Catherine Linard
Biographic Data
| ID | 3562574 |
|---|---|
| NAME | Catherine Linard |
| GIVEN NAMES | Catherine |
| FAMILY NAME | Linard |
| SIGNATURE | LINARD C |
| AFFILIATIONS | University of Namur |
| ORCID | 0000-0002-0819-7755 |
| VERIFIED | Yes |
| TOTAL WORKS | 19 |
| TOTAL CITATIONS | 32 |
| AUTHOR COUNT | 19 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2009 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 4 |
Spatio-temporal modelling of Covid-19 infection and associated risk factors in Dakar, Senegal
Infectious diseases are a major threat to global health and economy and the recent COVID-19 pandemic is a perfect example of this. Appropriate modelling and accurate prediction of the outcome of disease spread over time and across space are critical steps towards informed development of effective strategies for public health interventions. In low and middle-income countries, however, the scarcity of spatially disaggregated time-series infectious …
Dynamic Social Vulnerability Mapping Using Facebook Data
Assessing populations exposed to climate change impacts traditionally relies upon census data estimations. Yet, these only provide a static picture of risk since censuses are often undertaken and released over long periods and thus cannot be updated regularly. In this study, we investigate how to leverage multi‐temporal geolocated social media data from Meta‐Facebook and assess spatio‐temporal variations of population exposure and vulnerability t…
Mapping abundance distributions of allergenic tree species in urbanized landscapes: A nation-wide study for Belgium using forest inventory and citizen science data
Geographical random forests: A spatial extension of the random forest algorithm to address spatial heterogeneity in remote sensing and population modelling
Machine learning algorithms such as Random Forest (RF) are being increasingly applied on traditionally geographical topics such as population estimation. Even though RF is a well performing and generalizable algorithm, the vast majority of its implementations is still ‘aspatial’ and may not address spatial heterogenous processes. At the same time, remote sensing (RS) data which are commonly used to model population can be highly spatially heterog…
Residential green space types, allergy symptoms and mental health in a cohort of tree pollen allergy patients
Annually modelling built-settlements between remotely-sensed observations using relative changes in subnational populations and lights at night
Mapping urban features/human built-settlement extents at the annual time step has a wide variety of applications in demography, public health, sustainable development, and many other fields. Recently, while more multitemporal urban features/human built-settlement datasets have become available, issues still exist in remotely-sensed imagery due to spatial and temporal coverage, adverse atmospheric conditions, and expenses involved in producing suc…
An evaluation of species distribution models to estimate tree diversity at genus level in a heterogeneous urban-rural landscape
Can we use local climate zones for predicting malaria prevalence across sub-Saharan African cities
Malaria burden is increasing in sub-Saharan cities because of rapid and uncontrolled urbanization. Yet very few studies have studied the interactions between urban environments and malaria. Additionally, no standardized urban land-use/land-cover has been defined for urban malaria studies. Here, we demonstrate the potential of local climate zones (LCZs) for modeling malaria prevalence rate ( Pf PR 2-10 ) and studying malaria prevalence in urban se…
Sars-CoV-2 emergence and diffusion: A new disease manifesting human–environment interactions and a global geography of health
Need for an Integrated Deprived Area "Slum" Mapping System (Ideamaps) in Low- and Middle-Income Countries (LMICs)
Ninety percent of the people added to the planet over the next 30 years will live in African and Asian cities, and a large portion of these populations will reside in deprived neighborhoods defined by slum conditions, informal settlement, or inadequate housing. The four current approaches to neighborhood deprivation mapping are largely siloed, and each fall short of producing accurate, timely, and comparable maps that reflect local contexts. The …
Emerging challenges of infectious diseases as a feature of land systems
Extending Data for Urban Health Decision-Making: A Menu of New and Potential Neighborhood-Level Health Determinants Datasets in LMICs
Area-level indicators of the determinants of health are vital to plan and monitor progress toward targets such as the Sustainable Development Goals (SDGs). Tools such as the Urban Health Equity Assessment and Response Tool (Urban HEART) and UN-Habitat Urban Inequities Surveys identify dozens of area-level health determinant indicators that decision-makers can use to track and attempt to address population health burdens and inequalities. However,…
People and Pixels 20 years later: The current data landscape and research trends blending population and environmental data
Disaggregating Census Data for Population Mapping Using Random Forests with Remotely-Sensed and Ancillary Data
High resolution, contemporary data on human population distributions are vital for measuring impacts of population growth, monitoring human-environment interactions and for planning and policy development. Many methods are used to disaggregate census data and predict population densities for finer scale, gridded population data sets. We present a new semi-automated dasymetric modeling approach that incorporates detailed census and ancillary data …
Dynamic population mapping using mobile phone data
Significance Knowing where people are is critical for accurate impact assessments and intervention planning, particularly those focused on population health, food security, climate change, conflicts, and natural disasters. This study demonstrates how data collected by mobile phone network operators can cost-effectively provide accurate and detailed maps of population distribution over national scales and any time period while guaranteeing phone u…
Science–policy challenges for biodiversity, public health and urbanization: Examples from Belgium
Internationally, the importance of a coordinated effort to protect both biodiversity and public health is more and more recognized. These issues are often concentrated or particularly challenging in urban areas, and therefore on-going urbanization worldwide raises particular issues both for the conservation of living natural resources and for population health strategies. These challenges include significant difficulties associated with sustainab…
Population Distribution, Settlement Patterns and Accessibility across Africa in 2010
The spatial distribution of populations and settlements across a country and their interconnectivity and accessibility from urban areas are important for delivering healthcare, distributing resources and economic development. However, existing spatially explicit population data across Africa are generally based on outdated, low resolution input demographic data, and provide insufficient detail to quantify rural settlement patterns and, thus, accu…
Assessing the use of global land cover data for guiding large area population distribution modelling
Gridded population distribution data are finding increasing use in a wide range of fields, including resource allocation, disease burden estimation and climate change impact assessment. Land cover information can be used in combination with detailed settlement extents to redistribute aggregated census counts to improve the accuracy of national-scale gridded population data. In East Africa, such analyses have been done using regional land cover da…
Risk of Malaria Reemergence in Southern France: Testing Scenarios with a Multiagent Simulation Model
Need for an Integrated Deprived Area "Slum" Mapping System (Ideamaps) in Low- and Middle-Income Countries (LMICs)
Ninety percent of the people added to the planet over the next 30 years will live in African and Asian cities, and a large portion of these populations will reside in deprived neighborhoods defined by slum conditions, informal settlement, or inadequate housing. The four current approaches to neighborhood deprivation mapping are largely siloed, and each fall short of producing accurate, timely, and comparable maps that reflect local contexts. The …
People and Pixels 20 years later: The current data landscape and research trends blending population and environmental data
Assessing the use of global land cover data for guiding large area population distribution modelling
Gridded population distribution data are finding increasing use in a wide range of fields, including resource allocation, disease burden estimation and climate change impact assessment. Land cover information can be used in combination with detailed settlement extents to redistribute aggregated census counts to improve the accuracy of national-scale gridded population data. In East Africa, such analyses have been done using regional land cover da…
Extending Data for Urban Health Decision-Making: A Menu of New and Potential Neighborhood-Level Health Determinants Datasets in LMICs
Area-level indicators of the determinants of health are vital to plan and monitor progress toward targets such as the Sustainable Development Goals (SDGs). Tools such as the Urban Health Equity Assessment and Response Tool (Urban HEART) and UN-Habitat Urban Inequities Surveys identify dozens of area-level health determinant indicators that decision-makers can use to track and attempt to address population health burdens and inequalities. However,…
Emerging challenges of infectious diseases as a feature of land systems
Risk of Malaria Reemergence in Southern France: Testing Scenarios with a Multiagent Simulation Model
Assessing the use of global land cover data for guiding large area population distribution modelling
Gridded population distribution data are finding increasing use in a wide range of fields, including resource allocation, disease burden estimation and climate change impact assessment. Land cover information can be used in combination with detailed settlement extents to redistribute aggregated census counts to improve the accuracy of national-scale gridded population data. In East Africa, such analyses have been done using regional land cover da…
Population Distribution, Settlement Patterns and Accessibility across Africa in 2010
The spatial distribution of populations and settlements across a country and their interconnectivity and accessibility from urban areas are important for delivering healthcare, distributing resources and economic development. However, existing spatially explicit population data across Africa are generally based on outdated, low resolution input demographic data, and provide insufficient detail to quantify rural settlement patterns and, thus, accu…
Science–policy challenges for biodiversity, public health and urbanization: Examples from Belgium
Internationally, the importance of a coordinated effort to protect both biodiversity and public health is more and more recognized. These issues are often concentrated or particularly challenging in urban areas, and therefore on-going urbanization worldwide raises particular issues both for the conservation of living natural resources and for population health strategies. These challenges include significant difficulties associated with sustainab…
Dynamic population mapping using mobile phone data
Significance Knowing where people are is critical for accurate impact assessments and intervention planning, particularly those focused on population health, food security, climate change, conflicts, and natural disasters. This study demonstrates how data collected by mobile phone network operators can cost-effectively provide accurate and detailed maps of population distribution over national scales and any time period while guaranteeing phone u…
Disaggregating Census Data for Population Mapping Using Random Forests with Remotely-Sensed and Ancillary Data
High resolution, contemporary data on human population distributions are vital for measuring impacts of population growth, monitoring human-environment interactions and for planning and policy development. Many methods are used to disaggregate census data and predict population densities for finer scale, gridded population data sets. We present a new semi-automated dasymetric modeling approach that incorporates detailed census and ancillary data …
Emerging challenges of infectious diseases as a feature of land systems
Extending Data for Urban Health Decision-Making: A Menu of New and Potential Neighborhood-Level Health Determinants Datasets in LMICs
Area-level indicators of the determinants of health are vital to plan and monitor progress toward targets such as the Sustainable Development Goals (SDGs). Tools such as the Urban Health Equity Assessment and Response Tool (Urban HEART) and UN-Habitat Urban Inequities Surveys identify dozens of area-level health determinant indicators that decision-makers can use to track and attempt to address population health burdens and inequalities. However,…
People and Pixels 20 years later: The current data landscape and research trends blending population and environmental data
Annually modelling built-settlements between remotely-sensed observations using relative changes in subnational populations and lights at night
Mapping urban features/human built-settlement extents at the annual time step has a wide variety of applications in demography, public health, sustainable development, and many other fields. Recently, while more multitemporal urban features/human built-settlement datasets have become available, issues still exist in remotely-sensed imagery due to spatial and temporal coverage, adverse atmospheric conditions, and expenses involved in producing suc…
An evaluation of species distribution models to estimate tree diversity at genus level in a heterogeneous urban-rural landscape
Can we use local climate zones for predicting malaria prevalence across sub-Saharan African cities
Malaria burden is increasing in sub-Saharan cities because of rapid and uncontrolled urbanization. Yet very few studies have studied the interactions between urban environments and malaria. Additionally, no standardized urban land-use/land-cover has been defined for urban malaria studies. Here, we demonstrate the potential of local climate zones (LCZs) for modeling malaria prevalence rate ( Pf PR 2-10 ) and studying malaria prevalence in urban se…
Sars-CoV-2 emergence and diffusion: A new disease manifesting human–environment interactions and a global geography of health
Need for an Integrated Deprived Area "Slum" Mapping System (Ideamaps) in Low- and Middle-Income Countries (LMICs)
Ninety percent of the people added to the planet over the next 30 years will live in African and Asian cities, and a large portion of these populations will reside in deprived neighborhoods defined by slum conditions, informal settlement, or inadequate housing. The four current approaches to neighborhood deprivation mapping are largely siloed, and each fall short of producing accurate, timely, and comparable maps that reflect local contexts. The …
Geographical random forests: A spatial extension of the random forest algorithm to address spatial heterogeneity in remote sensing and population modelling
Machine learning algorithms such as Random Forest (RF) are being increasingly applied on traditionally geographical topics such as population estimation. Even though RF is a well performing and generalizable algorithm, the vast majority of its implementations is still ‘aspatial’ and may not address spatial heterogenous processes. At the same time, remote sensing (RS) data which are commonly used to model population can be highly spatially heterog…
Residential green space types, allergy symptoms and mental health in a cohort of tree pollen allergy patients
Mapping abundance distributions of allergenic tree species in urbanized landscapes: A nation-wide study for Belgium using forest inventory and citizen science data
Dynamic Social Vulnerability Mapping Using Facebook Data
Assessing populations exposed to climate change impacts traditionally relies upon census data estimations. Yet, these only provide a static picture of risk since censuses are often undertaken and released over long periods and thus cannot be updated regularly. In this study, we investigate how to leverage multi‐temporal geolocated social media data from Meta‐Facebook and assess spatio‐temporal variations of population exposure and vulnerability t…
Spatio-temporal modelling of Covid-19 infection and associated risk factors in Dakar, Senegal
Infectious diseases are a major threat to global health and economy and the recent COVID-19 pandemic is a perfect example of this. Appropriate modelling and accurate prediction of the outcome of disease spread over time and across space are critical steps towards informed development of effective strategies for public health interventions. In low and middle-income countries, however, the scarcity of spatially disaggregated time-series infectious …
Geography (17 works) · Medicine (11 works) · Environmental health (9 works) · Population (9 works) · Ecology (8 works) · Environmental Science (8 works) · Biology (7 works) · Environmental resource management (7 works) · Impact of Light on Environment and Health (7 works) · Computer Science (6 works)