Impact of digital twins and metaverse on cities: History, current situation, and application perspectives

Z Lv, WL Shang, M Guizani - Applied Sciences, 2022 - mdpi.com
To promote the expansion and adoption of Digital Twins (DTs) in Smart Cities (SCs), a
detailed review of the impact of DTs and digitalization on cities is made to assess the …

AI security for geoscience and remote sensing: Challenges and future trends

Y Xu, T Bai, W Yu, S Chang… - … and Remote Sensing …, 2023 - ieeexplore.ieee.org
Recent advances in artificial intelligence (AI) have significantly intensified research in the
geoscience and remote sensing (RS) field. AI algorithms, especially deep learning-based …

Using machine learning and remote sensing to track land use/land cover changes due to armed conflict

S Mhanna, LJS Halloran, F Zwahlen, AH Asaad… - Science of The Total …, 2023 - Elsevier
Armed conflicts have detrimental impacts on the environment, including land systems. The
prevailing understanding of the relation between Land Use/Land Cover (LULC) and armed …

[HTML][HTML] Instance segmentation of standing dead trees in dense forest from aerial imagery using deep learning

A Sani-Mohammed, W Yao, M Heurich - ISPRS Open Journal of …, 2022 - Elsevier
Mapping standing dead trees, especially, in natural forests is very important for evaluation of
the forest's health status, and its capability for storing Carbon, and the conservation of …

[HTML][HTML] Spatially transferable dwelling extraction from Multi-Sensor imagery in IDP/Refugee Settlements: A meta-Learning approach

GW Gella, D Tiede, S Lang, L Wendit, Y Gao - International Journal of …, 2023 - Elsevier
Dwelling information is very important for various applications in humanitarian emergency
response. For this, Earth observation is crucial to have spatially explicit and temporally …

Comparing OBIA-Generated Labels and Manually Annotated Labels for Semantic Segmentation in Extracting Refugee-Dwelling Footprints

Y Gao, S Lang, D Tiede, GW Gella, L Wendt - Applied Sciences, 2022 - mdpi.com
Refugee-dwelling footprints derived from satellite imagery are beneficial for humanitarian
operations. Recently, deep learning approaches have attracted much attention in this …

[HTML][HTML] Automatic impervious surface mapping in subtropical China via a terrain-guided gated fusion network

Z Li, A Zhang, G Sun, Z Han, X Jia - International Journal of Applied Earth …, 2024 - Elsevier
Large-scale, high-resolution and multi-temporal impervious surface maps from remote
sensing are essential for socioeconomic and environmental studies. However, in complex …

Mapping Dwellings in IDP/Refugee Settlements Using Deep Learning

O Ghorbanzadeh, A Crivellari, D Tiede, P Ghamisi… - Remote Sensing, 2022 - mdpi.com
The improvement in computer vision, sensor quality, and remote sensing data availability
makes satellite imagery increasingly useful for studying human settlements. Several …

Using spatial video and deep learning for automated mapping of ground-level context in relief camps

J Ajayakumar, AJ Curtis, FM Maisha, S Bempah… - International Journal of …, 2024 - Springer
Background The creation of relief camps following a disaster, conflict or other form of
externality often generates additional health problems. The density of people in a highly …

Unsupervised Domain Adaptation for Instance Segmentation: Extracting Dwellings in Temporary Settlements Across Various Geographical Settings

GW Gella, C Pelletier, S Lefèvre… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Dwelling information is essential for humanitarian emergency response during or in the
aftermath of disasters, especially in temporary settlement areas hosting forcibly displaced …