the square of the selected factors for rotation | ||
---|---|---|---|
% cumulative | % variance | % cumulative | |
1 | 2,100 | 20,999 | 20,999 |
2 | 1,969 | 19,688 | 40,687 |
The statistical principal component analysis study improves information about the spatial relationships between different lineaments groups trend. According to the
Diagram of the principal components distribution of the Imilchil-Tounfite fractures in space after rotation; A: with cumulated length (LCD) depending on the direction of fractures (D1, D2, D3 and D4) B: Cumulated lengths (LCD) and percent (PD) and fractures number (ND of each directions ((D1, D2, D3 and D4). With D1=ENE-WSW; D2=WNW-ESE; D3=NE-SW and D4=NW-SE.
Analysis of the lineaments length shows a variation from 500 m to 12 km. The lengths of 374 lineaments mapped by Landsat remote sensing are distributed in 21 classes in steps of 500 m (
Histogram showing the frequency by length of the Imiclhil-Tounfite fractures extracted by remote sensing.
The digital processing of Landsat TM satellite image and the Geographic Information System (GIS) were used to create a fracture map of the Imilchil-Toufinte Area in the central High Atlas of Morocco. The statistical analysis of faults network, frequency diagram shows clearly that all trends are organized into four main groups (
The principal component analysis study revealed that the four trend groups of fractures have particular space distribution. Thus the two groups trending ENE/WSW and WNW/ESE cannot coexisting in space of 200 Km square. The two other groups trending NW/SE and NE/SW, are coexisting in the field. This spatial relationship is also visible on the geological map (
The fracture length analysis shows three main groups, the first one is between 0.5 and 4 km (75.66%), the second is between 5 and 7 km (22.19%), and finally a third group is with length greater than 7 km (2.15%). The lineaments lengths distribution corresponds perfectly to the geological map of the study area (
The geostatistical study shows that the fracture system plotted from satellite imagery is not randomly distributed in the area, but it has a structured occurrence. The fractures have a degree of spatial correlation known as “structure” with ranges of influence up to 65 km. That is to say that when the separation distance between the fractures is upper to 65 km, fracture length well be independent.
In order to compare our results with geological field data, it is necessary to present a brief structural description of the Moroccan Atlas Mountain followed by a discussion. The installation of the Moroccan Atlas basin is controlled by the remobilization faults inherited from the Hercynian orogeny. Jacobshagen (
Those faults are reactivated during the opening stage of the Atlasic basin from upper Permian to Triassic age; this event is related to the opening of the central Atlantic Ocean in one side and the new Tethys in the other side. The tectonic inversion of the Moroccan Atlas Mountain is related to the Africa-Eurasia convergence, the uprising stage of the Atlas is characterized by a structural context controlled by multiple relay on left lateral fault trending EW and NE-SW since the Bathonian age (Laville & Fedan,
In The other hand, the opening of the Atlasic basin by favoring an oblique extension on a major transfer fault trending N120 to WNW-ESE since Triassic-Jurassic age (El Kochri & Chorowics
If we compare the direction lineaments to the faults described in the Atlas, the main directions of lineaments ENE-WSW and WNW-ESE are the most dominant; they could correspond to the major directions described in the paragraph above. They correspond to the direction of the anticline ridges as sinistral fault and probably inherited from the Hercynian basement.
The lineaments of NE-SW direction, with 20% of all the lineaments is an important direction, it would correspond to the anticlinal ridges trending NE-SW (
Concerning the age of the fractures, the first three principal directions NE-SW, ENE-WSW and WNW-ESE, have been described in the literature as faults that controlled the sedimentation during the Trias and Lower Lias age (Bouchouata
The use of remote sensing on the visible and infrared bands of Landsat TM image added to the geographic information system (GIS) have contributed widely to create the fractures map with a fairly high number of fractures compared to the existing geological and structural maps. Firstly, the digital processing of satellite images has given a significant contribution to complete structural map of the Imilchil-Tounfite area. It can be use as a guide for future filed company in this area.On the other hand, statistical and geostatistical studies of the Imilchil-Tounfite area fractures, allows explaining how the fault network is structured in this region. The new fault network, mapped by remote sensing, will help us to understand the regional hydrological system (Chuma
Control and mapping fractures in the study area can be used also in mining and hydrogeological exploration in the Imilchil-Tounfite region. This final cartographic document is a good starting point for any work of rural engineering. It will serve in a project study for the establishment of structures engineering such as road, railway or inland waterways (bridges, tunnels), dam or any other project and construction necessitating recognition characteristic soil and subsurface.
The authors would like to thank the anonymous reviewers for their comments and suggestions that improved the final manuscript of this work. They also like to thank the executive editor Jose-Maria Cebria for all communication efforts and the work for the publication of this paper.
“The Authors would like also to thank the Geosciences and Environment laboratory, the Department of Geology in the Faculty of Sciences and Techniques of Marrakesh, for supportin this work”.