Passive LWIR hyperspectral ranging estimates distance in low-light scenes by exploiting atmospheric absorption in thermal radiance. The proposed TEDA method decouples range estimation from temperature–emissivity inversion, using a baseline estimator and transmittance extraction to recover atmospheric transmittance, then matching it to sensor-domain models for each candidate distance. TEDA reduces ranging bias, yields mean range estimates closer to LiDAR medians, and achieves a 20‑fold speedup over reference-range joint inversion.
arXiv:2608. 07580v1 Announce Type: cross Abstract: In this work, we present a wildfire temperature retrieval framework for VSWIR imaging spectroscopy data, employed on data from NASA's Airborne Visible Infrared Imaging Spectrometer (AVIRIS-3).
arXiv:2606. 08324v1 Announce Type: cross Abstract: Passive long-wave infrared (LWIR) hyperspectral imaging under a standoff geometry depends on atmospheric absorption and emission, as well as reflected radiance, thus making atmospheric compensation essential to get knowledge of a target of interest.
The paper presents a dual‑encoder Transformer model for estimating Planetary Boundary Layer Height (PBLH) from satellite radiances, addressing challenges of multimodal, spatially incomplete data. It benchmarks eight different approaches, analyzes model reliance via grouped Shapley decomposition, and demonstrates that the proposed architecture achieves a mean absolute error of 155.8 m on a global test set, outperforming all baselines. On out‑of‑distribution data from the TEAMx campaign, the model attains 165.3 m MAE, better than a pixel‑wise baseline trained on the same data.
arXiv:2606. 19943v1 Announce Type: cross Abstract: Hyperspectral infrared observations are an important data source for numerical weather prediction (NWP) because they provide rich information on the vertical structure of atmospheric temperature and humidity.
The paper presents a method to replace traditional window-based tracking in geostationary atmospheric motion vector (AMV) stereo matching with deep optical flow, enabling efficient and accurate retrieval of dense three‑dimensional wind fields. A stereo teacher model is distilled into a single‑satellite student model that emulates the teacher’s uncertainty estimates, allowing global wind generation from full‑disk GEO imagery. Validation against radiosondes, operational AMVs, ERA5 reanalysis, and EarthCARE cloud profiles shows that the stereo winds outperform operational AMVs in water‑vapor bands while performing slightly worse in the long‑wave infrared band.
arXiv:2508.13977v4 Announce Type: replace Abstract: Depth estimation is a fundamental component of spatial perception for autonomous driving and other unmanned systems operating in open urban environ...
arXiv:2609.12521v1 Announce Type: new Abstract: Unmanned aerial vehicle facade inspection can combine red, green, and blue (RGB) imagery with thermal measurements to screen surface and subsurface ano...
arXiv:2509. 04991v2 Announce Type: replace-cross Abstract: Land surface temperature (LST) is a fundamental physical variable in land-atmosphere interactions, surface energy budgets, and climate processes.
arXiv:2608. 14645v1 Announce Type: new Abstract: Studying climate change requires reducing uncertainties in CO2 and CH4 emission estimates to better distinguish anthropogenic from natural sources, which motivates spaceborne measurements with improved revisit frequency and spatial coverage.
The paper presents a physics-informed neural network (PINN) that accelerates multilayer spectral inversion (MLSI) of solar chromospheric lines Hα 6562.8 Å and Ca II 8542.1 Å. The PINN predicts MLSI parameters from observed line profiles and uses a differentiable forward model to synthesize spectra, trained in two stages—first with spectral reconstruction loss, then fine‑tuned with conventional MLSI results on a single reference image. Applied to Fast Imaging Solar Spectrograph data, the method reproduces key spatial structures and achieves a 12–60× speedup, processing a raster in 5–15 s versus 3–5 min for traditional MLSI.
arXiv:2512. 04966v2 Announce Type: replace-cross Abstract: Accurate channel state information (CSI) underpins reliable and efficient wireless communication.
The Meteosat Third Generation (MTG) Flexible Combined Imager (FCI) offers new opportunities for tropospheric temperature and humidity profiling, at higher spatio-temporal resolutions and expanded spec...