scholarly journals Automatic Lineaments Extraction using the Line Algorithm in the Denguélé District (North West of Ivory Coast)

2021 ◽  
pp. 45-58
Keyword(s):  
Principal Component ◽  
Input Image ◽  
Contour Length ◽  
Landsat 8 ◽  
Difference Threshold ◽  
North West ◽  
Extraction Algorithm ◽  
Cumulative Length ◽  
Lineament Extraction ◽  
Automatic Lineament Extraction

The aim of this work was to apply the LINE Algorithm (Segment Extraction Algorithm) on Landsat 8 images for automatic lineament extraction in the Denguélé district. The Landsat 8 images had previously been subjected to the technique of Principal Component Analysis (PCA). After that, we implemented the LINE algorithm. Indeed, the LINE algorithm uses the following six (6) parameters : RADI (Radius of the filter) for improving the quality of the input image, GTHR (Threshold of the contour gradient), LTHR (Threshold of the contour length), FTHR (Threshold of mounting error), ATHR (Angular difference threshold between two contours ) and DTHR (Distance chaining threshold to link two contours ) for lineament discrimination. Analysis of the principal components PCA 1, PCA2 and PCA3 of bands 1, 2, 3, 4, 5 and 7 of the Landsat 8 images shows that they contain respectively 79.57; 15.88 and 2.15%, this represents overall 97.6% of all channels. 3468 lineaments were extracted. The minimum and maximum lengths of the lineaments extracted are respectively 4201.08 m and 16167.59 m and their cumulative length is 18 919 517.9 m. The lineaments average lengths are 5.55 km; 5.75 km; 5.6 km and 5.40 km respectively for NE-SW, NS, E-W and NW-SE directions. The analysis of the directions of the lineaments using a rose diagram with 10 ° of frequency, shows that the dominant directions are NE-SW (31.83% of the total lineaments), EW (28.71% of the total lineaments) and NS (27.91% of the total lineaments).

scholarly journals Lithological mapping and automatic lineament extraction using Aster and Gdem data in the Imini-Ounilla-Asfalou district, South High Atlas of Marrakech, Morocco

2021 ◽  
Vol 240 ◽  
pp. 04002
Author(s):  
Abdelouhed Farah ◽  
Ahmed Algouti ◽  
Abdellah Algouti ◽  
Kamal El badaoui ◽  
Maryam Errami ◽  
...  
Keyword(s):  
Near Infrared ◽  
Satellite Image ◽  
Principal Component ◽  
Short Wave ◽  
Spectral Angle Mapper ◽  
High Atlas ◽  
Lithological Mapping ◽  
High Concentrations ◽  
Lineament Extraction ◽  
Automatic Lineament Extraction

Lithological and lineament mapping using remote sensing is a fundamental step in various geological studies, as it forms the basis for the interpretation and validation of the results obtained. There were two objectives for this study, applied in the Imini-Ounilla-Asfalou district, South High Atlas of Marrakech region: first, lithological mapping by satellite image processing techniques such as ASTER L1B (hight spectral and spatial resolution), namely Principal Component Analysis (PCA), Minimum Noise Fraction (MNF), as well as the application of three types of supervised classification, namely Spectral Angle Mapper (SAM), Maximum Likelihood (ML) and Minimum Distance (MD), on the visible/near-infrared (VNIR) and short-wave infrared (SWIR) spectral bands of our ASTER image; second, an analysis of the distribution of lineaments by automatic extraction using a Global Digital Elevation Model (GDEM) and the PC1 image derived from the PCA transformation applied to the satellite image. The best results are highlighted by the delineation of new facies in relation to the existing map; after confirmation in the field, all of these facies, which include Eocene, Triassic and Jurassic formations, are represented on the new map. The results of lineaments showed that each of them systematically shows a similarity in terms of concentration and orientation, with four preferential oriented systems: NE-SW, E-W, NNE-SSW and NW-SE. The lineaments mainly follow those of the major fault zones, with high concentrations in the northeast and southwest parts of the study area.

scholarly journals A Satellite-based Remote Sensing Technique for Surface Water Quality Estimation

2019 ◽  
Vol 9 (2) ◽  
pp. 3965-3970 ◽  
Author(s):  
M. V. Japitana ◽  
M. E. C. Burce
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Temporal Trends ◽  
Oxygen Demand ◽  
Surface Water Quality ◽  
Principal Component ◽  
Input Image ◽  
Landsat 8 ◽  
Band Ratio ◽  
Remote Sensing Technique

Remote sensing provides a synoptic view of the earth surface that can provide spatial and temporal trends necessary for comprehensive water quality (WQ) monitoring and assessment. This study explores the applicability of Landsat 8 and regression analysis in developing models for estimating WQ parameters such as pH, dissolved oxygen (DO), total dissolved solids (TDS), total suspended solids (TSS), biological oxygen demand (BOD), turbidity, and conductivity. The input image was radiometrically-calibrated using fast line-of-sight atmospheric analysis (FLAASH) and then atmospherically corrected to obtain surface reflectance (SR) bands using FLAASH and dark object subtraction (DOS) for comparison. SR bands derived using FLAASH and DOS, water indices, band ratio, and principal component analysis (PCA) images were utilized as input data. Feature vectors were then collected from the input bands and subsequently regressed together with the WQ data. Forward regression results yielded significant high R2 values for all WQ parameters except TSS and conductivity which had only 60.1% and 67.7% respectively. Results also showed that the regression models of pH, BOD, TSS, TDS, DO, and conductivity are highly significant to SR bands derived using DOS. Furthermore, the results of this study showed the promising potential of using RS-based WQ models in performing periodic WQ monitoring and assessment.

scholarly journals Comparison of Multi-Resolution Optical Landsat-8, Sentinel-2 and Radar Sentinel-1 Data for Automatic Lineament Extraction: A Case Study of Alichur Area, SE Pamir

2019 ◽  
Vol 11 (7) ◽  
pp. 778 ◽  
Author(s):  
Aminov Javhar ◽  
Xi Chen ◽  
Anming Bao ◽  
Aminov Jamshed ◽  
Mamadjanov Yunus ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Accuracy Assessment ◽  
Remote Sensing Data ◽  
Radar Data ◽  
Optical Data ◽  
Landsat 8 ◽  
Geological Investigation ◽  
Lineament Extraction ◽  
Automatic Lineament Extraction ◽  
Sentinel 2A

Lineament mapping, which is an important part of any structural geological investigation, is made more efficient and easier by the availability of optical as well as radar remote sensing data, such as Landsat and Sentinel with medium and high spatial resolutions. However, the results from these multi-resolution data vary due to their difference in spatial resolution and sensitivity to soil occupation. The accuracy and quality of extracted lineaments depend strongly on the spatial resolution of the imagery. Therefore, the aim of this study was to compare the optical Landsat-8, Sentinel-2A, and radar Sentinel-1A satellite data for automatic lineament extraction. The framework of automatic approach includes defining the optimal parameters for automatic lineament extraction with a combination of edge detection and line-linking algorithms and determining suitable bands from optical data suited for lineament mapping in the study area. For the result validation, the extracted lineaments are compared against the manually obtained lineaments through the application of directional filtering and edge enhancement as well as to the lineaments digitized from the existing geological maps of the study area. In addition, a digital elevation model (DEM) has been utilized for an accuracy assessment followed by the field verification. The obtained results show that the best correlation between automatically extracted lineaments, manual interpretation, and the preexisting lineament map is achieved from the radar Sentinel-1A images. The tests indicate that the radar data used in this study, with 5872 and 5865 lineaments extracted from VH and VV polarizations respectively, is more efficient for structural lineament mapping than the Landsat-8 and Sentinel-2A optical imagery, from which 2338 and 4745 lineaments were extracted respectively.

scholarly journals Development of the Statistical Model for Monitoring Salinization in the Mekong Delta of Vietnam Using Remote Sensing Data and In-Situ Measurements

Proceedings ◽  
2018 ◽  
Vol 2 (10) ◽  
pp. 565
Author(s):  
Nguyen Nguyen Vu ◽  
Le Van Trung ◽  
Tran Thi Van
Keyword(s):  
Statistical Model ◽  
Mekong Delta ◽  
Remote Sensing Data ◽  
Principal Component ◽  
Measured Data ◽  
In Situ Measurements ◽  
Landsat 8 ◽  
Spectral Bands ◽  
Component Band

This article presents the methodology for developing a statistical model for monitoring salinity intrusion in the Mekong Delta based on the integration of satellite imagery and in-situ measurements. We used Landsat-8 Operational Land Imager and Thermal Infrared Sensor (Landsat- 8 OLI and TIRS) satellite data to establish the relationship between the planetary reflectance and the ground measured data in the dry season during 2014. The three spectral bands (blue, green, red) and the principal component band were used to obtain the most suitable models. The selected model showed a good correlation with the exponential function of the principal component band and the ground measured data (R2 > 0.8). Simulation of the salinity distribution along the river shows the intrusion of a 4 g/L salt boundary from the estuary to the inner field of more than 50 km. The developed model will be an active contribution, providing managers with adaptation and response solutions suitable for intrusion in the estuary as well as the inner field of the Mekong Delta.

Robust-PCA-based hierarchical plane extraction for application to geometric 3D indoor mapping

2014 ◽  
Vol 41 (2) ◽  
pp. 203-212 ◽  
Author(s):  
Suyong Yeon ◽  
ChangHyun Jun ◽  
Hyunga Choi ◽  
Jaehyeon Kang ◽  
Youngmok Yun ◽  
...  
Keyword(s):  
Principal Component ◽  
Point Clouds ◽  
Previous Method ◽  
Divide And Conquer ◽  
Sensor Data ◽  
Estimation Accuracy ◽  
Content Type ◽  
Extraction Algorithm ◽  
Plane Extraction ◽  
Scan Data

Purpose – The authors aim to propose a novel plane extraction algorithm for geometric 3D indoor mapping with range scan data. Design/methodology/approach – The proposed method utilizes a divide-and-conquer step to efficiently handle huge amounts of point clouds not in a whole group, but in forms of separate sub-groups with similar plane parameters. This method adopts robust principal component analysis to enhance estimation accuracy. Findings – Experimental results verify that the method not only shows enhanced performance in the plane extraction, but also broadens the domain of interest of the plane registration to an information-poor environment (such as simple indoor corridors), while the previous method only adequately works in an information-rich environment (such as a space with many features). Originality/value – The proposed algorithm has three advantages over the current state-of-the-art method in that it is fast, utilizes more inlier sensor data that does not become contaminated by severe sensor noise and extracts more accurate plane parameters.

scholarly journals Exploring Electronic Payment System Acceptibility Determinants: A Consumer Outlook

2018 ◽  
Vol 6 (1) ◽  
pp. 21-27 ◽  
Author(s):  
Akanksha Upadhyaya ◽  
Bhajneet Kaur
Keyword(s):  
Age Groups ◽  
Principal Component ◽  
Payment System ◽  
Electronic Payment ◽  
North West ◽  
Rotation Method ◽  
Consumer Perspective ◽  
Best Fitting ◽  
Electronic Payment System ◽  
Security Concern

The aim of this research paper is to explore the electronic payment system (EPS) acceptability determinants, from the consumer perspective. Exploratory factor analysis has been used to explore the factors based on different statements. The study has been conducted in North-West region of Delhi. Data has been collected from male-female of different age groups by using the questionnaire tool of data collection. For extraction of factors Principal component analyses and Varimax with Kaiser Normalization rotation method was used. The rotated component matrix shows best fitting of items to form a factor. As per the convergence of items, 4 factors were extracted and named. These factors are security concern, Knowledge, awareness and acceptability & convenience which are contributing for acceptability of electronic payment system among the consumers.

scholarly journals Harumanis Mango Leaves Image Segmentation based on Wavelet Transformation with Phansalkar and Sauvola Thresholding

2021 ◽  
Vol 2107 (1) ◽  
pp. 012067
Author(s):  
Ong Boon Chin ◽  
Aimi Salihah Abdul Nasir ◽  
Ooi Wei Herng ◽  
Erdy Sulino Mohd Muslim Tan
Keyword(s):  
Wavelet Transformation ◽  
Soil Nutrient ◽  
Principal Component ◽  
Health Condition ◽  
Input Image ◽  
Nutrient Contents ◽  
Mango Tree ◽  
Mango Leaves ◽  
Ph Level ◽  
Sensitivity Specificity

Abstract Harumanis mango is one of the economic sources of the Perlis state. It has a sweeter taste compared to other mangoes. However, the Harumanis mango tree required specific weather, soil nutrient contents and pH level. This makes the farmer does not know the health condition of their Harumanis mango tree. Therefore, this project aims to provide the best method of leaves detection to the farmer. The leaves image samples are collecting from the orchard and undergo pre-processing. Then the input image was converted into grayscale with principal component analysis (PCA). Wavelet transformation was implemented to increase the discriminability of the segmentation technique for separating the leaf and background. The leaf segmentation is done by using Phansalkar and Sauvola thresholding techniques. After that, fill hole and area opening techniques are implementing to reduce noise in the image. These two thresholding techniques are comparing and discuss with their segmentation performance. Overall, Phansalkar thresholding has produced better performance in segmenting healthy and unhealthy Harumanis mango leaves with sensitivity, specificity and accuracy of 92.05%, 81.37% and 83.51%, respectively.

A Study on The Use of UAV Images to Improve the Separation Accuracy of Agricultural Land Areas

2021 ◽  
Author(s):  
Fahime Arabi Aliabad ◽  
Hamid Reza Ghafarian Malamiri ◽  
Saeed Shojaei
Keyword(s):  
Spatial Resolution ◽  
Agricultural Land ◽  
Principal Component ◽  
Landsat Image ◽  
Fuzzy Artmap ◽  
Landsat 8 ◽  
Pass Filter ◽  
Tree Methods ◽  
Uav Images ◽  
High Pass

Abstract Classifying satellite images with medium spatial resolution such as Landsat, it is usually difficult to distinguish between plant species, and it is impossible to determine the area covered with weeds. In this study, a Landsat 8 image along with UAV images was used to separate pistachio cultivars and separate weed from trees. In order to use the high spatial resolution of UAV images, image fusion was carried out through high-pass filter, wavelet, principal component transformation, BROVEY, IHS and Gram Schmidt methods, and ERGAS, RMSE and correlation criteria were applied to assess their accuracy. The results represented that the wavelet method with R2, RMSE and ERGAS 0.91, 12.22 cm and 2.05 respectively had the highest accuracy in combining these images. Then, images obtained by this method were chosen with a spatial resolution of 20 cm for classification. Different classification methods including unsupervised method, maximum likelihood, minimum distance, fuzzy artmap, perceptron and tree methods were evaluated. Moreover, six soil classes, Ahmad Aghaei, Akbari, Kalleh Ghoochi, Fandoghi and a mixing class of Kalleh Ghoochi and Fandoghi were applied and also three classes of soil, pistachio tree and weeds were extracted from the trees. The results demonstrated that the fuzzy artmap method had the highest accuracy in separating weeds from trees, differentiating various pistachio cultivars with Landsat image and also classification with combined image and had 0.87, 0.79 and 0.87 kappa coefficients respectively. The comparison between pistachio cultivars through Landsat image and combined image showed that the validation accuracy obtained from harvest has raised by 17% because of combination of images. The results of this study indicated that the combination of UAV and Landsat 8 images affects well to separate pistachio cultivars and determine the area covered with weeds.

scholarly journals Geospatial delineation and mapping of groundwater potential in Embu County, Kenya

2019 ◽  
Vol 8 (2) ◽  
Author(s):  
Mary Christine Chepchumba ◽  
James M. Raude ◽  
Joseph K. Sang
Keyword(s):  
Groundwater Resources ◽  
Principal Component ◽  
Groundwater Potential ◽  
Geographical Information ◽  
Landsat 8 ◽  
Potential Zone ◽  
Groundwater Potential Zones ◽  
Study Approach ◽  
Rs And Gis ◽  
Groundwater Potential Map

Integration of Remote Sensing (RS) and the Geographical Information System (GIS) approaches in the field of groundwater resources management is a breakthrough. The RS and GIS geospatial approaches can enhance the assessment, monitoring, and conservation of groundwater resources. In this study, RS and GIS geospatial techniques were applied with the aim of identifying groundwater potential zones in Embu County, Kenya, based on selected multi influencing factors. Lineament layer was obtained by processing Landsat 8 ETM+ image using Principal Component Analysis in ENVI®4.7 and automatic extraction from Principal Component Image using the LINE module in Geomatica software. The resultant groundwater potential map showed that approximately 78% of the total area ranged from ‘high’ to ‘very high’ zones indicating that almost half of the study area has good groundwater potential. About 20% showed moderate potential while only 2% fell under the low potential zone. The proposed study approach can be used as a new way of modeling geospatial data for identification and mapping of groundwater potential zones. The study findings are useful to first-hand information planners and local authorities for assessment, planning, management and administration of groundwater resources in Embu County.

Redescription of Paratrophurus anomalus (Rhabditida: Dolichodoridae) from South Africa

Nematology ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. 543-554 ◽  
Author(s):  
Ebrahim Shokoohi ◽  
Joaquín Abolafia ◽  
Phatu William Mashela
Keyword(s):  
South Africa ◽  
Principal Component ◽  
Tail Length ◽  
Tail Region ◽  
New Host ◽  
Lateral Field ◽  
North West ◽  
The North ◽  
Close Relationship ◽  
New Geographical Record

Summary Paratrophurus anomalus is redescribed from the North-West Province, South Africa, associated with the rhizosphere of a willow tree, a dominant ornamental tree in the province. This population is characterised by its adult body length (696 (625-834) μm for female and 706 μm for male), lateral field with four longitudinal incisures, cephalic framework well cuticularised, lip region smooth and lacking annuli, female stylet 19.6 (18-21) μm long, female tail cylindrical, 35 (31-38) μm long, c′ = 2.3 (2.1-2.8), with thick hyaline region forming 31-43% of the tail length, spicules 22 μm long and gubernaculum 12 μm long. Morphologically, P. anomalus is very similar to P. kenanae and P. dissitus, although they differ on the basis of lip region morphology, stylet length, hyaline tail region, and spicule length. In addition, SEM observations are provided for the first time for this species along with a new host and new geographical record of the species from South Africa, providing new information for the revision of Paratrophurus. Molecular analysis of P. anomalus using ITS rDNA showed a close relationship with P. bursifer, P. bhutanensis and Bitylenchus species. In addition, principal component analysis was done for 14 character states of species in the genus.

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