6 citations · 8 across the 6 of their papers we have counts for
6 papers
PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models
Valerio Marsocci, Yuru Jia, Georges Le Bellier +12
Geospatial Foundation Models (GFMs) have emerged as powerful tools for extracting representations from Earth observation data, but their evaluation remains inconsistent and narrow.…
Continuous Urban Change Detection from Satellite Image Time Series with Temporal Feature Refinement and Multi-Task Integration
Sebastian Hafner, Heng Fang, Hossein Azizpour +1
Urbanization advances at unprecedented rates, leading to negative environmental and societal impacts. Remote sensing can help mitigate these effects by supporting sustainable devel…
Multi-Modal Deep Learning for Multi-Temporal Urban Mapping With a Partly Missing Optical Modality
Sebastian Hafner, Yifang Ban
This paper proposes a novel multi-temporal urban mapping approach using multi-modal satellite data from the Sentinel-1 Synthetic Aperture Radar (SAR) and Sentinel-2 MultiSpectral I…
Investigating Imbalances Between SAR and Optical Utilization for Multi-Modal Urban Mapping
Sebastian Hafner, Yifang Ban, Andrea Nascetti
Accurate urban maps provide essential information to support sustainable urban development. Recent urban mapping methods use multi-modal deep neural networks to fuse Synthetic Aper…
Mapping Urban Population Growth from Sentinel-2 MSI and Census Data Using Deep Learning: A Case Study in Kigali, Rwanda
Sebastian Hafner, Stefanos Georganos, Theodomir Mugiraneza +1
To better understand current trends of urban population growth in Sub-Saharan Africa, high-quality spatiotemporal population estimates are necessary. While the joint use of remote…
Urban Change Detection Using a Dual-Task Siamese Network and Semi-Supervised Learning
Sebastian Hafner, Yifang Ban, Andrea Nascetti
In this study, a Semi-Supervised Learning (SSL) method for improving urban change detection from bi-temporal image pairs was presented. The proposed method adapted a Dual-Task Siam…