Barbara Buttenfield
Biographic Data
| ID | 274124 |
|---|---|
| NAME | Barbara Buttenfield |
| GIVEN NAMES | Barbara |
| FAMILY NAME | Buttenfield |
| SIGNATURE | BUTTENFIELD B |
| AFFILIATIONS | University of Colorado Boulder |
| ORCID | 0000-0001-5961-5809 |
| VERIFIED | Yes |
| TOTAL WORKS | 24 |
| TOTAL CITATIONS | 40 |
| AUTHOR COUNT | 24 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1985 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 3 |
Wetland Classification, Attribute Accuracy, and Scale
Quantification of all types of uncertainty helps to establish reliability in any analysis. This research focuses on uncertainty in two attribute levels of wetland classification and creates visualization tools to guide analysis of spatial uncertainty patterns over several scales. A novel variant of confusion matrix analysis compares the Cowardin and Hydrogeomorphic wetland classification systems, identifying areas and types of misclassification f…
Analyzing multi-scale spatial point patterns in a pyramid modeling framework
Many spatial analysis methods suffer from the scaling issue identified as part of the Modifiable Areal Unit Problem (MAUP). This article introduces the Pyramid Model (PM), a hierarchical data framework integrating space and spatial scale in a 3D environment to support multi-scale analysis. The utility of the PM is tested in examining quadrat density and kernel density, which are commonly used measures of point patterns. The two metrics computed f…
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…
An open source high-performance solution to extract surface water drainage networks from diverse terrain conditions
This paper describes a workflow for automating the extraction of elevation-derived stream lines using open source tools with parallel computing support and testing the effectiveness of procedures in various terrain conditions within the conterminous United States. Drainage networks are extracted from the US Geological Survey 1/3 arc-second 3D Elevation Program elevation data having a nominal cell size of 10 m. This research demonstrates the utili…
Deriving Small Area Mortality Estimates Using a Probabilistic Reweighting Method
Small area health estimates are important for studying environmental exposure, disease transmission, and health outcomes at the local scale. Yet, to protect privacy, the majority of publicly available health data are aggregated within larger spatial units such as states or counties. This article describes a method to generate small area mortality estimates from individual microdata that are available only for larger geographic entities. The morta…
A rapid approach for automated comparison of independently derived stream networks
This paper presents an improved coefficient of line correspondence (CLC) metric for automatically assessing the similarity of two different sets of linear features. Elevation-derived channels at 1:24,000 scale (24K) are generated from a weighted flow-accumulation model and compared to 24K National Hydrography Dataset (NHD) flowlines. The CLC process conflates two vector datasets through a raster line-density differencing approach that is faster a…
Exploring the impact of dasymetric refinement on spatiotemporal small area estimates
Comparing demographic small area estimates across multiple time periods is hindered by boundary changes in census enumeration units. Areal interpolation can resolve temporal incompatibilities, but underlying assumptions of uniform population density within units is sometimes flawed and results in distorted estimates. Dasymetric modeling refines spatial precision by limiting areal interpolation to the most likely residential areas. Here, a systema…
An evaluation of unsupervised and supervised learning algorithms for clustering landscape types in the United States
Knowledge of landscape type can inform cartographic generalization of hydrographic features, because landscape characteristics provide an important geographic context that affects variation in channel geometry, flow pattern, and network configuration. Landscape types are characterized by expansive spatial gradients, lacking abrupt changes between adjacent classes; and as having a limited number of outliers that might confound classification. The …
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…
Automated thinning of road networks and road labels for multiscale design of The National Map of the United States
This paper reports on progress in generalization and selective feature removal for a subset of fundamental base map layers that enables competent mapping through scales ranging from 1:24,000 to 1:1,000,000. Thinning and partitioning methods are applied to road features and labels for The National Map of the United States. Roads are thinned adaptively using the ArcGIS Thin Road Network geoprocessing tool, which removes features by feature hierarch…
Establishing relationships between parcel data and land cover for demographic small area estimation
Dasymetric and other small area estimation methods often use land-cover data in order to refine the spatial resolution of population data. The attribute tables of these land-cover data, however, are often related only weakly to population distribution. Recent studies have examined the use of parcel data, but parcel data are not available in all places. Thus, it becomes useful to identify the links between parcel data and land-cover data so that l…
Validation of spatially allocated small area estimates for 1880 Census demography
This paper details the validation of a methodology which spatially allocates Census microdata to census tracts, based on known, aggregate tract population distributions. To protect confidentiality, public-use microdata contain no spatial identifiers other
Hydrographic Generalization Tailored to Dry Mountainous Regions
A wide variety of climate and terrain conditions exist in the United States and optimal cartographic generalization techniques for one area of the country may not be suitable for another, particularly when working with surface hydrographic data. This paper presents generalization and data modeling to produce reduced scale versions of hydrographic data for a multi-resolution national data set, The National Map, of the United States Geological Surv…
Adapting Generalization Tools to Physiographic Diversity for the United States National Hydrography Dataset
This paper reports on generalization and data modeling to create reduced scale versions of the National Hydrographic Dataset (NHD) for dissemination through The National Map, the primary data delivery portal for USGS. Our approach distinguishes local differences in physiographic factors, to demonstrate that knowledge about varying terrain (mountainous, hilly or flat) and varying climate (dry or humid) can support decisions about algorithms, param…
Fuzzy Modeling of Geometric Textures for Identifying Archipelagos in Area-Patch Generalization
This paper describes a method to approach area-patch problems in model generalization using fuzzy set theory. The area-patch problem identifies polygons with the same semantics (feature code) but varying geometry and spatial distribution. Area-patch generalization can be understood as a pattern recognition problem with a variety of viable solutions, constrained by the purposes of the generalized output. The focus lies with identifying geometric t…
Framing Guidelines for Multi-Scale Map Design Using Databases at Multiple Resolutions
This paper extends European research on generating cartographic base maps at multiple scales from a single detailed database. Similar to the European work, we emphasize reference maps. In contrast to the Europeans' focus on data generalization, we emphasize changes to the map display, including symbol design or symbol modification. We also work from databases compiled at multiple resolutions rather than constructing all representations from a sin…
Terrorism, Information Technology, and Vulnerability
Digital Library Use
The contributors to this volume view digital libraries (DLs) from a social as well as technological perspective. They see DLs as sociotechnical systems, networks of technology, information artifacts, and people and practices interacting with the larger world of work and society. As Bruce Schatz observes in his foreword, for a digital to be useful, the users, the documents, and the information system must be in harmony.The contributors begin by as…
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…
Guidelines for the Display of Attribute Certainty
This research investigates how the inclusion of attribute certainty in map displays influences GIS modeling and spatial decision support. The goal is to establish empirical evidence documenting graphical guidelines that can be incorporated as GIS system defaults for mapping attribute certainty. Value, texture, and saturation appear as visual variables associated with the depiction of attribute certainty. These three variables, in addition to the …
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…
Treatment of the Cartographic Line
Traditionally, cartographic generalization has been considered in the context of eliminating map detail. In recent situations, however, details have been introduced to enhance the map message, as an aid in visual recognition. Enhancements are increasingly prevalent in displays of computer-generated lines, surfaces, and landscapes: some of the better known examples of this technique are fractal representations. The justification cited for this enh…
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…
Guidelines for the Display of Attribute Certainty
This research investigates how the inclusion of attribute certainty in map displays influences GIS modeling and spatial decision support. The goal is to establish empirical evidence documenting graphical guidelines that can be incorporated as GIS system defaults for mapping attribute certainty. Value, texture, and saturation appear as visual variables associated with the depiction of attribute certainty. These three variables, in addition to the …
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…
Automated thinning of road networks and road labels for multiscale design of The National Map of the United States
This paper reports on progress in generalization and selective feature removal for a subset of fundamental base map layers that enables competent mapping through scales ranging from 1:24,000 to 1:1,000,000. Thinning and partitioning methods are applied to road features and labels for The National Map of the United States. Roads are thinned adaptively using the ArcGIS Thin Road Network geoprocessing tool, which removes features by feature hierarch…
Validation of spatially allocated small area estimates for 1880 Census demography
This paper details the validation of a methodology which spatially allocates Census microdata to census tracts, based on known, aggregate tract population distributions. To protect confidentiality, public-use microdata contain no spatial identifiers other
Exploring the impact of dasymetric refinement on spatiotemporal small area estimates
Comparing demographic small area estimates across multiple time periods is hindered by boundary changes in census enumeration units. Areal interpolation can resolve temporal incompatibilities, but underlying assumptions of uniform population density within units is sometimes flawed and results in distorted estimates. Dasymetric modeling refines spatial precision by limiting areal interpolation to the most likely residential areas. Here, a systema…
Establishing relationships between parcel data and land cover for demographic small area estimation
Dasymetric and other small area estimation methods often use land-cover data in order to refine the spatial resolution of population data. The attribute tables of these land-cover data, however, are often related only weakly to population distribution. Recent studies have examined the use of parcel data, but parcel data are not available in all places. Thus, it becomes useful to identify the links between parcel data and land-cover data so that l…
Adapting Generalization Tools to Physiographic Diversity for the United States National Hydrography Dataset
This paper reports on generalization and data modeling to create reduced scale versions of the National Hydrographic Dataset (NHD) for dissemination through The National Map, the primary data delivery portal for USGS. Our approach distinguishes local differences in physiographic factors, to demonstrate that knowledge about varying terrain (mountainous, hilly or flat) and varying climate (dry or humid) can support decisions about algorithms, param…
An open source high-performance solution to extract surface water drainage networks from diverse terrain conditions
This paper describes a workflow for automating the extraction of elevation-derived stream lines using open source tools with parallel computing support and testing the effectiveness of procedures in various terrain conditions within the conterminous United States. Drainage networks are extracted from the US Geological Survey 1/3 arc-second 3D Elevation Program elevation data having a nominal cell size of 10 m. This research demonstrates the utili…
Hydrographic Generalization Tailored to Dry Mountainous Regions
A wide variety of climate and terrain conditions exist in the United States and optimal cartographic generalization techniques for one area of the country may not be suitable for another, particularly when working with surface hydrographic data. This paper presents generalization and data modeling to produce reduced scale versions of hydrographic data for a multi-resolution national data set, The National Map, of the United States Geological Surv…
Fuzzy Modeling of Geometric Textures for Identifying Archipelagos in Area-Patch Generalization
This paper describes a method to approach area-patch problems in model generalization using fuzzy set theory. The area-patch problem identifies polygons with the same semantics (feature code) but varying geometry and spatial distribution. Area-patch generalization can be understood as a pattern recognition problem with a variety of viable solutions, constrained by the purposes of the generalized output. The focus lies with identifying geometric t…
Framing Guidelines for Multi-Scale Map Design Using Databases at Multiple Resolutions
This paper extends European research on generating cartographic base maps at multiple scales from a single detailed database. Similar to the European work, we emphasize reference maps. In contrast to the Europeans' focus on data generalization, we emphasize changes to the map display, including symbol design or symbol modification. We also work from databases compiled at multiple resolutions rather than constructing all representations from a sin…
Terrorism, Information Technology, and Vulnerability
Treatment of the Cartographic Line
Traditionally, cartographic generalization has been considered in the context of eliminating map detail. In recent situations, however, details have been introduced to enhance the map message, as an aid in visual recognition. Enhancements are increasingly prevalent in displays of computer-generated lines, surfaces, and landscapes: some of the better known examples of this technique are fractal representations. The justification cited for this enh…
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…
Guidelines for the Display of Attribute Certainty
This research investigates how the inclusion of attribute certainty in map displays influences GIS modeling and spatial decision support. The goal is to establish empirical evidence documenting graphical guidelines that can be incorporated as GIS system defaults for mapping attribute certainty. Value, texture, and saturation appear as visual variables associated with the depiction of attribute certainty. These three variables, in addition to the …
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…
Digital Library Use
The contributors to this volume view digital libraries (DLs) from a social as well as technological perspective. They see DLs as sociotechnical systems, networks of technology, information artifacts, and people and practices interacting with the larger world of work and society. As Bruce Schatz observes in his foreword, for a digital to be useful, the users, the documents, and the information system must be in harmony.The contributors begin by as…
Terrorism, Information Technology, and Vulnerability
Framing Guidelines for Multi-Scale Map Design Using Databases at Multiple Resolutions
This paper extends European research on generating cartographic base maps at multiple scales from a single detailed database. Similar to the European work, we emphasize reference maps. In contrast to the Europeans' focus on data generalization, we emphasize changes to the map display, including symbol design or symbol modification. We also work from databases compiled at multiple resolutions rather than constructing all representations from a sin…
Hydrographic Generalization Tailored to Dry Mountainous Regions
A wide variety of climate and terrain conditions exist in the United States and optimal cartographic generalization techniques for one area of the country may not be suitable for another, particularly when working with surface hydrographic data. This paper presents generalization and data modeling to produce reduced scale versions of hydrographic data for a multi-resolution national data set, The National Map, of the United States Geological Surv…
Adapting Generalization Tools to Physiographic Diversity for the United States National Hydrography Dataset
This paper reports on generalization and data modeling to create reduced scale versions of the National Hydrographic Dataset (NHD) for dissemination through The National Map, the primary data delivery portal for USGS. Our approach distinguishes local differences in physiographic factors, to demonstrate that knowledge about varying terrain (mountainous, hilly or flat) and varying climate (dry or humid) can support decisions about algorithms, param…
Fuzzy Modeling of Geometric Textures for Identifying Archipelagos in Area-Patch Generalization
This paper describes a method to approach area-patch problems in model generalization using fuzzy set theory. The area-patch problem identifies polygons with the same semantics (feature code) but varying geometry and spatial distribution. Area-patch generalization can be understood as a pattern recognition problem with a variety of viable solutions, constrained by the purposes of the generalized output. The focus lies with identifying geometric t…
Automated thinning of road networks and road labels for multiscale design of The National Map of the United States
This paper reports on progress in generalization and selective feature removal for a subset of fundamental base map layers that enables competent mapping through scales ranging from 1:24,000 to 1:1,000,000. Thinning and partitioning methods are applied to road features and labels for The National Map of the United States. Roads are thinned adaptively using the ArcGIS Thin Road Network geoprocessing tool, which removes features by feature hierarch…
Establishing relationships between parcel data and land cover for demographic small area estimation
Dasymetric and other small area estimation methods often use land-cover data in order to refine the spatial resolution of population data. The attribute tables of these land-cover data, however, are often related only weakly to population distribution. Recent studies have examined the use of parcel data, but parcel data are not available in all places. Thus, it becomes useful to identify the links between parcel data and land-cover data so that l…
Validation of spatially allocated small area estimates for 1880 Census demography
This paper details the validation of a methodology which spatially allocates Census microdata to census tracts, based on known, aggregate tract population distributions. To protect confidentiality, public-use microdata contain no spatial identifiers other
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…
A rapid approach for automated comparison of independently derived stream networks
This paper presents an improved coefficient of line correspondence (CLC) metric for automatically assessing the similarity of two different sets of linear features. Elevation-derived channels at 1:24,000 scale (24K) are generated from a weighted flow-accumulation model and compared to 24K National Hydrography Dataset (NHD) flowlines. The CLC process conflates two vector datasets through a raster line-density differencing approach that is faster a…
Exploring the impact of dasymetric refinement on spatiotemporal small area estimates
Comparing demographic small area estimates across multiple time periods is hindered by boundary changes in census enumeration units. Areal interpolation can resolve temporal incompatibilities, but underlying assumptions of uniform population density within units is sometimes flawed and results in distorted estimates. Dasymetric modeling refines spatial precision by limiting areal interpolation to the most likely residential areas. Here, a systema…
An evaluation of unsupervised and supervised learning algorithms for clustering landscape types in the United States
Knowledge of landscape type can inform cartographic generalization of hydrographic features, because landscape characteristics provide an important geographic context that affects variation in channel geometry, flow pattern, and network configuration. Landscape types are characterized by expansive spatial gradients, lacking abrupt changes between adjacent classes; and as having a limited number of outliers that might confound classification. The …
An open source high-performance solution to extract surface water drainage networks from diverse terrain conditions
This paper describes a workflow for automating the extraction of elevation-derived stream lines using open source tools with parallel computing support and testing the effectiveness of procedures in various terrain conditions within the conterminous United States. Drainage networks are extracted from the US Geological Survey 1/3 arc-second 3D Elevation Program elevation data having a nominal cell size of 10 m. This research demonstrates the utili…
Deriving Small Area Mortality Estimates Using a Probabilistic Reweighting Method
Small area health estimates are important for studying environmental exposure, disease transmission, and health outcomes at the local scale. Yet, to protect privacy, the majority of publicly available health data are aggregated within larger spatial units such as states or counties. This article describes a method to generate small area mortality estimates from individual microdata that are available only for larger geographic entities. The morta…
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…
Analyzing multi-scale spatial point patterns in a pyramid modeling framework
Many spatial analysis methods suffer from the scaling issue identified as part of the Modifiable Areal Unit Problem (MAUP). This article introduces the Pyramid Model (PM), a hierarchical data framework integrating space and spatial scale in a 3D environment to support multi-scale analysis. The utility of the PM is tested in examining quadrat density and kernel density, which are commonly used measures of point patterns. The two metrics computed f…
Wetland Classification, Attribute Accuracy, and Scale
Quantification of all types of uncertainty helps to establish reliability in any analysis. This research focuses on uncertainty in two attribute levels of wetland classification and creates visualization tools to guide analysis of spatial uncertainty patterns over several scales. A novel variant of confusion matrix analysis compares the Cowardin and Hydrogeomorphic wetland classification systems, identifying areas and types of misclassification f…
Computer Science (22 works) · Geography (21 works) · Cartography (18 works) · Mathematics (15 works) · Data mining (13 works) · Geographic Information Systems Studies (11 works) · Artificial Intelligence (10 works) · Remote sensing (9 works) · Cartographic generalization (7 works) · Data Management and Algorithms (7 works)