Nina Siu-Ngan Lam
Biographic Data
| ID | 5232336 |
|---|---|
| NAME | Nina Siu-Ngan Lam |
| GIVEN NAMES | Nina Siu-Ngan |
| FAMILY NAME | Lam |
| SIGNATURE | LAM N S |
| VERIFIED | No |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 7 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1983 |
| LATEST PUBLICATION YEAR | 2012 |
| H-INDEX | 2 |
Geospatial Methods for Reducing Uncertainties in Environmental Health Risk Assessment
As in many studies involving disparate data and methodologies, environmental health risk assessment research is prone to errors and uncertainties. Unfortunately, uncertainties associated with the research findings can seldom be eliminated, and policy decisions often need to be made based on the uncertain findings. Hence methods that can help reduce uncertainties associated with the research findings would be most useful and need to be developed. …
Paleovegetational Reconstruction Based on Modern and Fossil Pollen Data
This paper introduces the use of discriminant analysis as an aid in paleovegetational reconstruction based on modern and fossil pollen data. We derived a set of discriminant functions that correctly classifies 95 percent of 121 surface samples collected from different vegetation regions in northeastern North America. These functions were then applied to the pollen-stratigraphic data from Jack Lake to reconstruct the postglacial vegetational histo…
Spatial Interpolation Methods
Two forms of spatial interpolation, the interpolation of point and areal data, are distinguished. Traditionally, point interpolation is applied to isarithmic, that is, contour mapping and areal interpolation to isopleth mapping. Recently, areal interpolation techniques have been used to obtain data for a set of administrative or political districts from another set of districts whose boundaries do not coincide. For point interpolation, the numero…
Paleovegetational Reconstruction Based on Modern and Fossil Pollen Data
This paper introduces the use of discriminant analysis as an aid in paleovegetational reconstruction based on modern and fossil pollen data. We derived a set of discriminant functions that correctly classifies 95 percent of 121 surface samples collected from different vegetation regions in northeastern North America. These functions were then applied to the pollen-stratigraphic data from Jack Lake to reconstruct the postglacial vegetational histo…
Geospatial Methods for Reducing Uncertainties in Environmental Health Risk Assessment
As in many studies involving disparate data and methodologies, environmental health risk assessment research is prone to errors and uncertainties. Unfortunately, uncertainties associated with the research findings can seldom be eliminated, and policy decisions often need to be made based on the uncertain findings. Hence methods that can help reduce uncertainties associated with the research findings would be most useful and need to be developed. …
Spatial Interpolation Methods
Two forms of spatial interpolation, the interpolation of point and areal data, are distinguished. Traditionally, point interpolation is applied to isarithmic, that is, contour mapping and areal interpolation to isopleth mapping. Recently, areal interpolation techniques have been used to obtain data for a set of administrative or political districts from another set of districts whose boundaries do not coincide. For point interpolation, the numero…
Paleovegetational Reconstruction Based on Modern and Fossil Pollen Data
This paper introduces the use of discriminant analysis as an aid in paleovegetational reconstruction based on modern and fossil pollen data. We derived a set of discriminant functions that correctly classifies 95 percent of 121 surface samples collected from different vegetation regions in northeastern North America. These functions were then applied to the pollen-stratigraphic data from Jack Lake to reconstruct the postglacial vegetational histo…
Geospatial Methods for Reducing Uncertainties in Environmental Health Risk Assessment
As in many studies involving disparate data and methodologies, environmental health risk assessment research is prone to errors and uncertainties. Unfortunately, uncertainties associated with the research findings can seldom be eliminated, and policy decisions often need to be made based on the uncertain findings. Hence methods that can help reduce uncertainties associated with the research findings would be most useful and need to be developed. …
Computer Science (3 works) · Artificial Intelligence (2 works) · Geography (2 works) · Mathematics (2 works) · Statistics (2 works) · Air Quality and Health Impacts (1 works) · Algorithm (1 works) · Artificial Intelligence (1 works) · Atmospheric and Environmental Gas Dynamics (1 works) · Bilinear interpolation (1 works)