arXiv:2606. 18661v1 Announce Type: cross Abstract: Intelligent landslide hazard interpretation is critical for disaster prevention, yet current paradigms struggle to simultaneously extract visual features and high-level geoscientific semantics, while general-purpose vision-language models (VLMs) suffer from perceptual limitations and domain hallucinations in complex geological scenarios.
By Chengfu Liu, Dongyang Hou, Junwu Xiang, Cheng Yang, Xuezhi Cui, Zeyuan Wang, Liangtian Liu, Zelang Miao
arXiv:2609.00712v1 Announce Type: new
Abstract: Landslides are widespread geological hazards, yet their automated detection and mapping in remote sensing imagery remain challenging because of their i...
By Yuanchao Su, Lianru Gao, Mengying Jiang, Jiangyi Chen, Jiaxin Cheng, Yicong Zhou
arXiv:2602.01163v2 Announce Type: replace
Abstract: Safe UAV emergency landing requires more than just identifying flat terrain; it demands understanding complex semantic risks (e.g., crowds, tempora...
By Chunliang Hua, Lei Zhang, Jiayang Sun, Chunlan Zeng, Xiao Hu
The paper introduces GRDisaster, a multi-task geospatial reasoning framework that leverages vision‑language models to interpret, geolocalize, and assess damage in crowdsourced disaster imagery. It builds on a new benchmark dataset of 26,340 images from PhotoMappers, linking volunteer geographic information, street‑view imagery, and remote sensing data across multiple disaster events from 2018 to 2024. GRDisaster combines deterministic and probabilistic cross‑view geolocalization with multi‑view fusion, and introduces spatial reasoning indicators to validate cross‑view matches and quantify disaster severity using expert‑verified annotations.
By Wenping Yin, Fabian Desuer, Ziqi Liu, Naixia Mou, Weijia Li, Pedram Ghamisi, Xiao Xiang Zhu, Hao Li
arXiv:2505.15147v3 Announce Type: replace
Abstract: Remote sensing images (RSIs) capture both natural and human-induced changes on the Earth's surface. Semantic segmentation (SS) of RSIs enables the...
By Quanwei Liu, Tao Huang, Jiaqi Yang, Wei Xiang
arXiv:2609.00046v1 Announce Type: cross
Abstract: Rapid and reliable disaster mapping of impacted areas, damaged infrastructure, and affected populations is essential for emergency response and recov...
By Yifan Yang, Lei Zou