Barbara P Buttenfield
Biographic Data
| ID | 5232801 |
|---|---|
| NAME | Barbara P Buttenfield |
| GIVEN NAMES | Barbara P |
| FAMILY NAME | Buttenfield |
| SIGNATURE | BUTTENFIELD B P |
| AFFILIATIONS | University at Buffalo, State University of New York |
| VERIFIED | No |
| TOTAL WORKS | 7 |
| TOTAL CITATIONS | 17 |
| WORKS AS AUTHOR | 7 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 1989 |
| LATEST PUBLICATION YEAR | 2021 |
| H-INDEX | 2 |
How to Measure Distance on a Digital Terrain Surface and Why it Matters in Geographical Analysis
Distance is the most fundamental metric in spatial analysis and modeling. Planar distance and geodesic distance are the common distance measurements in current geographic information systems and geospatial analytic tools. However, there is little understanding about how to measure distance in a digital terrain surface and the uncertainty of the measurement. To fill this gap, this study applies a Monte‐Carlo simulation to evaluate seven surface‐ad…
Dasymetric Modeling and Uncertainty
Dasymetric models increase the spatial resolution of population data by incorporating related ancillary data layers. The role of uncertainty in dasymetric modeling has not been fully addressed as of yet. Uncertainty is usually present because most population data are themselves uncertain, and/or the geographic processes that connect population and the ancillary data layers are not precisely known. A new dasymetric methodology - the Penalized Maxi…
Terrorism, Information Technology, and Vulnerability
Formalizing Semantic Spaces For Information Access
An exponentially growing volume of digital information makes extraction of relevant items increasingly difficult. This article documents the adoption of information visualization tools by researchers in the disciplines of geography, computer science, and information science to facilitate exploration of very large data archives. Graphic depiction of database content (or the database “semantics”) can be based on a spatial or even a geographic metap…
Representing Data Quality
Information on data quality is important for effective use of GIS data. It impacts the credibility of data representation and the confidence that is attached to data interpretations. It impacts the reliability of interpretations and thus decision making based on GIS modeling and data exploration. A number of impediments to representing data quality can be cited, including impediments to definition and assessment, to attribution in a database, and…
Reconsidering Rules For Point-Feature Name Placement
Existing guidelines for automated map name placement are usually based on Imhofâ€TMs (1975) and Yoeli's (1972) research, guidelines for name placement that have not been verified empirically. This study addresses the validity of Yoeli's model concerning eight possible positions for labeling a name to a point feature and their priorities. Investigation is focused on how lettering is placed on road maps, and on the diversities in styles of name pla…
Scale-Dependence And Self-Similarity In Cartographic Lines
This paper provides a typology of two classes of geometry for cartographic lines, based on the well-known Richardson plots. The first class contains objects having self-similar geometry, features whose structural characteristics are replicated either precisely or statistically with changes in scale. Self-similar features are currently described by fractal models, which some argue are appropriate for all cartographic objects. The fallacy of this s…
Formalizing Semantic Spaces For Information Access
An exponentially growing volume of digital information makes extraction of relevant items increasingly difficult. This article documents the adoption of information visualization tools by researchers in the disciplines of geography, computer science, and information science to facilitate exploration of very large data archives. Graphic depiction of database content (or the database “semantics”) can be based on a spatial or even a geographic metap…
Dasymetric Modeling and Uncertainty
Dasymetric models increase the spatial resolution of population data by incorporating related ancillary data layers. The role of uncertainty in dasymetric modeling has not been fully addressed as of yet. Uncertainty is usually present because most population data are themselves uncertain, and/or the geographic processes that connect population and the ancillary data layers are not precisely known. A new dasymetric methodology - the Penalized Maxi…
Terrorism, Information Technology, and Vulnerability
Scale-Dependence And Self-Similarity In Cartographic Lines
This paper provides a typology of two classes of geometry for cartographic lines, based on the well-known Richardson plots. The first class contains objects having self-similar geometry, features whose structural characteristics are replicated either precisely or statistically with changes in scale. Self-similar features are currently described by fractal models, which some argue are appropriate for all cartographic objects. The fallacy of this s…
Reconsidering Rules For Point-Feature Name Placement
Existing guidelines for automated map name placement are usually based on Imhofâ€TMs (1975) and Yoeli's (1972) research, guidelines for name placement that have not been verified empirically. This study addresses the validity of Yoeli's model concerning eight possible positions for labeling a name to a point feature and their priorities. Investigation is focused on how lettering is placed on road maps, and on the diversities in styles of name pla…
Representing Data Quality
Information on data quality is important for effective use of GIS data. It impacts the credibility of data representation and the confidence that is attached to data interpretations. It impacts the reliability of interpretations and thus decision making based on GIS modeling and data exploration. A number of impediments to representing data quality can be cited, including impediments to definition and assessment, to attribution in a database, and…
Formalizing Semantic Spaces For Information Access
An exponentially growing volume of digital information makes extraction of relevant items increasingly difficult. This article documents the adoption of information visualization tools by researchers in the disciplines of geography, computer science, and information science to facilitate exploration of very large data archives. Graphic depiction of database content (or the database “semantics”) can be based on a spatial or even a geographic metap…
Terrorism, Information Technology, and Vulnerability
Dasymetric Modeling and Uncertainty
Dasymetric models increase the spatial resolution of population data by incorporating related ancillary data layers. The role of uncertainty in dasymetric modeling has not been fully addressed as of yet. Uncertainty is usually present because most population data are themselves uncertain, and/or the geographic processes that connect population and the ancillary data layers are not precisely known. A new dasymetric methodology - the Penalized Maxi…
How to Measure Distance on a Digital Terrain Surface and Why it Matters in Geographical Analysis
Distance is the most fundamental metric in spatial analysis and modeling. Planar distance and geodesic distance are the common distance measurements in current geographic information systems and geospatial analytic tools. However, there is little understanding about how to measure distance in a digital terrain surface and the uncertainty of the measurement. To fill this gap, this study applies a Monte‐Carlo simulation to evaluate seven surface‐ad…
Geography (6 works) · Cartography (5 works) · Computer Science (5 works) · Data Management and Algorithms (4 works) · Geographic Information Systems Studies (4 works) · Data mining (3 works) · Engineering (3 works) · Data science (2 works) · Geospatial analysis (2 works) · Humanities (2 works)