|
|
|
|
|
| Wrublack,Suzana C.; Mercante,Erivelto; Boas,Marcio A. Vilas; Prudente,Victor H. R.; Silva,Jefferson L. G.. |
| ABSTRACT This study demonstrates using remote sensing, geographic information systems and multivariate statistics to study water quality in an agricultural watershed. The monitoring of water quality in the watershed of Lontras's river in the southwestern region of the State of Paraná had been done in 2012 and 2013 with a multi-parameter probe in ten sites that were defined upstream and downstream watershed, during four different seasons. Mosaicked images were used from Google Earth, Digital Elevation Model and soil types of maps, defined as the explanatory variables. The definition of the areas of influence and multivariate statistical techniques, particularly the Redundancy Analysis (RDA), were used for the correlation between variables. In a spring area,... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Geoprocessing; Mapping land use and occupation; Water quality. |
| Ano: 2018 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162018000100074 |
| |
|
|
| Wrublack,Suzana C.; Mercante,Erivelto; Vilas Boas,Marcio A.. |
| The objective of this study consisted on mapping the use and soil occupation and evaluation of the quality of irrigation water used in Salto do Lontra, in the state of Paraná, Brazil. Images of the satellite SPOT-5 were used to perform the supervised classification of the Maximum Likelihood algorithm - MAXVER, and the water quality parameters analyzed were pH, EC, HCO3-, Cl-, PO4(3-), NO3-, turbidity, temperature and thermotolerant coliforms in two distinct rainfall periods. The water quality data were subjected to statistical analysis by the techniques of PCA and FA, to identify the most relevant variables in assessing the quality of irrigation water. The characterization of soil use and occupation by the classifier MAXVER allowed the identification of... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Global Navigation Satellite Systems - GNSS; Geographic Information Systems - GIS; Irrigation. |
| Ano: 2013 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162013000500014 |
| |
|
|
|
