Ángela Abascal
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View article: Whose City Is It? Mapping Perceived Urban Livability with Citizen-Guided AI
Whose City Is It? Mapping Perceived Urban Livability with Citizen-Guided AI Open
Urban livability is shaped by dominant values, often economic or aesthetic, and power dynamics that often overlook the lived experiences of deprived urban area (DUA) residents. As a result, conventional livability indicators risk reinforci…
View article: Exploring the Relation of Livability Mapping and Flood Exposure Analysis by Combining Remote Sensing and Citizen Science
Exploring the Relation of Livability Mapping and Flood Exposure Analysis by Combining Remote Sensing and Citizen Science Open
Environmental hazards are key determinants of urban liveability, shaping the safety, health, and resilience of residents. This study investigates the intersection of urban livability and flood exposure by integrating remote sensing, citize…
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: Innovative Data Solutions for Inclusive Cities: The IDEAtlas User Portal
Innovative Data Solutions for Inclusive Cities: The IDEAtlas User Portal Open
Addressing the challenge of mapping deprived urban areas (DUAs) globally requires both technical innovation and user engagement. The IDEAtlas project developed a novel approach to monitor DUAs by combining advanced Earth Observation (EO) t…
View article: Using Low-Cost Sensors and Citizen Science: Assessing Thermal Inequality in African Slums
Using Low-Cost Sensors and Citizen Science: Assessing Thermal Inequality in African Slums Open
Urban heat exposure is intensifying due to climate change and urbanisation, with disproportionate impacts on vulnerable populations. Unfortunately, many urban areas, particularly informal settlements, lack sufficient data for detailed anal…
View article: Semi-Supervised ‘Soft’ Extraction of Urban Types Associated with Deprivation
Semi-Supervised ‘Soft’ Extraction of Urban Types Associated with Deprivation Open
info:eu-repo/semantics/published
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: User and Data-Centric Artificial Intelligence for Mapping Urban Deprivation in Multiple Cities Across the Globe
User and Data-Centric Artificial Intelligence for Mapping Urban Deprivation in Multiple Cities Across the Globe Open
The rapid urbanization in many regions worldwide results in the proliferation of deprived urban areas, also known as slums or informal settlements. Our study addresses the pressing need for accurate information by investigating User and Da…
View article: Author Correction: Monitoring, trends and impacts of light pollution
Author Correction: Monitoring, trends and impacts of light pollution Open
Correction to: Nature Reviews Earth & Environmenthttps://doi.org/10.1038/s43017-024-00555-9, published online 23 May 2024 In the version of the article initially published, the first affiliation originally included the wrong city which has…
View article: Monitoring, trends and impacts of light pollution
Monitoring, trends and impacts of light pollution Open
Light pollution has increased globally, with 80% of the total population now living under light-polluted skies. In this Review, we elucidate the scope and importance of light pollution and discuss techniques to monitor it. In urban areas, …
View article: Feature-guided deep learning model for mapping deprived areas
Feature-guided deep learning model for mapping deprived areas Open
Earth Observation (EO) data provides valuable information to localize and monitor deprived areas for the assessment of Sustainable Development Goals (SDGs). We propose a semantic segmentation model that uses a regression output to an impor…
View article: AI perceives like a local: predicting citizen deprivation perception using satellite imagery
AI perceives like a local: predicting citizen deprivation perception using satellite imagery Open
Deprived urban areas, commonly referred to as ‘slums,’ are the consequence of unprecedented urbanisation. Previous studies have highlighted the potential of Artificial Intelligence (AI) and Earth Observation (EO) in capturing physical aspe…
View article: Putting the Invisible on the Map: Low-Cost Earth Observation for Mapping and Characterizing Deprived Urban Areas (Slums)
Putting the Invisible on the Map: Low-Cost Earth Observation for Mapping and Characterizing Deprived Urban Areas (Slums) Open
It is estimated that more than half of city dwellers in sub-Saharan Africa currently live in deprived urban areas, often called slums or informal settlements, although these terms cover different urban realities. While the first target of …
View article: Night Watch, a New Earth Observation Mission Idea Theme: Technology and Design
Night Watch, a New Earth Observation Mission Idea Theme: Technology and Design Open
International audience
View article: Mapping the Invisibles: Global Urban Inequalities through Night Lights
Mapping the Invisibles: Global Urban Inequalities through Night Lights Open
Intra-urban poverty mapping using Earth Observation is primarily limited to daylight studies. Its present scope does not reveal several facets of urban poverty, such as access to reliable and sustainable energy for all (SDG-7). Most of our…
View article: Identifying degrees of deprivation from space using deep learning and morphological spatial analysis of deprived urban areas
Identifying degrees of deprivation from space using deep learning and morphological spatial analysis of deprived urban areas Open
Many cities in low- and medium-income countries (LMICs) are facing rapid unplanned growth of built-up areas, while detailed information on these deprived urban areas (DUAs) is lacking. There exist visible differences in housing conditions …
View article: “Domains of deprivation framework” for mapping slums, informal settlements, and other deprived areas in LMICs to improve urban planning and policy: A scoping review
“Domains of deprivation framework” for mapping slums, informal settlements, and other deprived areas in LMICs to improve urban planning and policy: A scoping review Open
The majority of urban inhabitants in low- and middle-income country (LMIC) cities live in deprived urban areas. However, policy efforts and the monitoring of global goals and agendas such as the United Nation's Sustainable Development Goal…
View article: Is It All the Same? Mapping and Characterizing Deprived Urban Areas Using WorldView-3 Superspectral Imagery. A Case Study in Nairobi, Kenya
Is It All the Same? Mapping and Characterizing Deprived Urban Areas Using WorldView-3 Superspectral Imagery. A Case Study in Nairobi, Kenya Open
In the past two decades, Earth observation (EO) data have been utilized for studying the spatial patterns of urban deprivation. Given the scope of many existing studies, it is still unclear how very-high-resolution EO data can help to impr…
View article: Earth Observations and Statistics: Unlocking Sociodemographic Knowledge through the Power of Satellite Images
Earth Observations and Statistics: Unlocking Sociodemographic Knowledge through the Power of Satellite Images Open
The continuous urbanisation in most Low-to-Middle-Income-Country (LMIC) cities is accompanied by rapid socio-economic changes in urban and peri-urban areas. Urban transformation processes, such as gentrification as well as the increase in …
View article: Spatial Information Gaps on Deprived Urban Areas (Slums) in Low-and-Middle-Income-Countries: A User-Centered Approach
Spatial Information Gaps on Deprived Urban Areas (Slums) in Low-and-Middle-Income-Countries: A User-Centered Approach Open
Routine and accurate data on deprivation are needed for urban planning and decision support at various scales (i.e., from community to international). However, analyzing information requirements of diverse users on urban deprivation, we fo…
View article: Extracting Urban Deprivation Indicators Using Superspectral Very-High-Resolution Satellite Imagery
Extracting Urban Deprivation Indicators Using Superspectral Very-High-Resolution Satellite Imagery Open
Most research pertaining to mapping deprived urban areas is limited to locating and delineating deprived area's extents within and across cities. In this work, we go beyond and characterize deprived areas by utilizing a wide suit of remote…
View article: "Domains of Deprivation Framework" for Mapping Slums, Informal Settlements, and Other Deprived Areas in LMICs to Improve Urban Planning and Policy: A Scoping Review
"Domains of Deprivation Framework" for Mapping Slums, Informal Settlements, and Other Deprived Areas in LMICs to Improve Urban Planning and Policy: A Scoping Review Open
The majority of urban inhabitants in low- and middle-income country (LMIC) cities live in deprived urban areas. However, statistics and data (e.g., local monitoring of Sustainable Development Goals - SDGs) are hindered by the unavailabilit…
View article: “Domains of Deprivation Framework” for Mapping Slums, Informal Settlements, and Other Deprived Areas in LMICs to Improve Urban Planning and Policy: A Scoping Review
“Domains of Deprivation Framework” for Mapping Slums, Informal Settlements, and Other Deprived Areas in LMICs to Improve Urban Planning and Policy: A Scoping Review Open
The majority of urban inhabitants in low- and middle-income country (LMIC) cities live in deprived urban areas. However, statistics and data (e.g., local monitoring of Sustainable Development Goals - SDGs) are hindered by the unavailabilit…