Nina S N Lam
Dados Biográficos
| ID | 1004858 |
|---|---|
| NOME | Nina S N Lam |
| PRENOMES | Nina S N |
| SOBRENOME | Lam |
| ASSINATURA | LAM N S N |
| AFILIAÇÕES | Louisiana State University |
| ORCID | 0000-0002-5344-9368 |
| VERIFICADO | Sim |
| TOTAL DE OBRAS | 26 |
| TOTAL DE CITAÇÕES | 59 |
| TOTAL COMO AUTOR | 26 |
| TOTAL COMO EDITOR | 0 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 1983 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 2026 |
| ÍNDICE H | 5 |
Assessing community resilience to hurricanes in the Guangdong–Hong Kong–Macao Greater Bay Area, China from 2013 to 2023
Hurricanes, one of the most devastating natural phenomena in coastal regions, pose significant risks to infrastructure, environment, and human lives. Understanding and monitoring the resilience capacity to the hurricane hazard are crucial for building an adaptable and sustainable society. This study employed the Resilience Inference Measurement (RIM) model to assess the community resilience level at the township level in the southern China mega-c…
Mining socioenvironmental drivers of bias in social media rescue data for fairness-aware modeling
Prime
Social media for emergency rescue
A Machine Learning Approach for Detecting Rescue Requests from Social Media
Hurricane Harvey in 2017 marked an important transition where many disaster victims used social media rather than the overloaded 911 system to seek rescue. This article presents a machine-learning-based detector of rescue requests from Harvey-related Twitter messages, which differentiates itself from existing ones by accounting for the potential impacts of ZIP codes on both the preparation of training samples and the performance of different mach…
Twitter Use in Hurricane Isaac and Its Implications for Disaster Resilience
Disaster resilience is the capacity of a community to “bounce back” from disastrous events. Most studies rely on traditional data such as census data to study community resilience. With increasing use of social media, new data sources such as Twitter could be utilized to monitor human response during different phases of disasters to better understand resilience. An important research question is: Does Twitter use correlate with disaster resilienc…
Economics over Risk
We analyzed the migration consideration factors of residents from the Mississippi River Delta in southern Louisiana, which is under the influence of rising sea levels, subsiding land, and increasing flood risks. Through the use of a telephone survey of 1,125 adult individuals in twenty-four parishes, we gathered the demographic data and flood risk experiences and perceptions of each respondent. The data were analyzed through descriptive statistic…
Modeling the dynamics of drought resilience in South-Central United States using a Bayesian Network
Extending Getis–Ord Statistics to Account for Local Space–Time Autocorrelation in Spatial Panel Data
Space and time are both crucial characteristic dimensions of geographic events and phenomena. Although exploratory spatial data analysis (ESDA) can be used to visualize and summarize complex spatial patterns, it has limitations in capturing the temporal dynamics of geographic features. Efforts have been made to incorporate the time dimension into ESDA techniques to detect space–time clustering or trends. Localized space–time statistics that could…
A synthesis of disaster resilience measurement methods and indices
Geographically Weighted Elastic Net
This study develops a linear regression model to select local, low-collinear explanatory variables. This model combines two well-known models: geographically weighted regression (GWR) and elastic net (EN). The GWR model posits that the regression coefficients vary as a function of location and focuses on solving the problem of explaining the relationships under the spatially nonstationary condition, which a global model cannot solve. GWR cannot f…
Community Resilience to Drought Hazard in the South-Central United States
Drought is a hazard that inflicts costly damage to agricultural, hydrologic, and ecological systems and affects human health and prosperity. A comprehensive assessment of resilience to the drought hazard in various communities and an identification of the main variables that affect resilience is crucial to coping with the hazard and promoting resilience. This study assessed the community resilience to drought hazards of all 503 counties of Arkans…
Modeling the Dynamics of Community Resilience to Coastal Hazards Using a Bayesian Network
Studies on how variables of community resilience to natural hazards interact as a system that affects the final resilience (i.e., their dynamical linkages) have rarely been conducted. Bayesian network (BN), which represents the interdependencies among variables in a graph while expressing the uncertainty in the form of probability distributions, offers an effective way to investigate the interactions among different resilience components and addr…
Mining Twitter Data for Improved Understanding of Disaster Resilience
Coastal communities faced with multiple hazards have shown uneven responses and behaviors. These responses and behaviors could be better understood by analyzing real-time social media data through categorizing them into the three phases of the emergency management: preparedness, response, and recovery. This study analyzes the spatial–temporal patterns of Twitter activities during Hurricane Sandy, which struck the U.S. Northeast on 29 October 2012…
Fractal Analysis
Since Mandelbrot developed fractal geometry in the 1970s to overcome the difficulty in describing complex forms, applications of the fractal model have been numerous and diverse. Fractal applications in geography fall into two groups. The first group uses the fractal simulation model to generate real‐world‐like curves and surfaces for testing geographical models and algorithms. The second group of application uses the fractal dimension as an aid …
Interpolation
Areal interpolation refers to the problem of transforming one set of areal data (source zones) to another (target zones), where their boundaries do not coincide. It is increasingly an indispensable technology for integrating disparate spatial data for modeling and analysis. Areal interpolation methods that have the volume‐preserving (pycnophylactic) property are far more accurate than those that do not have such property. With ancillary data such…
Changes in Exposure to Flood Hazards in the United States
This article conducts a national, county-based assessment of the changes in population and urban areas in high-risk flood zones from 2001 to 2011 in the contiguous United States. The U.S. Federal Emergency Management Agency's (FEMA) 100-year flood maps, land cover data, and census data were used to extract the proportion of developed (urban) land in flood zones by county at the two time points, and indexes of difference were calculated. Local Mor…
Co-evolution of wetland landscapes, flooding, and human settlement in the Mississippi River Delta Plain
River deltas all over the world are sinking beneath sea-level rise, causing significant threats to natural and social systems. This is due to the combined effects of anthropogenic changes to sediment supply and river flow, subsidence, and sea-level rise, posing an immediate threat to the 500-1,000 million residents, many in megacities that live on deltaic coasts. The Mississippi River Deltaic Plain (MRDP) provides examples for many of the functio…
A cyberinfrastructure for community resilience assessment and visualization
Disaster resilience is a major societal challenge. Cartography and GIS can contribute substantially to this research area. This paper describes a cyberinfrastructure for disaster resilience assessment and visualization for all counties in the United States. Aided by the Application Programming Interface-enabled web mapping and component-oriented web tools, the cyberinfrastructure is designed to better serve the US communities with comprehensive r…
Mapping and assessing coastal resilience in the Caribbean region
Assessing the vulnerability and resilience to coastal hazards is a critical worldwide issue, especially for hurricane-prone coastal regions such as the Caribbean. However, the development of a useful metric for vulnerability and resilience assessment has a lot of challenges. Cartography and GIS analysis can contribute effectively to the solution of the issue by integrating natural and human data layers for assessment, mapping, and visualization. …
Applications of integrated geophysical method in archaeological surveys of the ancient Shu ruins
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. …
A new method for estimating carbon dioxide emissions from transportation at fine spatial scales
Detailed estimates of carbon dioxide (CO 2 ) emissions at fine spatial scales are useful to both modelers and decision makers who are faced with the problem of global warming and climate change. Globally, transport related emissions of carbon dioxide are growing. This letter presents a new method based on the volume-preserving principle in the areal interpolation literature to disaggregate transportation-related CO 2 emission estimates from the c…
Geographic Information Systems and Science
Key Words: geographic information sciencegeographic information systems Additional informationNotes on contributorsNina LamReviewed by
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…
Mining Twitter Data for Improved Understanding of Disaster Resilience
Coastal communities faced with multiple hazards have shown uneven responses and behaviors. These responses and behaviors could be better understood by analyzing real-time social media data through categorizing them into the three phases of the emergency management: preparedness, response, and recovery. This study analyzes the spatial–temporal patterns of Twitter activities during Hurricane Sandy, which struck the U.S. Northeast on 29 October 2012…
Mapping and assessing coastal resilience in the Caribbean region
Assessing the vulnerability and resilience to coastal hazards is a critical worldwide issue, especially for hurricane-prone coastal regions such as the Caribbean. However, the development of a useful metric for vulnerability and resilience assessment has a lot of challenges. Cartography and GIS analysis can contribute effectively to the solution of the issue by integrating natural and human data layers for assessment, mapping, and visualization. …
Co-evolution of wetland landscapes, flooding, and human settlement in the Mississippi River Delta Plain
River deltas all over the world are sinking beneath sea-level rise, causing significant threats to natural and social systems. This is due to the combined effects of anthropogenic changes to sediment supply and river flow, subsidence, and sea-level rise, posing an immediate threat to the 500-1,000 million residents, many in megacities that live on deltaic coasts. The Mississippi River Deltaic Plain (MRDP) provides examples for many of the functio…
Applications of integrated geophysical method in archaeological surveys of the ancient Shu ruins
Changes in Exposure to Flood Hazards in the United States
This article conducts a national, county-based assessment of the changes in population and urban areas in high-risk flood zones from 2001 to 2011 in the contiguous United States. The U.S. Federal Emergency Management Agency's (FEMA) 100-year flood maps, land cover data, and census data were used to extract the proportion of developed (urban) land in flood zones by county at the two time points, and indexes of difference were calculated. Local Mor…
Geographically Weighted Elastic Net
This study develops a linear regression model to select local, low-collinear explanatory variables. This model combines two well-known models: geographically weighted regression (GWR) and elastic net (EN). The GWR model posits that the regression coefficients vary as a function of location and focuses on solving the problem of explaining the relationships under the spatially nonstationary condition, which a global model cannot solve. GWR cannot f…
Modeling the Dynamics of Community Resilience to Coastal Hazards Using a Bayesian Network
Studies on how variables of community resilience to natural hazards interact as a system that affects the final resilience (i.e., their dynamical linkages) have rarely been conducted. Bayesian network (BN), which represents the interdependencies among variables in a graph while expressing the uncertainty in the form of probability distributions, offers an effective way to investigate the interactions among different resilience components and addr…
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…
Community Resilience to Drought Hazard in the South-Central United States
Drought is a hazard that inflicts costly damage to agricultural, hydrologic, and ecological systems and affects human health and prosperity. A comprehensive assessment of resilience to the drought hazard in various communities and an identification of the main variables that affect resilience is crucial to coping with the hazard and promoting resilience. This study assessed the community resilience to drought hazards of all 503 counties of Arkans…
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. …
A cyberinfrastructure for community resilience assessment and visualization
Disaster resilience is a major societal challenge. Cartography and GIS can contribute substantially to this research area. This paper describes a cyberinfrastructure for disaster resilience assessment and visualization for all counties in the United States. Aided by the Application Programming Interface-enabled web mapping and component-oriented web tools, the cyberinfrastructure is designed to better serve the US communities with comprehensive r…
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…
Geographic Information Systems and Science
Key Words: geographic information sciencegeographic information systems Additional informationNotes on contributorsNina LamReviewed by
A new method for estimating carbon dioxide emissions from transportation at fine spatial scales
Detailed estimates of carbon dioxide (CO 2 ) emissions at fine spatial scales are useful to both modelers and decision makers who are faced with the problem of global warming and climate change. Globally, transport related emissions of carbon dioxide are growing. This letter presents a new method based on the volume-preserving principle in the areal interpolation literature to disaggregate transportation-related CO 2 emission estimates from the c…
Applications of integrated geophysical method in archaeological surveys of the ancient Shu ruins
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. …
A cyberinfrastructure for community resilience assessment and visualization
Disaster resilience is a major societal challenge. Cartography and GIS can contribute substantially to this research area. This paper describes a cyberinfrastructure for disaster resilience assessment and visualization for all counties in the United States. Aided by the Application Programming Interface-enabled web mapping and component-oriented web tools, the cyberinfrastructure is designed to better serve the US communities with comprehensive r…
Mapping and assessing coastal resilience in the Caribbean region
Assessing the vulnerability and resilience to coastal hazards is a critical worldwide issue, especially for hurricane-prone coastal regions such as the Caribbean. However, the development of a useful metric for vulnerability and resilience assessment has a lot of challenges. Cartography and GIS analysis can contribute effectively to the solution of the issue by integrating natural and human data layers for assessment, mapping, and visualization. …
Co-evolution of wetland landscapes, flooding, and human settlement in the Mississippi River Delta Plain
River deltas all over the world are sinking beneath sea-level rise, causing significant threats to natural and social systems. This is due to the combined effects of anthropogenic changes to sediment supply and river flow, subsidence, and sea-level rise, posing an immediate threat to the 500-1,000 million residents, many in megacities that live on deltaic coasts. The Mississippi River Deltaic Plain (MRDP) provides examples for many of the functio…
Fractal Analysis
Since Mandelbrot developed fractal geometry in the 1970s to overcome the difficulty in describing complex forms, applications of the fractal model have been numerous and diverse. Fractal applications in geography fall into two groups. The first group uses the fractal simulation model to generate real‐world‐like curves and surfaces for testing geographical models and algorithms. The second group of application uses the fractal dimension as an aid …
Interpolation
Areal interpolation refers to the problem of transforming one set of areal data (source zones) to another (target zones), where their boundaries do not coincide. It is increasingly an indispensable technology for integrating disparate spatial data for modeling and analysis. Areal interpolation methods that have the volume‐preserving (pycnophylactic) property are far more accurate than those that do not have such property. With ancillary data such…
Changes in Exposure to Flood Hazards in the United States
This article conducts a national, county-based assessment of the changes in population and urban areas in high-risk flood zones from 2001 to 2011 in the contiguous United States. The U.S. Federal Emergency Management Agency's (FEMA) 100-year flood maps, land cover data, and census data were used to extract the proportion of developed (urban) land in flood zones by county at the two time points, and indexes of difference were calculated. Local Mor…
A synthesis of disaster resilience measurement methods and indices
Geographically Weighted Elastic Net
This study develops a linear regression model to select local, low-collinear explanatory variables. This model combines two well-known models: geographically weighted regression (GWR) and elastic net (EN). The GWR model posits that the regression coefficients vary as a function of location and focuses on solving the problem of explaining the relationships under the spatially nonstationary condition, which a global model cannot solve. GWR cannot f…
Community Resilience to Drought Hazard in the South-Central United States
Drought is a hazard that inflicts costly damage to agricultural, hydrologic, and ecological systems and affects human health and prosperity. A comprehensive assessment of resilience to the drought hazard in various communities and an identification of the main variables that affect resilience is crucial to coping with the hazard and promoting resilience. This study assessed the community resilience to drought hazards of all 503 counties of Arkans…
Modeling the Dynamics of Community Resilience to Coastal Hazards Using a Bayesian Network
Studies on how variables of community resilience to natural hazards interact as a system that affects the final resilience (i.e., their dynamical linkages) have rarely been conducted. Bayesian network (BN), which represents the interdependencies among variables in a graph while expressing the uncertainty in the form of probability distributions, offers an effective way to investigate the interactions among different resilience components and addr…
Mining Twitter Data for Improved Understanding of Disaster Resilience
Coastal communities faced with multiple hazards have shown uneven responses and behaviors. These responses and behaviors could be better understood by analyzing real-time social media data through categorizing them into the three phases of the emergency management: preparedness, response, and recovery. This study analyzes the spatial–temporal patterns of Twitter activities during Hurricane Sandy, which struck the U.S. Northeast on 29 October 2012…
Modeling the dynamics of drought resilience in South-Central United States using a Bayesian Network
Extending Getis–Ord Statistics to Account for Local Space–Time Autocorrelation in Spatial Panel Data
Space and time are both crucial characteristic dimensions of geographic events and phenomena. Although exploratory spatial data analysis (ESDA) can be used to visualize and summarize complex spatial patterns, it has limitations in capturing the temporal dynamics of geographic features. Efforts have been made to incorporate the time dimension into ESDA techniques to detect space–time clustering or trends. Localized space–time statistics that could…
Twitter Use in Hurricane Isaac and Its Implications for Disaster Resilience
Disaster resilience is the capacity of a community to “bounce back” from disastrous events. Most studies rely on traditional data such as census data to study community resilience. With increasing use of social media, new data sources such as Twitter could be utilized to monitor human response during different phases of disasters to better understand resilience. An important research question is: Does Twitter use correlate with disaster resilienc…
Economics over Risk
We analyzed the migration consideration factors of residents from the Mississippi River Delta in southern Louisiana, which is under the influence of rising sea levels, subsiding land, and increasing flood risks. Through the use of a telephone survey of 1,125 adult individuals in twenty-four parishes, we gathered the demographic data and flood risk experiences and perceptions of each respondent. The data were analyzed through descriptive statistic…
A Machine Learning Approach for Detecting Rescue Requests from Social Media
Hurricane Harvey in 2017 marked an important transition where many disaster victims used social media rather than the overloaded 911 system to seek rescue. This article presents a machine-learning-based detector of rescue requests from Harvey-related Twitter messages, which differentiates itself from existing ones by accounting for the potential impacts of ZIP codes on both the preparation of training samples and the performance of different mach…
Social media for emergency rescue
Prime
Mining socioenvironmental drivers of bias in social media rescue data for fairness-aware modeling
Computer Science (19 obras) · Geography (18 obras) · Disaster Management and Resilience (12 obras) · Flood Risk Assessment and Management (8 obras) · Mathematics (8 obras) · Engineering (7 obras) · Environmental Science (7 obras) · Statistics (7 obras) · Cartography (6 obras) · Ecology (6 obras)