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  • geostatistics  (1)
  • health effects  (1)
  • Springer  (2)
  • 1995-1999  (2)
  • 1960-1964
  • 1999  (2)
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  • Springer  (2)
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  • 1995-1999  (2)
  • 1960-1964
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  • 1999  (2)
  • 1
    Electronic Resource
    Electronic Resource
    Adverse Health Experiences, Environmental Attitudes, and Pesticide Usage Behavior of Farm Operators (1999)
    Springer
    Risk analysis 19 (1999), S. 283-294 
    Details
    ISSN: 1539-6924
    Keywords: Risk perception ; pesticides ; pest management ; health effects ; agricultural pollution
    Source: Springer Online Journal Archives 1860-2000
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Notes: Abstract Water pollution from agricultural pesticides continues to be a public concern. Given that the use of such pesticides on the farm is largely governed by voluntary behavior, it is important to understand what drives farmer behavior. Health belief models in public health and social psychology argue that persons who have adverse health experiences are likely to undertake preventive behavior. An analogous hypothesis set was tested here: farmers who believe they have had adverse health experiences from pesticides are likely to have heightened concerns about pesticides and are more likely to take greater precautions in dealing with pesticides. This work is based on an original survey of a population of 2700 corn and soybean growers in Maryland, New York, and Pennsylvania using the U.S. Department of Agriculture data base. It was designed as a mail survey with telephone follow-up, and resulted in a 60 percent response rate. Farm operators report experiencing adverse health problems they believe are associated with pesticides that is equivalent to an incidence rate that is higher than the reported incidence of occupational pesticide poisonings, but similar to the reported incidence of all pesticide poisonings. Farmers who report experiencing such problems have more heightened concerns about water pollution from fertilizers and pesticides, and illness and injury from mixing, loading, and applying pesticides than farmers who have not experienced such problems. Farmers who report experiencing such problems also are more likely to report using alternative pest management practices than farmers who do not report having such problems. This implies that farmers who have had such experiences do care about the effects of application and do engage in alternative means of pest management, which at least involve the reduction in pesticide use.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1006929812285
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  • 2
    Electronic Resource
    Electronic Resource
    An Experimental Comparison of Ordinary and Universal Kriging and Inverse Distance Weighting (1999)
    Springer
    Mathematical geology 31 (1999), S. 375-390 
    Details
    ISSN: 1573-8868
    Keywords: geostatistics ; spatial interpolation ; spatial pattern ; surface-fitting algorithms
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract A factorial, computational experiment was conducted to compare the spatial interpolation accuracy of ordinary and universal kriging and two types of inverse squared-distance weighting. The experiment considered, in addition to these four interpolation methods, the effects of four data and sampling characteristics: surface type, sampling pattern, noise level, and strength of small-scale spatial correlation. Interpolation accuracy was measured by the natural logarithm of the mean squared interpolation error. Main effects of all five factors, all two-factor interactions, and several three-factor interactions were highly statistically significant. Among numerous findings, the most striking was that the two kriging methods were substantially superior to the inverse distance weighting methods over all levels of surface type, sampling pattern, noise, and correlation.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1007586507433
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    Paper (German National Licenses)
    Fulltext
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