Ryan Engstrom
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Author Swipe
View article: Nowcasting Disruptions to Human Capital Formation: Evidence from High-Frequency Household and Geospatial Data in Rural Malawi
Nowcasting Disruptions to Human Capital Formation: Evidence from High-Frequency Household and Geospatial Data in Rural Malawi Open
Exposure to extreme weather events and other adverse shocks has led to an increasing number of humanitarian crises in developing countries in recent years. These events cause acute suffering and compromise future welfare by adversely impac…
View article: Towards an Indicator-Based Morphological Informality Model for Sub-Saharan Africa Using Open Building Footprint and Road Data (Version 1)
Towards an Indicator-Based Morphological Informality Model for Sub-Saharan Africa Using Open Building Footprint and Road Data (Version 1) Open
This study addresses the challenge of accurately mapping informal settlements, which are home to over a billion people globally. Current maps often simplify these areas into binary categories, ignoring the nuanced dimensions of deprivation…
View article: Large Area Mapping of Urban Deprivation from Sentinel-2 and Google Open Buildings using Deep Learning
Large Area Mapping of Urban Deprivation from Sentinel-2 and Google Open Buildings using Deep Learning Open
This study explores the potential of a synergistic approach combining Sentinel-2 data and Google Open Buildings (GOB) for mapping urban deprivation over large areas at a 100m spatial resolution. Urban deprivation, including slums, is a cru…
View article: IDEAMAPS: Modelling Sub-Domains of Deprivation with EO and AI
IDEAMAPS: Modelling Sub-Domains of Deprivation with EO and AI Open
IDEAMAPS is developing a participatory data-modelling ecosystem to produce maps of deprived areas ("slums") routinely and accurately at scale across cities in lower- and middle-income countries (LMICs). The Ecosystem is co-designed with lo…
View article: Towards a scalable and transferable approach to map deprived areas using Sentinel-2 images and machine learning
Towards a scalable and transferable approach to map deprived areas using Sentinel-2 images and machine learning Open
African cities are growing rapidly and more than half of their populations live in deprived areas. Local stakeholders urgently need accurate, granular, and routine maps to plan, upgrade, and monitor dynamic neighborhood-level changes. Sate…
View article: Mapping Deprived Urban Areas Using Open Geospatial Data and Machine Learning in Africa
Mapping Deprived Urban Areas Using Open Geospatial Data and Machine Learning in Africa Open
Reliable data on slums or deprived living conditions remain scarce in many low- and middle-income countries (LMICs). Global high-resolution maps of deprived areas are fundamental for both research- and evidence-based policies. Existing map…
View article: Reflecting on the YouthMappers Movement
Reflecting on the YouthMappers Movement Open
YouthMappers co-founders and organizers reflect on the contributions narrated in this volume, and in a larger sense, the contributions of the more than 300 university campus chapters in more than 60 countries. These reflections provide a p…
View article: A Methodology for Georeferencing and Mosaicking Corona Imagery in Semi-Arid Environments
A Methodology for Georeferencing and Mosaicking Corona Imagery in Semi-Arid Environments Open
High-resolution Corona imagery acquired by the United States through spy missions in the 1960s presents an opportunity to gain critical insight into historic land cover conditions and expand the timeline of available data for land cover ch…
View article: Small area estimation of non-monetary poverty with geospatial data
Small area estimation of non-monetary poverty with geospatial data Open
This paper evaluates the benefits of combining household surveys with satellite and other geospatial data to generate small area estimates of non-monetary poverty. Using data from Tanzania and Sri Lanka and applying a household-level empir…
View article: Evaluating the Ability to Use Contextual Features Derived from Multi-Scale Satellite Imagery to Map Spatial Patterns of Urban Attributes and Population Distributions
Evaluating the Ability to Use Contextual Features Derived from Multi-Scale Satellite Imagery to Map Spatial Patterns of Urban Attributes and Population Distributions Open
With an increasing global population, accurate and timely population counts are essential for urban planning and disaster management. Previous research using contextual features, using mainly very-high-spatial-resolution imagery (<2 m spat…
View article: Poverty from Space: Using High Resolution Satellite Imagery for Estimating Economic Well-being
Poverty from Space: Using High Resolution Satellite Imagery for Estimating Economic Well-being Open
Can features extracted from high spatial resolution satellite imagery accurately estimate poverty and economic well-being The present study investigates this question by extracting both object and texture features from satellite images of …
View article: Poverty from Space: Using High Resolution Satellite Imagery for Estimating Economic Well-being
Poverty from Space: Using High Resolution Satellite Imagery for Estimating Economic Well-being Open
Can features extracted from high spatial resolution satellite imagery accurately estimate poverty and economic well-being? The present study investigates this question by extracting both object and texture features from satellite images of…
View article: Development of a Multi-City Deprived Area Mapping Ecosystem
Development of a Multi-City Deprived Area Mapping Ecosystem Open
The number of people living in deprived urban areas within low and middle income countries (LMICs) is large and predicted to continue to grow. Mapping these areas over time and space in a consistent manner is important for monitoring the S…
View article: Estimating small-area population density in Sri Lanka using surveys and Geo-spatial data
Estimating small-area population density in Sri Lanka using surveys and Geo-spatial data Open
Country-level census data are typically collected once every 10 years. However, conflicts, migration, urbanization, and natural disasters can rapidly shift local population patterns. This study demonstrates the feasibility of a "bottom-up"…
View article: The Role of Earth Observation in an Integrated Deprived Area Mapping “System” for Low-to-Middle Income Countries
The Role of Earth Observation in an Integrated Deprived Area Mapping “System” for Low-to-Middle Income Countries Open
Urbanization in the global South has been accompanied by the proliferation of vast informal and marginalized urban areas that lack access to essential services and infrastructure. UN-Habitat estimates that close to a billion people current…
View article: Estimating Small Area Population Density Using Survey Data and Satellite Imagery: An Application to Sri Lanka
Estimating Small Area Population Density Using Survey Data and Satellite Imagery: An Application to Sri Lanka Open
Country-level census data are typically
\n collected once every 10 years. However, conflict, migration,
\n urbanization, and natural disasters can cause rapid shifts
\n in local population patterns. This study uses Sri Lankan
\n data to de…
View article: Land Cover Change in the Lower Yenisei River Using Dense Stacking of Landsat Imagery in Google Earth Engine
Land Cover Change in the Lower Yenisei River Using Dense Stacking of Landsat Imagery in Google Earth Engine Open
Climate warming is occurring at an unprecedented rate in the Arctic due to regional amplification, potentially accelerating land cover change. Measuring and monitoring land cover change utilizing optical remote sensing in the Arctic has be…