Image Quality Assessment for Fused Remote Sensing Imageries

2014 ◽  
Vol 71 (4) ◽  
Author(s):  
Mohd Nadzri Md Reba ◽  
Ong Juey C’uang
Keyword(s):  
Image Quality Assessment ◽  
Principal Component ◽  
High Accuracy ◽  
Fusion Image ◽  
Precise Information ◽  
Qualitative And Quantitative ◽  
Fused Image ◽  
Quantitative Assessments

Image fusion provides precise information in both spatial and spectral resolutions that benefit significantly in high accuracy mapping. Yet, there is less intention withdrawn in justifying the performance of the fused image. In this study, qualitative and quantitative assessments were carried out to test the quality of fusion image. Principal Component Analysis (PCA), Gram-Schmidt and Ehlers were applied to fuse the hyperspectral and Lidar image. Ehlers fusion showed good in preserving the color of image and contained the most information. Besides, the classification of Ehlers fused image showed the highest accuracy.

scholarly journals Metabolomics Approach for Discrimination and Quality Control of Natural and Commercial Fallopia multiflora Products in Vietnam

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Nguyen Thi Thoa ◽  
Nguyen Hai Dang ◽  
Do Hoang Giang ◽  
Nguyen Thi Thu Minh ◽  
Nguyen Tien Dat
Keyword(s):  
Clustering Analysis ◽  
Principal Component ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
Fda Guidance ◽  
Promising Tool ◽  
Precision And Accuracy ◽  
And Control

A precise HPLC-DAD-based quantification together with the metabolomics statistical method was developed to distinguish and control the quality of Fallopia multiflora, a popular medicinal material in Vietnam. Multivariate statistical methods such as hierarchical clustering analysis and principal component analysis were utilized to compare and discriminate six natural and twelve commercial samples. 2,3,4′,5-Tetrahydroxystilbene 2-O-β-D-glucopyranoside (THSG) (1), emodin (4), and the new compound 6-hydroxymusizin 8-O-α-D-apiofuranosyl-(1⟶6)-β-D-glucopyranoside (5) could be considered as important markers for classification of F. multiflora. Furthermore, seven phenolics were quantified that the variation in the contents of selected metabolites revealed the differences in the quality of natural and commercial samples. Recovery of the compounds from the analytes was more than 98%, while the limits of detection (LOD) and the limits of quantitation (LOQ) ranged from 0.5 to 6.6 μg/ml and 1.5 to 19.8 μg/ml, respectively. The linearity, LOD, LOQ, precision, and accuracy satisfied the criteria FDA guidance on bioanalytical methods. Overall, this method is a promising tool for discrimination and quality assurance of F. multiflora products.

scholarly journals CLASSIFICATION OF SATELLITE FUSED DATA FOR LAND USE MAPPING IN DEVELOPMENT PLAN

2011 ◽  
Vol 9 (2) ◽  
Author(s):  
Norzailawati Mohd Noor ◽  
Alias Abdullah ◽  
Mazlan Hashim
Keyword(s):  
Land Use ◽  
Principal Component ◽  
Kappa Statistic ◽  
Development Plan ◽  
Remotely Sensed Data ◽  
Data Set ◽  
Principal Component Transform ◽  
Fused Image ◽  
Fine Resolution

Land use mapping in development plan basically provides resources of information and important tool in decision making. In relation to this, fine resolution of recent satellite remotely sensed data have found wide applications in land use/land cover mapping. This study reports on work carried out for classification of fused image for land use mapping in detail scale for Local Plan. The LANDSATTM, SPOT Pan and IKONOS satellite were fused and examined using three data fusion techniques, namely Principal Component Transfonn (PCT), Wavelet Transform and Multiplicative fusing approach. The best fusion technique for three datasets was determined based on the assessment of class separabilities and visualizations evaluation of the selected subset of the fused datasets, respectively. Principal Component Transform has been found to be the best technique for fusing the three datasets, where the best fused data set was subjected to further classification for producing level of land use classes while level II and III pass on to nine classes of detail classification for local plan. The overall data classification accuracy of the best fused data set was 0.86 (kappa statistic). Final land use output from classified data was successfully generated in accordance to local plan land use mapping for development plan purposes.

Making the Best Use of Beamtime

2018 ◽  
Author(s):  
Eaton E. Lattman ◽  
Thomas D. Grant ◽  
Edward H. Snell
Keyword(s):  
Initial Data ◽  
Data Processing ◽  
Data Quality ◽  
Radiation Damage ◽  
Scattering Data ◽  
Modeling And Analysis ◽  
Flexible Molecules ◽  
Qualitative And Quantitative ◽  
Quantitative Assessments

Extracting information from scattering data is very sensitive to the quality of the data. In this chapter data quality characterization is described, including initial data processing procedures to alert the user to potential data quality issues. Accurate buffer subtraction is crucial for correct modeling and analysis of SAS data, and mechanisms for identifying buffer subtraction errors are discussed. Examining SAS parameters such as a function of concentration or exposure is very useful for identifying concentration dependent artifacts or radiation damage that, if unnoticed, can be very detrimental to further analysis, including misinterpreting the results and drawing erroneous conclusions. SAS is often used for analyzing flexible molecules in solution that may be difficult to study with other structural techniques. Qualitative and quantitative assessments of flexibility are described.

scholarly journals A Frequency-Based Approach for the Detection and Classification of Structural Changes Using t-SNE †

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5097 ◽  
Author(s):  
David Agis ◽  
Francesc Pozo
Keyword(s):  
Structural Changes ◽  
Dimensional Space ◽  
Principal Component ◽  
Majority Voting ◽  
Data Set ◽  
Centroid Distance ◽  
Low Dimensional ◽  
Reduced Data

This work presents a structural health monitoring (SHM) approach for the detection and classification of structural changes. The proposed strategy is based on t-distributed stochastic neighbor embedding (t-SNE), a nonlinear procedure that is able to represent the local structure of high-dimensional data in a low-dimensional space. The steps of the detection and classification procedure are: (i) the data collected are scaled using mean-centered group scaling (MCGS); (ii) then principal component analysis (PCA) is applied to reduce the dimensionality of the data set; (iii) t-SNE is applied to represent the scaled and reduced data as points in a plane defining as many clusters as different structural states; and (iv) the current structure to be diagnosed will be associated with a cluster or structural state based on three strategies: (a) the smallest point-centroid distance; (b) majority voting; and (c) the sum of the inverse distances. The combination of PCA and t-SNE improves the quality of the clusters related to the structural states. The method is evaluated using experimental data from an aluminum plate with four piezoelectric transducers (PZTs). Results are illustrated in frequency domain, and they manifest the high classification accuracy and the strong performance of this method.

Towards a Rural Sustainable Development? Contributions of the EAFRD 2007-2013 in Low Demographic Density Territories. The case of Extremadura (SW Spain)

2017 ◽  
Author(s):  
Gema Cárdenas Alonso ◽  
Ana Nieto Masot
Keyword(s):  
Sustainable Development ◽  
Rural Development ◽  
Rural Areas ◽  
Agricultural Sector ◽  
Principal Component ◽  
Quantitative Methodology ◽  
Sustainable Rural Development ◽  
Qualitative And Quantitative ◽  
Sw Spain

The European Commission has been striving to achieve sustainable development in its rural areas for more than 25 years through funds aimed at modernizing the agricultural and forestry sectors, protecting the environment and improving the quality of life. But is sustainable rural development really being accomplished? This study sets out to answer this question in the case of Extremadura, a Spanish territory with Low Demographic Density and a Gross Domestic Product still below 75 % of the European average. Both qualitative and quantitative methodology have been employed, using a Principal Component Analysis the result of which has provided us with a model which shows how various behaviors coexist in the region in view of the distribution of current funding from the EAFRD. The most dynamic areas have received the largest amounts of funding and these are linked to the agricultural sector and to the protection of the environment, leaving aside the more depressed areas and the implementation of the LEADER Approach as well. Therefore, we have come to the conclusion that the current rural development in Extremadura is not sustainable enough.

Assessment of SPOT-6 optical remote sensing data against GF-1 using NNDiffuse image fusion algorithm

2017 ◽  
Vol 31 (19-21) ◽  
pp. 1740043 ◽  
Author(s):  
Jinling Zhao ◽  
Junjie Guo ◽  
Wenjie Cheng ◽  
Chao Xu ◽  
Linsheng Huang
Keyword(s):  
Image Fusion ◽  
Near Infrared ◽  
Spectral Response ◽  
Remote Sensing Data ◽  
Principal Component ◽  
Optical Remote Sensing ◽  
Fusion Image ◽  
Fusion Algorithm ◽  
Color Quality ◽  
Fused Image

A cross-comparison method was used to assess the SPOT-6 optical satellite imagery against Chinese GF-1 imagery using three types of indicators: spectral and color quality, fusion effect and identification potential. More specifically, spectral response function (SRF) curves were used to compare the two imagery, showing that the SRF curve shape of SPOT-6 is more like a rectangle compared to GF-1 in blue, green, red and near-infrared bands. NNDiffuse image fusion algorithm was used to evaluate the capability of information conservation in comparison with wavelet transform (WT) and principal component (PC) algorithms. The results show that NNDiffuse fused image has extremely similar entropy vales than original image (1.849 versus 1.852) and better color quality. In addition, the object-oriented classification toolset (ENVI EX) was used to identify greenlands for comparing the effect of self-fusion image of SPOT-6 and inter-fusion image between SPOT-6 and GF-1 based on the NNDiffuse algorithm. The overall accuracy is 97.27% and 76.88%, respectively, showing that self-fused image of SPOT-6 has better identification capability.

scholarly journals Classification of Sediment Quality according to Its Behavior in the Accelerated Particle Wear Test (APW)

2021 ◽  
Vol 13 (5) ◽  
pp. 2633
Author(s):  
José I. Pagán ◽  
Antonio J. Tenza-Abril ◽  
Luis Aragonés ◽  
Yolanda Villacampa ◽  
Isabel López
Keyword(s):  
Coastal Erosion ◽  
Sediment Quality ◽  
Principal Component ◽  
Wear Test ◽  
Wear Process ◽  
Simple Tool ◽  
Quality Classification ◽  
Classification Index

One of the main problems faced in coastal management is the loss or destruction of beaches due to erosion. A considerable diversity of factors is involved in coastal erosion, which makes it a complex system to study. The quality of the material that constitutes the beach, as well as the choice of appropriate materials for its nourishment are two of the main ones. Therefore, to make future nourishment projects more sustainable and durable, this work proposes a sediment quality classification based on the physical properties and wear process obtained through laboratory tests. The study of these variables, using principal component analysis, discriminant analysis and ANOVA, has divided the quality of 70 samples into three main groups. A Sediment Quality Classification Index (SQCI) is proposed, which categorizes the quality of the material into poor, regular or good, providing the coastal engineer with a simple tool to ensure more sustainable beach nourishments.

scholarly journals Telehealth to the Rescue During COVID-19: A Convergent Mixed Methods Study Investigating Patients' Perception

2021 ◽  
Vol 9 ◽  
Author(s):  
Ghadah A. Al-Sharif ◽  
Alia A. Almulla ◽  
Eman AlMerashi ◽  
Reem Alqutami ◽  
Mohammad Almoosa ◽  
...  
Keyword(s):  
Mixed Methods ◽  
United Arab Emirates ◽  
Qualitative Data ◽  
Principal Component ◽  
Decision Makers ◽  
Healthcare Sector ◽  
Mixed Methods Design ◽  
Qualitative And Quantitative ◽  
Selection Of

Background: The onset of the pandemic necessitated abrupt transition to telehealth consultations. Although there is a few tools that gauge the patients' perception about their experiences, none of them are contextualized to an emergency in the Middle East and North Africa region. Accordingly, this study aims at developing and validating a tool to address this gap, and deploying it to assess the patients' perception of telehealth services during COVID-19 in Dubai, United Arab Emirates (UAE).Methods: A convergent mixed methods design was adapted. A random selection of 100 patients from Dubai, UAE were invited to participate. Qualitative and quantitative datasets were collected using a tailor-made survey. The qualitative data, collected through open-ended questions, was analyzed using multi-staged thematic analysis. As for the quantitative data, it captured the patients' extent of satisfaction, and was assessed using SPSS (with a series of descriptive and inferential analyses). The qualitative and quantitative findings were then merged via joint display analysis.Results: Out of the 100 patients that were randomly selected, 94 patients participated in this study. The reliability score of Cronbach's Alpha for the instrument was 98.9%. The percentage of the total average of satisfaction was 80.67%. The Principal Component Analysis showed that 88.1% of the variance can be explained by the instrument (p < 0.001). The qualitative data analysis expanded upon the quantitative findings enabling a better understanding of the patients' perception. Three themes, revolving around the quality of the patient telehealth experiences, surfaced: “Factors that worked to the benefit of the patients,” “Factors that the patients were not in favor of,” and “Opportunities for improvements as perceived by the patients.”Discussion: This study introduced a novel patient satisfaction with telehealth consultation survey contextualized to the COVID-19 times in Dubai, UAE. The participants were quite satisfied with the quality of their experience, however they suggested areas for improvement. Regional healthcare decision-makers can leverage the identified advantages and opportunities for improvement of telehealth. This will enable making informed decisions regarding the continuity of telehealth irrespective of how matters unfold in relation to the pandemic. It will also better prepare the healthcare sector for potential resurgence(s) of COVID-19 and/or the occurrence of other similar emergencies.

Analysis of Suitability for Development of New Mining Field in Northern Part of Kosovo Lignite Basin - Sibovc / Analiza Możliwości Udostępnienia Nowego Obszaru Wybierania W Północnej Części Zagłębia Węgla Brunatnego Sibovc W Kosowie

2013 ◽  
Vol 58 (2) ◽  
pp. 557-568
Author(s):  
Michal Cehlár ◽  
Radim Rybár ◽  
Ján Pinka ◽  
Lorik Haxhiu ◽  
Martin Beer
Keyword(s):  
Approximate Calculation ◽  
Financial Analysis ◽  
Energy Sector ◽  
Geological Model ◽  
Initial State ◽  
Qualitative And Quantitative ◽  
Quantitative Characteristics ◽  
Qualitative And Quantitative Characteristics

This review describes the possibility of development a new lignite deposit in northern Kosovo lignite basin - Sibovc. Analysis of the initial state briefly evaluates Kosovo energy sector, geomorphological conditions and quality of lignite from Sibovc deposit. With using Dataminesoft it was created geological model and approximate calculation of lignite reserves in the deposit. The data obtained from Dataminesoft were used as starting points of the financial analysis of project. The result of the analysis is exactly describe the qualitative and quantitative characteristics of deposit Sibovc compared to other deposits in the area and creating of geological model with productive horizons deposit of lignite. Based on these data lignite deposit Sibovc was classified, according to the classification of deposits the UN, as economical.

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