N Xiao
Datos Biográficos
| ID | 5419 |
|---|---|
| NOMBRE | N Xiao |
| NOMBRES | N |
| APELLIDO | Xiao |
| FIRMA | XIAO N |
| AFILIACIONES | The Ohio State University |
| ORCID | 0000-0002-6585-6294 |
| VERIFICADO | Sí |
| TOTAL DE OBRAS | 24 |
| TOTAL DE CITAS | 49 |
| TOTAL COMO AUTOR | 24 |
| TOTAL COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 2002 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 2025 |
| ÍNDICE H | 4 |
Where Is Central Ohio? Many-Valued Logic Approaches to Understanding and Measuring Vague Geographic Regions
Geographic regions are often vague or uncertain because they do not have clearly defined boundaries. The region referred to as Central Ohio, for example, is commonly recognized and referred to by people in the area around Columbus, Ohio. For places that are near Columbus, however, people are often indeterminate about whether they are in or out of the region. This article discusses the use of a suite of formal approaches known as many-valued logic…
Inclusive accessibility
Exploring the Tradeoff Between Privacy and Utility of Complete‐count Census Data Using a Multiobjective Optimization Approach
Privacy and utility are two important objectives to consider when releasing census data. However, these two objectives are often conflicting, as protecting privacy usually necessitates introducing noise into the data, which compromises data utility. Determining the appropriate level of privacy protection presents a significant challenge in the data release. Therefore, it is necessary to investigate the tradeoff between privacy and utility before …
Generating Small Areal Synthetic Microdata from Public Aggregated Data Using an Optimization Method
Small area microdata contain attributes and locations of individual members of a population in small census geographies. This type of data is critical in research and policymaking, but it is often not publicly available due to confidentiality concerns. The limited access to small area microdata can result in insufficient data for certain research (data scarcity). Even for researchers qualified to access the small area microdata, their research ca…
Visualizing economic drivers of virtual land trade
Exploring virtual land trade (VLT) embodied in the global agricultural trade enables us to uncover potential risks to economy, environment, and food security within the trade structure. Using the bilateral trade data for the periods of 1988–1990, 1998–2000, 2008–2010, and 2018–2020, we created halfcircle diagrams depicting how virtual land of cereals is traded between countries of different income levels. The diagrams show that the global trend o…
Assessing the Impact of Differential Privacy on Population Uniques in Geographically Aggregated Data
A Computational Framework for Preserving Privacy and Maintaining Utility of Geographically Aggregated Data
Geographically aggregated data are often considered to be safe because information can be published by group as population counts rather than by individual. Identifiable information about individuals can still be disclosed when using such data, however. Conventional methods for protecting privacy, such as data swapping, often lack transparency because they do not quantify the reduction in disclosure risk. Recent methods, such as those based on di…
Computational Cartographic Recognition
Map reading is a challenging task for computer programs. This article explores how artificial intelligence and machine learning methods can be used to understand maps, an area we broadly refer to as computational cartographic recognition. Specifically, we use machine learning methods to (1) identify whether an image is a map, (2) recognize the geographic region on the map, and (3) recognize the projection used on the map. Four machine learning mo…
Retrospective Deconstruction of Statistical Maps
The process of creating printed statistical maps in the predigital era was expensive and time consuming. These and other interacting factors constrained the number of design alternatives, such as color choices, that a cartographer might reasonably have been able to consider. In this article, we develop an approach to map deconstruction that enables researchers to investigate the statistical choices made by cartographers by placing each printed ma…
Machine Learning
Machine learning is a research field in artificial intelligence and statistics that an aims to develop computational methods that can be used to learn from data and to predict with new data. Many machine learning methods, such as decision trees and support vector machine, have been developed. In geography, machine learning methods are used in areas such as remote sensing, cartography, spatial analysis and modeling, spatial decision‐making, and ge…
Simulating the Transmission of Foot-And-Mouth Disease Among Mobile Herds in the Far North Region, Cameroon
Animal and human movements can impact the transmission of infectious diseases. Modeling such impacts presents a significant challenge to disease transmission models because these models o en assume a fully mixing population where individuals have an equal chance to contact each other. Whereas movements result in populations that can be best represented as a dynamic networks whose structure changes over time as individual movements result in chang…
Social-ecological feedbacks lead to unsustainable lock-in in an inland fishery
Herding Contracts and Pastoral Mobility in the Far North Region of Cameroon
Towards a Multiobjective View of Cartographic Design
Cartographers must make numerous decisions during the process of constructing a map. In the present era, when spatial data sets are abundant and mapping software is accessible to the general public, cartographic knowledge developed in the literature is under-used and threatened with irrelevance. We view cartographic design as a multiobjective problem solving process that must meet many, often conflicting, goals. The application of this multiobjec…
Mapping the Census
An Integrated Approach to Modeling Grazing Pressure in Pastoral Systems
Visualizing Migration Flows Using Kriskograms
This paper describes a new approach called kriskogram to visualizing migration flows. To create a kriskogram, geographical units are projected as a set of points on a straight line segment called a location line. The migration flow between two points on the location line is represented using a half-circle drawn from the origin to the destination in a clockwise direction. Translucent symbols and a classification scheme can be used to make a krisko…
Heuristics in Spatial Analysis
Many government agencies and corporations face locational decisions, such as where to locate fire stations, postal facilities, nature reserves, computer centers, bank branches, and so on. To reach such location-related decisions, geographical information systems (GIS) are essential for providing access to spatial data and analysis tools. Moreover, geographic insights can be gained from GIS as they enable capabilities for better reflecting problem…
Examining the tradeoff between residential broadband service coverage and network connectivity using a bi‐objective facility location model
A Unified Conceptual Framework for Geographical Optimization Using Evolutionary Algorithms
During the last two decades, evolutionary algorithms (EAs) have been applied to a wide range of optimization and decision-making problems. Work on EAs for geographical analysis, however, has been conducted in a problem-specific manner, which prevents an EA designed for one type of problem from being used on others. In this article, a formal, conceptual framework is developed to unify the design and implementation of EAs for many geographical opti…
Supporting the Comparison of Choropleth Maps Using an Evolutionary Algorithm
Choropleth maps can be used to compare the patterns exhibited by different spatial variables. In this paper, we develop an evolutionary algorithm that can be used to generate classifications that allow a user to explore the spatial patterns of multiple choropleth maps in terms of their visual correlation and the equality of area contained in each class. Synthetic and census data are used to demonstrate the effectiveness of our approach
Exploring the Geographic Consequences of Public Policies Using Evolutionary Algorithms
Public policies with geographical consequences are often difficult to analyze because they affect multiple stakeholders with competing objectives. While such problems fall conceptually into the domain of multiobjective evaluation, associated analytical techniques often search for a single optimum solution. Within the context of geographical problems, optimality often means different things to different stakeholders and, thus, an optimum optimorum…
Using Genetic Algorithms to Create Multicriteria Class Intervals for Choropleth Maps
During the past three decades a large body of research has investigated the problem of specifying class intervals for choropleth maps. This work, however, has focused almost exclusively on placing observations in quasi-continuous data distributions into ordinal bins along the number line. All enumeration units that fall into each bin are then assigned an areal symbol that is used to create the choropleth map. The geographical characteristics of t…
Using Evolutionary Algorithms to Generate Alternatives for Multiobjective Site-Search Problems
Multiobjective site-search problems are a class of decision problems that have geographical components and multiple, often conflicting, objectives; this kind of problem is often encountered and is technically difficult to solve. In this paper we describe an evolutionary algorithm (EA) based approach that can be used to address such problems. We first describe the general design of EAs that can be used to generate alternatives that are optimal or …
An Integrated Approach to Modeling Grazing Pressure in Pastoral Systems
Using Genetic Algorithms to Create Multicriteria Class Intervals for Choropleth Maps
During the past three decades a large body of research has investigated the problem of specifying class intervals for choropleth maps. This work, however, has focused almost exclusively on placing observations in quasi-continuous data distributions into ordinal bins along the number line. All enumeration units that fall into each bin are then assigned an areal symbol that is used to create the choropleth map. The geographical characteristics of t…
Heuristics in Spatial Analysis
Many government agencies and corporations face locational decisions, such as where to locate fire stations, postal facilities, nature reserves, computer centers, bank branches, and so on. To reach such location-related decisions, geographical information systems (GIS) are essential for providing access to spatial data and analysis tools. Moreover, geographic insights can be gained from GIS as they enable capabilities for better reflecting problem…
Using Evolutionary Algorithms to Generate Alternatives for Multiobjective Site-Search Problems
Multiobjective site-search problems are a class of decision problems that have geographical components and multiple, often conflicting, objectives; this kind of problem is often encountered and is technically difficult to solve. In this paper we describe an evolutionary algorithm (EA) based approach that can be used to address such problems. We first describe the general design of EAs that can be used to generate alternatives that are optimal or …
Social-ecological feedbacks lead to unsustainable lock-in in an inland fishery
Herding Contracts and Pastoral Mobility in the Far North Region of Cameroon
Towards a Multiobjective View of Cartographic Design
Cartographers must make numerous decisions during the process of constructing a map. In the present era, when spatial data sets are abundant and mapping software is accessible to the general public, cartographic knowledge developed in the literature is under-used and threatened with irrelevance. We view cartographic design as a multiobjective problem solving process that must meet many, often conflicting, goals. The application of this multiobjec…
Visualizing Migration Flows Using Kriskograms
This paper describes a new approach called kriskogram to visualizing migration flows. To create a kriskogram, geographical units are projected as a set of points on a straight line segment called a location line. The migration flow between two points on the location line is represented using a half-circle drawn from the origin to the destination in a clockwise direction. Translucent symbols and a classification scheme can be used to make a krisko…
A Unified Conceptual Framework for Geographical Optimization Using Evolutionary Algorithms
During the last two decades, evolutionary algorithms (EAs) have been applied to a wide range of optimization and decision-making problems. Work on EAs for geographical analysis, however, has been conducted in a problem-specific manner, which prevents an EA designed for one type of problem from being used on others. In this article, a formal, conceptual framework is developed to unify the design and implementation of EAs for many geographical opti…
Supporting the Comparison of Choropleth Maps Using an Evolutionary Algorithm
Choropleth maps can be used to compare the patterns exhibited by different spatial variables. In this paper, we develop an evolutionary algorithm that can be used to generate classifications that allow a user to explore the spatial patterns of multiple choropleth maps in terms of their visual correlation and the equality of area contained in each class. Synthetic and census data are used to demonstrate the effectiveness of our approach
Exploring the Geographic Consequences of Public Policies Using Evolutionary Algorithms
Public policies with geographical consequences are often difficult to analyze because they affect multiple stakeholders with competing objectives. While such problems fall conceptually into the domain of multiobjective evaluation, associated analytical techniques often search for a single optimum solution. Within the context of geographical problems, optimality often means different things to different stakeholders and, thus, an optimum optimorum…
A Computational Framework for Preserving Privacy and Maintaining Utility of Geographically Aggregated Data
Geographically aggregated data are often considered to be safe because information can be published by group as population counts rather than by individual. Identifiable information about individuals can still be disclosed when using such data, however. Conventional methods for protecting privacy, such as data swapping, often lack transparency because they do not quantify the reduction in disclosure risk. Recent methods, such as those based on di…
Using Evolutionary Algorithms to Generate Alternatives for Multiobjective Site-Search Problems
Multiobjective site-search problems are a class of decision problems that have geographical components and multiple, often conflicting, objectives; this kind of problem is often encountered and is technically difficult to solve. In this paper we describe an evolutionary algorithm (EA) based approach that can be used to address such problems. We first describe the general design of EAs that can be used to generate alternatives that are optimal or …
Using Genetic Algorithms to Create Multicriteria Class Intervals for Choropleth Maps
During the past three decades a large body of research has investigated the problem of specifying class intervals for choropleth maps. This work, however, has focused almost exclusively on placing observations in quasi-continuous data distributions into ordinal bins along the number line. All enumeration units that fall into each bin are then assigned an areal symbol that is used to create the choropleth map. The geographical characteristics of t…
Exploring the Geographic Consequences of Public Policies Using Evolutionary Algorithms
Public policies with geographical consequences are often difficult to analyze because they affect multiple stakeholders with competing objectives. While such problems fall conceptually into the domain of multiobjective evaluation, associated analytical techniques often search for a single optimum solution. Within the context of geographical problems, optimality often means different things to different stakeholders and, thus, an optimum optimorum…
Supporting the Comparison of Choropleth Maps Using an Evolutionary Algorithm
Choropleth maps can be used to compare the patterns exhibited by different spatial variables. In this paper, we develop an evolutionary algorithm that can be used to generate classifications that allow a user to explore the spatial patterns of multiple choropleth maps in terms of their visual correlation and the equality of area contained in each class. Synthetic and census data are used to demonstrate the effectiveness of our approach
Examining the tradeoff between residential broadband service coverage and network connectivity using a bi‐objective facility location model
A Unified Conceptual Framework for Geographical Optimization Using Evolutionary Algorithms
During the last two decades, evolutionary algorithms (EAs) have been applied to a wide range of optimization and decision-making problems. Work on EAs for geographical analysis, however, has been conducted in a problem-specific manner, which prevents an EA designed for one type of problem from being used on others. In this article, a formal, conceptual framework is developed to unify the design and implementation of EAs for many geographical opti…
Visualizing Migration Flows Using Kriskograms
This paper describes a new approach called kriskogram to visualizing migration flows. To create a kriskogram, geographical units are projected as a set of points on a straight line segment called a location line. The migration flow between two points on the location line is represented using a half-circle drawn from the origin to the destination in a clockwise direction. Translucent symbols and a classification scheme can be used to make a krisko…
Heuristics in Spatial Analysis
Many government agencies and corporations face locational decisions, such as where to locate fire stations, postal facilities, nature reserves, computer centers, bank branches, and so on. To reach such location-related decisions, geographical information systems (GIS) are essential for providing access to spatial data and analysis tools. Moreover, geographic insights can be gained from GIS as they enable capabilities for better reflecting problem…
Mapping the Census
An Integrated Approach to Modeling Grazing Pressure in Pastoral Systems
Towards a Multiobjective View of Cartographic Design
Cartographers must make numerous decisions during the process of constructing a map. In the present era, when spatial data sets are abundant and mapping software is accessible to the general public, cartographic knowledge developed in the literature is under-used and threatened with irrelevance. We view cartographic design as a multiobjective problem solving process that must meet many, often conflicting, goals. The application of this multiobjec…
Herding Contracts and Pastoral Mobility in the Far North Region of Cameroon
Simulating the Transmission of Foot-And-Mouth Disease Among Mobile Herds in the Far North Region, Cameroon
Animal and human movements can impact the transmission of infectious diseases. Modeling such impacts presents a significant challenge to disease transmission models because these models o en assume a fully mixing population where individuals have an equal chance to contact each other. Whereas movements result in populations that can be best represented as a dynamic networks whose structure changes over time as individual movements result in chang…
Social-ecological feedbacks lead to unsustainable lock-in in an inland fishery
Machine Learning
Machine learning is a research field in artificial intelligence and statistics that an aims to develop computational methods that can be used to learn from data and to predict with new data. Many machine learning methods, such as decision trees and support vector machine, have been developed. In geography, machine learning methods are used in areas such as remote sensing, cartography, spatial analysis and modeling, spatial decision‐making, and ge…
Retrospective Deconstruction of Statistical Maps
The process of creating printed statistical maps in the predigital era was expensive and time consuming. These and other interacting factors constrained the number of design alternatives, such as color choices, that a cartographer might reasonably have been able to consider. In this article, we develop an approach to map deconstruction that enables researchers to investigate the statistical choices made by cartographers by placing each printed ma…
Generating Small Areal Synthetic Microdata from Public Aggregated Data Using an Optimization Method
Small area microdata contain attributes and locations of individual members of a population in small census geographies. This type of data is critical in research and policymaking, but it is often not publicly available due to confidentiality concerns. The limited access to small area microdata can result in insufficient data for certain research (data scarcity). Even for researchers qualified to access the small area microdata, their research ca…
Visualizing economic drivers of virtual land trade
Exploring virtual land trade (VLT) embodied in the global agricultural trade enables us to uncover potential risks to economy, environment, and food security within the trade structure. Using the bilateral trade data for the periods of 1988–1990, 1998–2000, 2008–2010, and 2018–2020, we created halfcircle diagrams depicting how virtual land of cereals is traded between countries of different income levels. The diagrams show that the global trend o…
Assessing the Impact of Differential Privacy on Population Uniques in Geographically Aggregated Data
A Computational Framework for Preserving Privacy and Maintaining Utility of Geographically Aggregated Data
Geographically aggregated data are often considered to be safe because information can be published by group as population counts rather than by individual. Identifiable information about individuals can still be disclosed when using such data, however. Conventional methods for protecting privacy, such as data swapping, often lack transparency because they do not quantify the reduction in disclosure risk. Recent methods, such as those based on di…
Computational Cartographic Recognition
Map reading is a challenging task for computer programs. This article explores how artificial intelligence and machine learning methods can be used to understand maps, an area we broadly refer to as computational cartographic recognition. Specifically, we use machine learning methods to (1) identify whether an image is a map, (2) recognize the geographic region on the map, and (3) recognize the projection used on the map. Four machine learning mo…
Inclusive accessibility
Exploring the Tradeoff Between Privacy and Utility of Complete‐count Census Data Using a Multiobjective Optimization Approach
Privacy and utility are two important objectives to consider when releasing census data. However, these two objectives are often conflicting, as protecting privacy usually necessitates introducing noise into the data, which compromises data utility. Determining the appropriate level of privacy protection presents a significant challenge in the data release. Therefore, it is necessary to investigate the tradeoff between privacy and utility before …
Where Is Central Ohio? Many-Valued Logic Approaches to Understanding and Measuring Vague Geographic Regions
Geographic regions are often vague or uncertain because they do not have clearly defined boundaries. The region referred to as Central Ohio, for example, is commonly recognized and referred to by people in the area around Columbus, Ohio. For places that are near Columbus, however, people are often indeterminate about whether they are in or out of the region. This article discusses the use of a suite of formal approaches known as many-valued logic…
Geography (20 obras) · Computer Science (19 obras) · Mathematics (11 obras) · Artificial Intelligence (9 obras) · Cartography (8 obras) · Data mining (7 obras) · Geographic Information Systems Studies (6 obras) · Artificial Intelligence (5 obras) · Data science (5 obras) · Economics (5 obras)