Socio-Economic Indicators for Performance Evaluation and Quality Assessment: Statistical Methods and Applications

2019 ◽  
Vol 146 (1-2) ◽  
pp. 1-5
Author(s):  
Matilde Bini ◽  
Maurizio Carpita ◽  
Donato Posa ◽  
Pasquale Sarnacchiaro
Author(s):  
D. Gursoy ◽  
M. Uysal ◽  
E. Sirakaya-Turk ◽  
Y. Ekinci ◽  
S. Baloglu

2012 ◽  
Vol 223 (9) ◽  
pp. 5549-5561 ◽  
Author(s):  
Judite S. Vieira ◽  
José C. M. Pires ◽  
Fernando G. Martins ◽  
Vítor J. P. Vilar ◽  
Rui A. R. Boaventura ◽  
...  

2009 ◽  
Vol 44 (3) ◽  
pp. 279-293 ◽  
Author(s):  
Ozan Arslan

Abstract The study offers a GIS-based multivariate statistical analysis strategy to assess river water quality. Multivariate statistical methods and Geographic Information System (GIS) technology have effectively been used for water quality management. Recognizing the fact that the use of standard statistical methods can be restrictive due to the complexity of water quality datasets, geospatial statistical methods have been recommended for the water quality assessment. The objective of the study was to explore the potential capabilities of GIS-based joint multivariate statistical analysis for water quality assessment of Porsuk River in Turkey. A well-known multivariate statistical technique, principal component analysis (PCA), is incorporated into a geographic database for interpretation of water quality data. To characterize spatial variability of water quality data, spatial PCA was performed on the basis of spatial autocorrelation. Application of the joint spatio-multivariate statistical analysis for interpretation of the water quality database offered a better understanding of the hydrochemistry in the study region.


Sign in / Sign up

Export Citation Format

Share Document