Anderson Dias de Freitas
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Anderson Dias de Freitas has a total of 6 co-authors. Here are the top co-authors by number of shared publications:
- Federico Costa
Federal University of Bahia
1 shared publication - Jiong Wang
Department of Urban and Regional Planning and Geo-Information Management, ITC, University of Twente, Enschede, The Netherlands
1 shared publication - Julio Cesar Pedrassoli
Universidade Federal da Bahia (UFBA)
1 shared publication - Mila Koeva
Univerity of Twente
1 shared publication - Monika Kuffer
Faculty of Geo-Information Science and Earth Observation, University of Twente, Enschede, The Netherlands
1 shared publication - Patricia Lustosa Brito
Universidade Federal da Bahia
1 shared publication
Latest Publications
- Open Access
- 20 September 2020
- Published by MDPI AG in ISPRS International Journal of Geo-Information
- Vol. 9 (9) , 557
The Spatial Dimension of COVID-19: The Potential of Earth Observation Data in Support of Slum Communities with Evidence from Brazil
The COVID-19 health emergency is impacting all of our lives, but the living conditions and urban morphologies found in poor communities make inhabitants more vulnerable to the COVID-19 outbreak as compared to the formal city, where inhabitants have the resources to follow WHO guidelines. In general, municipal spatial datasets are not well equipped to support spatial responses to health emergencies, particularly in poor communities. In such critical situations, Earth observation (EO) data can play a vital role in timely decision making and can save many people’s lives. This work provides an overview of the potential of EO-based global and local datasets, as well as local data gathering procedures (e.g., drones), in support of COVID-19 responses by referring to two slum areas in Salvador, Brazil as a case study. We discuss the role of datasets as well as data gaps that hinder COVID-19 responses. In Salvador and other low- and middle-income countries’ (LMICs) cities, local data are available; however, they are not up to date. For example, depending on the source, the population of the study areas in 2020 varies by more than 20%. Thus, EO data integration can help in updating local datasets and in the acquisition of physical parameters of poor urban communities, which are often not systematically collected in local surveys.
- 20 September 2020
- Published by MDPI AG in ISPRS International Journal of Geo-Information
- Vol. 9 (9) , 557
Open AccessThe Spatial Dimension of COVID-19: The Potential of Earth Observation Data in Support of Slum Communities with Evidence from Brazil
The COVID-19 health emergency is impacting all of our lives, but the living conditions and urban morphologies found in poor communities make inhabitants more vulnerable to the COVID-19 outbreak as compared to the formal city, where inhabitants have the resources to follow WHO guidelines. In general, municipal spatial datasets are not well equipped to support spatial responses to health emergencies, particularly in poor communities. In such critical situations, Earth observation (EO) data can play a vital role in timely decision making and can save many people’s lives. This work provides an overview of the potential of EO-based global and local datasets, as well as local data gathering procedures (e.g., drones), in support of COVID-19 responses by referring to two slum areas in Salvador, Brazil as a case study. We discuss the role of datasets as well as data gaps that hinder COVID-19 responses. In Salvador and other low- and middle-income countries’ (LMICs) cities, local data are available; however, they are not up to date. For example, depending on the source, the population of the study areas in 2020 varies by more than 20%. Thus, EO data integration can help in updating local datasets and in the acquisition of physical parameters of poor urban communities, which are often not systematically collected in local surveys.