Application of ASTER remote sensing data to geological mapping of basement domains in arid regions: a case study from the Central Anti-Atlas, Iguerda inlier, Morocco

Janati, M’hamed El; Soulaı̈mani, Abderrahmane; Admou, Hassan; Youbi, Nasrrddine; Hafid, Ahmid; Hefferan, Kevin

doi:10.1007/s12517-013-0945-y

Cited by 41 publications

(16 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…M. Khaleghi [18] used SID, SAM and principal component analysis (PCA) change detection technique to enhance the alteration of the Sarduiyeh area of Kerman province of Iran. M. Janati [19] used the fusion of SID, SAM and Advanced Spaceborne Thermal Emission and Reflection * Corresponding author Radiometer (ASTER) data for the geographical mapping of the basement domain in Arid Regions. H.Jiao [20] used a combination of the SID and SAM supervised classification techniques to develop a novel algorithm for the computer-based spectral encoding.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Supervised Classification Techniques With Alos Palsar Sensor for Roorkee Region of Uttarakhand, India

Shakya¹,

Ramola²,

Kandwal³

et al. 2018

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

<p><strong>Abstract.</strong> The Advanced Land Observing Satellite (ALOS) is developed by the Japanese Aerospace Exploration Agency (JAXA) which was launched in the year 2006 for the Earth observation and exploration purpose. The ALOS was carrying PRISM, AVNIR-2 and PALSAR sensors for this purpose. PALSAR is L-Band synthetic aperture radar (SAR). The PALSAR sensor is designed in a way that it can work in all weather conditions with a resolution of 10 meters. In this research work we have made an investigation on the accuracy obtained from the various supervised classification techniques. We have compared the accuracy obtained by classifying the ALOS PALSAR data of the Roorkee region of Uttarakhand, India. The training ROI’S (Region of Interest) are created manually with the assistance of ArcGIS Earth and for the testing purpose, we have used the Global positioning system (GPS) coordinates of the region. Supervised classification techniques included in this comparison are Parallelepiped classification (PC), Minimum distance classification (MDC), Mahalanobis distance classification (MaDC), Maximum likelihood classification (MLC), Spectral angle mapper (SAM), Spectral information divergence (SID) and Support vector machine (SVM). Later, through the post classification confusion matrix accuracy assessment test is performed and the corresponding value of the kappa coefficient is obtained. In the result, we have concluded MDC as best in term of overall accuracy with 82.3634% and MLC with a kappa value of 0.7591. Finally, a peculiar relationship is developed in between classification accuracy and kappa coefficient.</p>

show abstract

Section: Introductionmentioning

confidence: 99%

Comparison of Supervised Classification Techniques With Alos Palsar Sensor for Roorkee Region of Uttarakhand, India

Shakya¹,

Ramola²,

Kandwal³

et al. 2018

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

show abstract

“…The siltations are studied for spectral absorption characters and mapped using parallelepiped method 60,61 . In www.nature.com/scientificreports www.nature.com/scientificreports/ addition, an accuracy assessment for the distribution of siltation and associated formations of the study area is carried out by confusion matrix using the Maximum Likelihood (ML), and newest algorithms namely Spectral Angle Mapper (SAM) and Spectral Information Divergence (SID) to understand the ability among the methods [62][63][64][65][66][67] . All the processed images are interpreted and discussed and the results are verified in the field study and confirmed through laboratory analyses.…”

Section: Methodsmentioning

confidence: 99%

Mapping and accuracy assessment of siltation of recharge dams using remote sensing technique

Rajendran

Nasir

Jabri

2020

Sci Rep

View full text Add to dashboard Cite

this study demonstrates the use of ASteR data to map the siltation of the Al-Khod Dam constructed at the lower reaches of Samail catchment area, north Muscat, Sultanate of oman. in this study, the decorrelated image of spectral bands 6, 3, and 1 clearly discriminated the distribution of siltation. The occurrence of siltation is confirmed by the detection of minerals using the VNIR-SWIR bands by the Spectral Angle Mapper (SAM) method. in addition, the siltation of the dam is studied for the years 1987 to 2018 using Landsat satellite images. Interpretation of images showed a gradual increase of the siltation. Mapping accuracy for the occurrence of siltation is assessed by a confusion matrix which produced an overall accuracy of 97.88% and Kappa coefficient of 0.98 in the Maximum Likelihood method. Results of image analyses are verified in the field and confirmed through laboratory analyses. The study of spectral absorption characters of field samples using a Portable Infrared Mineral Analyzer (piMA) showed the presence of oH molecule bearing minerals (clays, serpentines, etc.) and carbonate minerals (calcite and dolomite) in the silt deposits. The occurrence of these minerals is confirmed further by X-ray diffraction (XRD) and Scanning Electron Microscope (SEM) analyses. Groundwater recharge in dams to increase the yield of groundwater for sustainability is very important in arid regions 1. Heavy rainfall and occurrence of flash floods in the regions may deposit large amounts of silts in the dams 2-7. The siltation is a major issue, hindering the infiltration of surface water into groundwater. Increase of such deposits reduce or stop groundwater recharge, decline groundwater levels, and well yields, and deteriorate water quality in and around the dam yearly 5,8. Researchers described the groundwater mounds beneath recharge sites 9-11 and infiltration during erratic floods in karstic basins 12-14. An in-depth study of alluvial stratigraphy provides detail about the number of timing, events, and deposited volumes of floods 15,16. A large number of check dams in the Mediterranean ephemeral streams have been built to prevent sediment inputs 17. Sedimentation rates are studied by infill stratigraphy of check dam and a model is proposed to evaluate erosion and sediment yield processes 18,19. However, meager attempts were made to study the siltations of the dams in Oman. Here the sedimentation in dams is influenced by numerous factors and the dams must be regularly cleaned and dried to continue the rates infiltration and storage capacities 4. In the Sultanate of Oman, many recharge dams across wadis were constructed by the government to hold up runoff and recharge the aquifers. But, most of the dams are silted now due to wadi flow after flash floods in catchments. A suitable technique to map and assess the silt deposits and sedimentation, an alternative to expensive and time-consuming methods 20,21 , is essential and urgently needed by scientists and engineers to remove or protect the deposits of the recharge dams. In thi...

show abstract

“…Each pixel is assigned to the class that has the highest probability. If the highest probability is smaller than a specified threshold, the pixel remains unclassified [40,41]. SAM determines the spectral similarity between the spectra of each pixel and reference spectral end-members by calculating the angle between the vectors in a space with dimensionality equal to the number of bands [42,43].…”

Section: Image Elaboration Methodologiesmentioning

confidence: 99%

Spectral Signature Characterization and Remote Mapping of Oman Exotic Limestones for Industrial Rock Resource Assessment

et al. 2018

View full text Add to dashboard Cite

This study demonstrates the capability of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor data to remotely map industrial carbonate rocks known as the 'Oman exotics' of the Sultanate of Oman. We measured reflectance spectra of marble using a PIMA™ spectrometer and studied their spectral absorptions distinguishing calcite from spectral absorptions of dolomite of the same region. The spectral band 8 of ASTER is processed by simple decorrelation stretch image processing method to map the exotic limestone rock of the Nakhl region, Oman. Results showed that carbonate rocks displayed distinctive tonal variation on the image. A comparative study with the spectral band 7 of Landsat 7 (ETM+) does not discriminate the calcite-bearing marbles and associated carbonate formations in the studied area. ASTER data were also processed by the application of the Maximum Likelihood Classification (MLC), Spectral Angle Mapper (SAM) and Spectral Information Divergence (SID) image classification algorithms. The results were assessed by the production of a confusion matrix. The study shows the capability of visible near infrared (VNIR) and shortwave infrared (SWIR) spectral bands of the ASTER sensor and potential of the image processing methods to remotely identify industrial carbonate rocks and we recommend this technique to similar regions of the world.

show abstract

Application of ASTER remote sensing data to geological mapping of basement domains in arid regions: a case study from the Central Anti-Atlas, Iguerda inlier, Morocco

Cited by 41 publications

References 50 publications

Comparison of Supervised Classification Techniques With Alos Palsar Sensor for Roorkee Region of Uttarakhand, India

Comparison of Supervised Classification Techniques With Alos Palsar Sensor for Roorkee Region of Uttarakhand, India

Mapping and accuracy assessment of siltation of recharge dams using remote sensing technique

Spectral Signature Characterization and Remote Mapping of Oman Exotic Limestones for Industrial Rock Resource Assessment

Contact Info

Product

Resources

About