Nina Lam - Academia.edu (original) (raw)

Papers by Nina Lam

Applied Geography, Jul 1, 2019

Social media data is increasingly being used to improve disaster resilience and response. Recent ... more Social media data is increasingly being used to improve disaster resilience and response. Recent years have seen more efforts to integrate social media feeds with various demographic and socioeconomic variables to gain insight into the geographical and social disparities in social media use surrounding disasters. However, vulnerability concepts and indicators have been largely overlooked despite that they can offer aid in understanding and measuring the communities' sensitivity to natural hazards and their capability of responding to and recovering from disasters. This study addresses a research question: Are vulnerable communities digitally left behind in social responses to natural disasters? Our empirical analysis is based on Hurricane Sandy and is conducted in a pre-disaster setting with spatial regression modeling. We observe that physically vulnerable communities had more intense social responses while socially vulnerable communities were digitally left behind in pre-disaster social responses to Hurricane Sandy.

The Professional Geographer, Feb 13, 2020

Space and time are both crucial characteristic dimensions of geographic events and phenomena. Alt... more 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 help in exploratory space-time data analysis (ESTDA), however, are still lacking. Focusing on spatial panel data, our work extended Getis-Ord G i and G Ã i statistics using a space-time contemporaneous weight matrix and a space-time lagged weight matrix to account for local space-time autocorrelation. Two applications in this article show that the newly developed method can be used to summarize space-time patterns from spatial panel data, identify changes of landscape more consistently, and lend the results readily to visualization. Key Words: exploratory space-time data analysis (ESTDA), local space-time autocorrelation, space-time G i and G i * , space-time contemporaneous weight matrix, space-time lagged weight matrix.

Annals of the American Association of Geographers, Mar 14, 2018

Studies on how variables of community resilience to natural hazards interact as a system that aff... more 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 addresses the natural-human system as a whole. This article employs a BN to study the interdependencies of ten resilience variables and population change in the Lower Mississippi River Basin (LMRB) at the census block group scale. A genetic algorithm was used to identify an optimal BN where population change, a cumulative resilience indicator, was the target variable. The genetic algorithm yielded an optimized BN model with a cross-validation accuracy of 67 percent over a period of 906 generations. Six variables were found to have direct impacts on population change, including level of threat from coastal hazards, hazard damage, distance to coastline, employment rate, percentage of housing units built before 1970, and percentage of households with a female householder. The remaining four variables were indirect variables, including percentage agriculture land, percentage flood zone area, percentage owner-occupied house units, and population density. Each variable has a conditional probability table so that its impacts on the probability of population change can be evaluated as it propagates through the network. These probabilities could be used for scenario modeling to help inform policies to reduce vulnerability and enhance disaster resilience.

Remote Sensing Data Scale is an "innate" concept in geographic information systems. It is recogni... more Remote Sensing Data Scale is an "innate" concept in geographic information systems. It is recognized as something that is intrinsic to the ingestion, storage, manipulation, analysis, modeling, and output of space and time data within a GIS purview, yet the relative meaning and ramifications of scaling spatial and temporal data from this perspective remain enigmatic. As GISs become more sophisticated as a product of more robust sottware and more powerful computer systems, there is an urgent need to examine the issue of scale, and its relationship to the whole body of spatiotemporal data, as imparted in GISs. Scale is fundamental to the characterization of geo-spatial data as represented in GISs, but we have relatively little insight on the effects of, or how to measure the effects of, scale in representing multiscaled data; i.e., data that are acquired in different formats (e.g., map, digital) and exist in varying spatial, temporal, and in the case of remote sensing data,

AGU Fall Meeting Abstracts, Dec 1, 2017

Geomorphology, Jun 1, 2020

Delta deposits show large spatial heterogeneity in terms of depositional rate and age, which is c... more Delta deposits show large spatial heterogeneity in terms of depositional rate and age, which is critical to the study of delta erosion in response to the declining fluvial sediment load observed at many river mouths in the world. In this study, we show that the magnetic susceptibility (χ) can be an indicator to reveal age variations and stratigraphic heterogeneity in the Yangtze River subaqueous delta. Ages of three short sediment cores (b2 m) collected at 20-32 m water depth from the Yangtze River subaqueous delta were determined using 210 Pb, 137 Cs, and optically stimulated luminescence (OSL) dating. In addition, depth variation of χ, which is influenced by postdepositional diagenesis and hence age, was used to roughly infer sediment ages among the cores in a simple way. The profiles of 210 Pb, 137 Cs, and OSL dating results indicate the spatial variability of ages, ranging from the last 100 years to N1700 years. The cores at shallow water depths are younger than those from deeper sites. Modern deposits (i.e., b100 years old) occur primarily at water depths shallower than ca. 30 m. The core in the northern part of the subaqueous delta shows much older ages than the core at the southern site with similar water depth, which is caused by their longer distance relative to the mouth of active sediment discharge distributary. Profile of χ confirms such spatial variation of ages in terms of depth distribution pattern and χ value. Older sediments (N800 a) show lower and uniform χ values due to the reductive dissolution of ferrimagnetic minerals, while younger sediments (b350 a) show higher χ values in the top layer but they decline with increasing depth. Considering the quick way of magnetic measurement, stratigraphic correlation based on χ can be used first to screen for cores before they are subjected to more detailed dating. This study shows that the methodological approach of combining sediment dating with magnetic measurement has great potential in revealing heterogeneous deltaic deposits.

Remote Sensing of Environment, May 1, 2018

Coastal Louisiana has been facing a serious land loss problem over the past several decades, and ... more Coastal Louisiana has been facing a serious land loss problem over the past several decades, and extensive research has been undertaken to address the problem. However, the importance of landscape fragmentation on land loss has seldom been examined. This paper evaluates the effects of landscape fragmentation on land loss in the Lower Mississippi River Basin region. The research hypothesis is that the higher the degree of fragmentation in a locality, the greater the amount of land loss in the next time period. We used Landsat-TM data with a pixel size of 30 m × 30 m in 1996 and 2010 and transformed the images into either land or water pixels. We then calculated the fractal dimension and Moran's I spatial autocorrelation statistics and used them to represent the degree of landscape fragmentation. Four sample box sizes, including sizes of 101 × 101, 71 × 71, 51 × 51, and 31 × 31 pixels, were used to detect if there is a relationship between fragmentation and land loss at different neighborhood (context) scales. For each box size, 100 samples were randomly selected. To isolate the fragmentation effect so that it can be better evaluated, we used only sample boxes with a 50% land-water ratio. Regression results between fragmentation and land loss show that the R 2 values for box sizes of 71 × 71, 51 × 51 and 31 × 31 were statistically significant (0.20, 0.45, 0.35; p < 0.001 for Moran's I) but not for the 101 × 101 box size. These results imply that land protection may be most effective by prioritizing areas with land patches that have the least fragmentation. Furthermore, the neighborhood scale at which the R 2 value is the highest indicates the scale at which the effects are most likely to be observed (51 × 51 box size, approximately 1.5 × 1.5 km 2 , R 2 = 0.45), which suggests that future land loss modeling using this neighborhood scale would be most effective.

Routledge eBooks, Jan 6, 2023

Anthropocene coasts, May 11, 2022

Coastal erosion is widespread under conditions of changing hydrodynamics and diminishing sediment... more Coastal erosion is widespread under conditions of changing hydrodynamics and diminishing sediment supply, and exposure assessment to erosion hazard has received increasing attention. In this study, we explore the impact of spatial heterogeneity of land use within administrative units on exposure assessment of land use value to erosional hazard. We illustrate land use diversity using the Shannon's diversity index (SHDI) and consider the distance effect by comparing five different buffer zones according to the distance to the coast (i.e., 0-1 km, 0-2 km, 0-3 km, 0-4 km, 0-5 km). Our results show that coastline change and socioeconomic development are responsible for land use heterogeneity within the administrative units. Using a buffer zone of 1-km along the coast as the assessment unit leads to an increase in the number of townships that have high and very high exposure of land use value when compared with the assessment result that is based on the whole township area. Furthermore, the 1-km buffer zone can be divided into subunits if very high SHDI values exist within the administrative boundary. This study demonstrates that heterogeneity in land use identified at a fine spatial scale should be given full consideration in carrying out exposure assessment to hazards in a dynamic deltaic coast.

Routledge eBooks, Jan 6, 2023

Water, Sep 24, 2018

This book contains 14 articles selected from a special issue on the assessment of resilience and ... more This book contains 14 articles selected from a special issue on the assessment of resilience and sustainability of the Mississippi River Delta as a coupled natural-human system. This effort is supported in part by a U. S. National Science Foundation grant. The goal of this book is to present some of the recent advances in research and research methodologies, major discoveries, and new understanding of the Mississippi River Delta, which represents one of the most challenging cases in finding the pathways for coastal resilience and sustainability because of the complexity of environmental and socioeconomic interactions. The articles are contributed by 39 researchers and they studied the deltaic system from five aspects including 1) riverine processes and sediment availability, 2) sediment deposition and land creation, 3) wetland loss, saltwater intrusion, and subsidence, 4) community resilience and planning, and 5) review and synthesis. As editors, by reviewing and putting these papers together, we have realized a major challenge in conducting an interdisciplinary assessment of resilience: How to identify a "Common Threshold" from different scientific disciplines for a highly nature-human intertwined river delta system? For instance, the threshold for sustaining a river delta in the view of physical sciences is different from that of social sciences. Such a common threshold would be a radical change and/or a collapse of a coupled natural-human delta system if nothing can be or will be done. Identifying the common threshold would help guide assessment and evaluation of the resilience of a CNH system as well as the feasibility and willingness of protecting the system's resilience. We hope this book will be a first step toward inspiring researchers from different disciplines to work closely together to solve real problems in sustaining precious river delta ecosystems across the globe.

International journal of disaster risk reduction, Dec 1, 2019

In search of new insights into the dynamics of hazard resilience, this study assessed the tempora... more In search of new insights into the dynamics of hazard resilience, this study assessed the temporal changes of community resilience to the drought hazard in the south-central U.S. The study hypothesized that over time counties with more affluent socioeconomic conditions and more diverse agriculture would improve their resilience while counties with poorer socioeconomic conditions and heavy reliance on agriculture decreased their resilience, thus widening the regional disparities in community resilience to the drought hazard. The study applied the Resilience Inference Measurement (RIM) framework to measure the resilience levels of the 503 counties of Arkansas, Louisiana, New Mexico, Oklahoma, and Texas. Using data of Year 2000, the RIM model selected 10 variables as resilience predictors with a 67.9% classification accuracy and assigned a resilience level to each county. The variables selected in the RIM model are related to the economic performance in the agricultural sector, socioeconomic well-being, and health. The derived discriminant functions from the RIM model were then used to estimate the resilience levels in 2005, 2010, and 2015. Over the 15-year period, 262 counties across the study area improved their resilience, whereas 48 counties, mostly in the Texas High Plains, experienced a decrease in their resilience level. The results support the hypothesis and suggest a widening gap in resilience levels among counties. These results increase our understanding of the complex process underlying communities' response to the drought impacts.

Ocean & Coastal Management, Dec 1, 2021

Journal of Coastal Research, May 1, 2018

It is widely known that the same type and strength of hazard could lead to very uneven impacts on... more It is widely known that the same type and strength of hazard could lead to very uneven impacts on different communities due to their varying vulnerability and resilience capacity. Hence, identifying the factors that make a community more resilient to hazards is critical to its sustainability and is central to climate change research and planning. This paper addresses three questions: what is the best way to measure community resilience to disasters and how to identify the key indicators? How do the resilience indicators dynamically interact in a quantitative manner that would lead to long-term resilience? And how can we translate the scientific results into practical tools for decision making? Using the population change pattern in the Mississippi River Delta as a case study, this paper demonstrates the use of a relatively new resilience assessment method called the Resilience Inference Measurement (RIM) method to measure resilience. Then, a newly developed spatial dynamic model is used to simulate population changes in the study area. The results show that without any changes in the current condition, the coastal portion of the study area will continue to suffer population loss and the region is unlikely to sustain in the future.

International journal of disaster risk reduction, Oct 1, 2018

Disaster resilience has become an important societal goal which captures the attention of academi... more Disaster resilience has become an important societal goal which captures the attention of academics and decision makers from various disciplines and sectors. Developing tools or metrics for measuring and monitoring progress of resilience is a critical component that requires extensive research to achieve better understanding. However, different fields have different emphases and the knowledge gained from the various studies are scattered and fragmented. To provide an integration of the literature and reflect on the current state of resilience measurement, we conducted a synthesis analysis through a systematic review of 174 scholarly articles on disaster resilience measurement from 2005 to 2017. Using a review table designed for this study and content analysis, we extracted key information from each article on resilience definition, type of measurement method, resilience indicators used, and proposed adaptation strategies. Results indicate that 39.7% of the articles used qualitative methods for resilience measurement and 39.1% of the articles used quantitative methods. However, only 10.3% of all the 174 articles 2 conducted empirical validation of their proposed resilience indices. The three most frequently suggested adaptation strategies were empowering local governments and leaders, raising community awareness, and enhancing community infrastructure and communication. These findings suggest that future research need to incorporate validation and inferential ability into resilience measurement. Extending from static resilience measurement to dynamic system modeling and bridging the disconnection between resilience scientific research and practical actions are also pressing needs.

International Journal of Digital Earth

Applied Geography, Jul 1, 2019

Social media data is increasingly being used to improve disaster resilience and response. Recent ... more Social media data is increasingly being used to improve disaster resilience and response. Recent years have seen more efforts to integrate social media feeds with various demographic and socioeconomic variables to gain insight into the geographical and social disparities in social media use surrounding disasters. However, vulnerability concepts and indicators have been largely overlooked despite that they can offer aid in understanding and measuring the communities' sensitivity to natural hazards and their capability of responding to and recovering from disasters. This study addresses a research question: Are vulnerable communities digitally left behind in social responses to natural disasters? Our empirical analysis is based on Hurricane Sandy and is conducted in a pre-disaster setting with spatial regression modeling. We observe that physically vulnerable communities had more intense social responses while socially vulnerable communities were digitally left behind in pre-disaster social responses to Hurricane Sandy.

The Professional Geographer, Feb 13, 2020

Space and time are both crucial characteristic dimensions of geographic events and phenomena. Alt... more 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 help in exploratory space-time data analysis (ESTDA), however, are still lacking. Focusing on spatial panel data, our work extended Getis-Ord G i and G Ã i statistics using a space-time contemporaneous weight matrix and a space-time lagged weight matrix to account for local space-time autocorrelation. Two applications in this article show that the newly developed method can be used to summarize space-time patterns from spatial panel data, identify changes of landscape more consistently, and lend the results readily to visualization. Key Words: exploratory space-time data analysis (ESTDA), local space-time autocorrelation, space-time G i and G i * , space-time contemporaneous weight matrix, space-time lagged weight matrix.

Annals of the American Association of Geographers, Mar 14, 2018

Studies on how variables of community resilience to natural hazards interact as a system that aff... more 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 addresses the natural-human system as a whole. This article employs a BN to study the interdependencies of ten resilience variables and population change in the Lower Mississippi River Basin (LMRB) at the census block group scale. A genetic algorithm was used to identify an optimal BN where population change, a cumulative resilience indicator, was the target variable. The genetic algorithm yielded an optimized BN model with a cross-validation accuracy of 67 percent over a period of 906 generations. Six variables were found to have direct impacts on population change, including level of threat from coastal hazards, hazard damage, distance to coastline, employment rate, percentage of housing units built before 1970, and percentage of households with a female householder. The remaining four variables were indirect variables, including percentage agriculture land, percentage flood zone area, percentage owner-occupied house units, and population density. Each variable has a conditional probability table so that its impacts on the probability of population change can be evaluated as it propagates through the network. These probabilities could be used for scenario modeling to help inform policies to reduce vulnerability and enhance disaster resilience.

Remote Sensing Data Scale is an "innate" concept in geographic information systems. It is recogni... more Remote Sensing Data Scale is an "innate" concept in geographic information systems. It is recognized as something that is intrinsic to the ingestion, storage, manipulation, analysis, modeling, and output of space and time data within a GIS purview, yet the relative meaning and ramifications of scaling spatial and temporal data from this perspective remain enigmatic. As GISs become more sophisticated as a product of more robust sottware and more powerful computer systems, there is an urgent need to examine the issue of scale, and its relationship to the whole body of spatiotemporal data, as imparted in GISs. Scale is fundamental to the characterization of geo-spatial data as represented in GISs, but we have relatively little insight on the effects of, or how to measure the effects of, scale in representing multiscaled data; i.e., data that are acquired in different formats (e.g., map, digital) and exist in varying spatial, temporal, and in the case of remote sensing data,

AGU Fall Meeting Abstracts, Dec 1, 2017

Geomorphology, Jun 1, 2020

Delta deposits show large spatial heterogeneity in terms of depositional rate and age, which is c... more Delta deposits show large spatial heterogeneity in terms of depositional rate and age, which is critical to the study of delta erosion in response to the declining fluvial sediment load observed at many river mouths in the world. In this study, we show that the magnetic susceptibility (χ) can be an indicator to reveal age variations and stratigraphic heterogeneity in the Yangtze River subaqueous delta. Ages of three short sediment cores (b2 m) collected at 20-32 m water depth from the Yangtze River subaqueous delta were determined using 210 Pb, 137 Cs, and optically stimulated luminescence (OSL) dating. In addition, depth variation of χ, which is influenced by postdepositional diagenesis and hence age, was used to roughly infer sediment ages among the cores in a simple way. The profiles of 210 Pb, 137 Cs, and OSL dating results indicate the spatial variability of ages, ranging from the last 100 years to N1700 years. The cores at shallow water depths are younger than those from deeper sites. Modern deposits (i.e., b100 years old) occur primarily at water depths shallower than ca. 30 m. The core in the northern part of the subaqueous delta shows much older ages than the core at the southern site with similar water depth, which is caused by their longer distance relative to the mouth of active sediment discharge distributary. Profile of χ confirms such spatial variation of ages in terms of depth distribution pattern and χ value. Older sediments (N800 a) show lower and uniform χ values due to the reductive dissolution of ferrimagnetic minerals, while younger sediments (b350 a) show higher χ values in the top layer but they decline with increasing depth. Considering the quick way of magnetic measurement, stratigraphic correlation based on χ can be used first to screen for cores before they are subjected to more detailed dating. This study shows that the methodological approach of combining sediment dating with magnetic measurement has great potential in revealing heterogeneous deltaic deposits.

Remote Sensing of Environment, May 1, 2018

Coastal Louisiana has been facing a serious land loss problem over the past several decades, and ... more Coastal Louisiana has been facing a serious land loss problem over the past several decades, and extensive research has been undertaken to address the problem. However, the importance of landscape fragmentation on land loss has seldom been examined. This paper evaluates the effects of landscape fragmentation on land loss in the Lower Mississippi River Basin region. The research hypothesis is that the higher the degree of fragmentation in a locality, the greater the amount of land loss in the next time period. We used Landsat-TM data with a pixel size of 30 m × 30 m in 1996 and 2010 and transformed the images into either land or water pixels. We then calculated the fractal dimension and Moran's I spatial autocorrelation statistics and used them to represent the degree of landscape fragmentation. Four sample box sizes, including sizes of 101 × 101, 71 × 71, 51 × 51, and 31 × 31 pixels, were used to detect if there is a relationship between fragmentation and land loss at different neighborhood (context) scales. For each box size, 100 samples were randomly selected. To isolate the fragmentation effect so that it can be better evaluated, we used only sample boxes with a 50% land-water ratio. Regression results between fragmentation and land loss show that the R 2 values for box sizes of 71 × 71, 51 × 51 and 31 × 31 were statistically significant (0.20, 0.45, 0.35; p < 0.001 for Moran's I) but not for the 101 × 101 box size. These results imply that land protection may be most effective by prioritizing areas with land patches that have the least fragmentation. Furthermore, the neighborhood scale at which the R 2 value is the highest indicates the scale at which the effects are most likely to be observed (51 × 51 box size, approximately 1.5 × 1.5 km 2 , R 2 = 0.45), which suggests that future land loss modeling using this neighborhood scale would be most effective.

Routledge eBooks, Jan 6, 2023

Anthropocene coasts, May 11, 2022

Coastal erosion is widespread under conditions of changing hydrodynamics and diminishing sediment... more Coastal erosion is widespread under conditions of changing hydrodynamics and diminishing sediment supply, and exposure assessment to erosion hazard has received increasing attention. In this study, we explore the impact of spatial heterogeneity of land use within administrative units on exposure assessment of land use value to erosional hazard. We illustrate land use diversity using the Shannon's diversity index (SHDI) and consider the distance effect by comparing five different buffer zones according to the distance to the coast (i.e., 0-1 km, 0-2 km, 0-3 km, 0-4 km, 0-5 km). Our results show that coastline change and socioeconomic development are responsible for land use heterogeneity within the administrative units. Using a buffer zone of 1-km along the coast as the assessment unit leads to an increase in the number of townships that have high and very high exposure of land use value when compared with the assessment result that is based on the whole township area. Furthermore, the 1-km buffer zone can be divided into subunits if very high SHDI values exist within the administrative boundary. This study demonstrates that heterogeneity in land use identified at a fine spatial scale should be given full consideration in carrying out exposure assessment to hazards in a dynamic deltaic coast.

Routledge eBooks, Jan 6, 2023

Water, Sep 24, 2018

This book contains 14 articles selected from a special issue on the assessment of resilience and ... more This book contains 14 articles selected from a special issue on the assessment of resilience and sustainability of the Mississippi River Delta as a coupled natural-human system. This effort is supported in part by a U. S. National Science Foundation grant. The goal of this book is to present some of the recent advances in research and research methodologies, major discoveries, and new understanding of the Mississippi River Delta, which represents one of the most challenging cases in finding the pathways for coastal resilience and sustainability because of the complexity of environmental and socioeconomic interactions. The articles are contributed by 39 researchers and they studied the deltaic system from five aspects including 1) riverine processes and sediment availability, 2) sediment deposition and land creation, 3) wetland loss, saltwater intrusion, and subsidence, 4) community resilience and planning, and 5) review and synthesis. As editors, by reviewing and putting these papers together, we have realized a major challenge in conducting an interdisciplinary assessment of resilience: How to identify a "Common Threshold" from different scientific disciplines for a highly nature-human intertwined river delta system? For instance, the threshold for sustaining a river delta in the view of physical sciences is different from that of social sciences. Such a common threshold would be a radical change and/or a collapse of a coupled natural-human delta system if nothing can be or will be done. Identifying the common threshold would help guide assessment and evaluation of the resilience of a CNH system as well as the feasibility and willingness of protecting the system's resilience. We hope this book will be a first step toward inspiring researchers from different disciplines to work closely together to solve real problems in sustaining precious river delta ecosystems across the globe.

International journal of disaster risk reduction, Dec 1, 2019

In search of new insights into the dynamics of hazard resilience, this study assessed the tempora... more In search of new insights into the dynamics of hazard resilience, this study assessed the temporal changes of community resilience to the drought hazard in the south-central U.S. The study hypothesized that over time counties with more affluent socioeconomic conditions and more diverse agriculture would improve their resilience while counties with poorer socioeconomic conditions and heavy reliance on agriculture decreased their resilience, thus widening the regional disparities in community resilience to the drought hazard. The study applied the Resilience Inference Measurement (RIM) framework to measure the resilience levels of the 503 counties of Arkansas, Louisiana, New Mexico, Oklahoma, and Texas. Using data of Year 2000, the RIM model selected 10 variables as resilience predictors with a 67.9% classification accuracy and assigned a resilience level to each county. The variables selected in the RIM model are related to the economic performance in the agricultural sector, socioeconomic well-being, and health. The derived discriminant functions from the RIM model were then used to estimate the resilience levels in 2005, 2010, and 2015. Over the 15-year period, 262 counties across the study area improved their resilience, whereas 48 counties, mostly in the Texas High Plains, experienced a decrease in their resilience level. The results support the hypothesis and suggest a widening gap in resilience levels among counties. These results increase our understanding of the complex process underlying communities' response to the drought impacts.

Ocean & Coastal Management, Dec 1, 2021

Journal of Coastal Research, May 1, 2018

It is widely known that the same type and strength of hazard could lead to very uneven impacts on... more It is widely known that the same type and strength of hazard could lead to very uneven impacts on different communities due to their varying vulnerability and resilience capacity. Hence, identifying the factors that make a community more resilient to hazards is critical to its sustainability and is central to climate change research and planning. This paper addresses three questions: what is the best way to measure community resilience to disasters and how to identify the key indicators? How do the resilience indicators dynamically interact in a quantitative manner that would lead to long-term resilience? And how can we translate the scientific results into practical tools for decision making? Using the population change pattern in the Mississippi River Delta as a case study, this paper demonstrates the use of a relatively new resilience assessment method called the Resilience Inference Measurement (RIM) method to measure resilience. Then, a newly developed spatial dynamic model is used to simulate population changes in the study area. The results show that without any changes in the current condition, the coastal portion of the study area will continue to suffer population loss and the region is unlikely to sustain in the future.

International journal of disaster risk reduction, Oct 1, 2018

Disaster resilience has become an important societal goal which captures the attention of academi... more Disaster resilience has become an important societal goal which captures the attention of academics and decision makers from various disciplines and sectors. Developing tools or metrics for measuring and monitoring progress of resilience is a critical component that requires extensive research to achieve better understanding. However, different fields have different emphases and the knowledge gained from the various studies are scattered and fragmented. To provide an integration of the literature and reflect on the current state of resilience measurement, we conducted a synthesis analysis through a systematic review of 174 scholarly articles on disaster resilience measurement from 2005 to 2017. Using a review table designed for this study and content analysis, we extracted key information from each article on resilience definition, type of measurement method, resilience indicators used, and proposed adaptation strategies. Results indicate that 39.7% of the articles used qualitative methods for resilience measurement and 39.1% of the articles used quantitative methods. However, only 10.3% of all the 174 articles 2 conducted empirical validation of their proposed resilience indices. The three most frequently suggested adaptation strategies were empowering local governments and leaders, raising community awareness, and enhancing community infrastructure and communication. These findings suggest that future research need to incorporate validation and inferential ability into resilience measurement. Extending from static resilience measurement to dynamic system modeling and bridging the disconnection between resilience scientific research and practical actions are also pressing needs.

International Journal of Digital Earth