Abstract
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 crucial aspect of Sustainable Development Goal 11 (SDG): Make cities and human settlements inclusive, safe, resilient and sustainable. Using a Convolutional Neural Network (CNN) and a VGG19 architecture, we experimented with pre-training, self-training, and post-processing using OpenStreetMap to improve classification accuracy. Our results show that combining outputs from both Sentinel-2 and GOB models improves the overall model performance with an F1 score of 81%. The incorporation of post-processing is useful for the final map creation, particularly in correcting for mis-classifications in areas with obvious morphological similarities to deprived areas, such as markets. This approach, which reduces known errors in the model, holds promise for advancing the precision and reliability of urban deprivation mapping over extensive geographical areas.
Original language | English |
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Title of host publication | IGARSS 2024 |
Subtitle of host publication | 2024 IEEE International Geoscience and Remote Sensing Symposium |
Place of Publication | Piscataway, NJ |
Publisher | IEEE |
Pages | 1567-1570 |
Number of pages | 4 |
ISBN (Electronic) | 9798350360325 |
ISBN (Print) | 979-8-3503-6032-5 |
DOIs | |
Publication status | Published - 2024 |
Event | IEEE International Symposium on Geoscience and Remote Sensing, IGARRS 2024: Acting for sustainability and resilience - Athens, Greece Duration: 7 Jul 2024 → 12 Jul 2024 https://www.2024.ieeeigarss.org/index.php |
Publication series
Name | Proceedings International Geoscience and Remote Sensing Symposium (IGARSS) |
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Publisher | IEEE |
Volume | 2024 |
ISSN (Print) | 2153-6996 |
ISSN (Electronic) | 2153-7003 |
Conference
Conference | IEEE International Symposium on Geoscience and Remote Sensing, IGARRS 2024 |
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Abbreviated title | IGARRS 2024 |
Country/Territory | Greece |
City | Athens |
Period | 7/07/24 → 12/07/24 |
Internet address |
Keywords
- Deep Learning (DL)
- Architecture
- Buildings
- Urban areas
- Geoscience and remote sensing
- Internet
- Convolutional neural networks
- Slums
- Open building
- Deprived areas
- 2024 OA procedure