Zobrazeno 1 - 10
of 153
pro vyhledávání: '"Nascetti, Andrea"'
Accurate estimation of building heights is essential for urban planning, infrastructure management, and environmental analysis. In this study, we propose a supervised Multimodal Building Height Regression Network (MBHR-Net) for estimating building he
Externí odkaz:
http://arxiv.org/abs/2307.01378
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 information, they are often hindered by cloud cover, limiting their usa
Externí odkaz:
http://arxiv.org/abs/2306.08935
Accurate urban maps provide essential information to support sustainable urban development. Recent urban mapping methods use multi-modal deep neural networks to fuse Synthetic Aperture Radar (SAR) and optical data. However, multi-modal networks may r
Externí odkaz:
http://arxiv.org/abs/2304.05080
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 increasing in recent years. Earth observations are an invaluable source for as
Externí odkaz:
http://arxiv.org/abs/2212.03675
Building change detection is essential for monitoring urbanization, disaster assessment, urban planning and frequently updating the maps. 3D structure information from airborne light detection and ranging (LiDAR) is very effective for detecting urban
Externí odkaz:
http://arxiv.org/abs/2204.12535
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 Siamese Difference network that not only predicts changes with the differe
Externí odkaz:
http://arxiv.org/abs/2204.12202
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 response and disaster management. In this work, we propose a flood detecti
Externí odkaz:
http://arxiv.org/abs/2204.09387
Publikováno v:
In International Journal of Applied Earth Observation and Geoinformation February 2024 126
Publikováno v:
In Automation in Construction December 2023 156
Publikováno v:
In Remote Sensing Applications: Society and Environment November 2023 32