#satellite imagery
12 papers · 1 filter
Finding Change in Satellite Archives from Text: How to Combine Before-and-After Images Efficiently
Simon Roy, Mark Bong, Giovanni Beltrame
The paper studies how to efficiently combine before-and-after satellite images to match natural‑language change queries, comparing attention, state‑space (Mamba), and compressed fu…
Forecasting Land Art Under Climate Scenarios
Alev Cinbarci, Sean Kalaycioglu
The paper builds a two‑stage pipeline to forecast visual complexity of the Spiral Jetty land artwork under future climate scenarios, using climate model outputs, statistical regres…
Large scale cross-regional remote sensing flood monitoring framework for operative mapping and impact analysis
Ilya Novikov, Svetlana Illarionova, Ruslan Dzharkinov +6
The paper proposes an end‑to‑end multimodal deep‑learning framework that combines SAR, multispectral and elevation data to detect flood water surfaces and assess damage across larg…
Meteosat Third Generation imagery improves CNN-based SSI retrieval
Gordei Pribõtkin, Piia Post, Velle Toll
The paper presents a multi-resolution CNN that combines Meteosat Third Generation (MTG) and Second Generation (MSG) satellite images to estimate surface solar irradiance over Eston…
SeasonStereo: Robust Dense Stereo Matching for Multi-Date Satellite Imagery via Generative AI
Ãlvaro DÃaz-Laureano, Roger MarÃ, ElÃas Masquil +2
SeasonStereo is a framework that trains dense stereo matching models on synthetic satellite image pairs with varied seasonal appearances and uses zero‑shot geometric priors from fo…
Robust RPC Bundle Adjustment for Multi-Date Satellite Imagery with Season-Invariant Correspondences
Roger MarÃ, ElÃas Masquil, Xavier Bou +2
The paper introduces a method that refines satellite camera models by using learned, season‑invariant feature matching and global image descriptors to select reliable image pairs,…