27 citations · 34 across the 9 of their papers we have counts for
9 papers · 1 filter
A CNN regression model to estimate buildings height maps using Sentinel-1 SAR and Sentinel-2 MSI time series
Ritu Yadav, Andrea Nascetti, Yifang Ban
Accurate estimation of building heights is essential for urban planning, infrastructure management, and environmental analysis. In this study, we propose a supervised Multimodal Bu…
Context-Aware Change Detection With Semi-Supervised Learning
Ritu Yadav, Andrea Nascetti, Yifang Ban
Change detection using earth observation data plays a vital role in quantifying the impact of disasters in affected areas. While data sources like Sentinel-2 provide rich optical i…
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…
Unsupervised Flood Detection on SAR Time Series
Ritu Yadav, Andrea Nascetti, Hossein Azizpour +1
Human civilization has an increasingly powerful influence on the earth system. Affected by climate change and land-use change, natural disasters such as flooding have been increasi…
Building Change Detection using Multi-Temporal Airborne LiDAR Data
Ritu Yadav, Andrea Nascetti, Yifang Ban
Building change detection is essential for monitoring urbanization, disaster assessment, urban planning and frequently updating the maps. 3D structure information from airborne lig…
Attentive Dual Stream Siamese U-net for Flood Detection on Multi-temporal Sentinel-1 Data
Ritu Yadav, Andrea Nascetti, Yifang Ban
Due to climate and land-use change, natural disasters such as flooding have been increasing in recent years. Timely and reliable flood detection and mapping can help emergency resp…
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…