V. Chris Lakhan

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Since it is necessary to isolate the most significant factors influencing personal concern for the environment, this paper utilizes loglinear models for identifying the interactions and interrelationships underlying multidimensional environmental survey data. A field study in Guyana conducted face-to-face interviews with 1600 citizens. Acquired categorical(More)
The existence of uncertainty in classified remotely sensed data necessitates the application of enhanced techniques for identifying and visualizing the various degrees of uncertainty. This paper, therefore, applies the multidimensional graphical data analysis technique of parallel coordinate plots (PCP) to visualize the uncertainty in Landsat Thematic(More)
Soils from different land use areas in Lahore City, Pakistan, were analyzed for concentrations of heavy metals-cadmium (Cd), chromium (Cr), nickel (Ni), and lead (Pb). One hundred one samples were randomly collected from six land use areas categorized as park, commercial, agricultural, residential, urban, and industrial. Each sample was analyzed in the(More)
Loglinear modelling techniques were used to identify the interactions and interrelationships underlying categorical environmental concern data collected from 9062 respondents in Iran. After fitting various loglinear models to the data, the most parsimonious model highlighted that a combination of interacting factors, namely educational attainment, age,(More)
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