Related papers: AODisaggregation: toward global aerosol vertical p…
The global phenomenon of forest degradation is a pressing issue with severe implications for climate stability and biodiversity protection. In this work we generate Bayesian updating deforestation detection (BUDD) algorithms by…
Most contributions on Few-Shot Object Detection (FSOD) evaluate their methods on natural images only, yet the transferability of the announced performance is not guaranteed for applications on other kinds of images. We demonstrate this with…
Ammonia (NH3) emissions significantly contribute to atmospheric pollution, yet discrepancies exist between bottom-up inventories and satellite-constrained top-down estimates, with the latter typically one-third higher. This study quantifies…
Aerosols from natural and antropogenic sources are one of the atmospheric components that have the largest spacial-temporal variability, depending on the type (land or ocean) surface, human activity and climatic conditions (mainly…
The ability of the deep learning model to recognize when a sample falls outside its learned distribution is critical for safe and reliable deployment. Recent state-of-the-art out-of-distribution (OOD) detection methods leverage activation…
Nighttime monitoring of the aerosol content of the lower atmosphere is a challenging task, because appropriate reference natural light sources are lacking. Here we show that the anthropogenic night sky brightness due to city lights can be…
Organic aerosols (OA) comprise a major fraction of atmospheric particulate matter and frequently contain acidic species, yet their contribution to overall aerosol acidity has not been explicitly considered in global climate models. We…
Aerosol-cloud interactions (ACI) pose the largest uncertainty for climate projections. Among many challenges of understanding ACI, the question of whether ACI is deterministic or stochastic has not been explicitly formulated and asked. Here…
Geostationary observations offer the unique opportunity to resolve the diurnal cycle of the Earth's Radiation Budget at the top of the atmosphere (TOA), crucial for climate-change studies. However, a drawback of the continuous temporal…
Interstellar medium widely exists in the universe at multi-scales. In this study, we introduce the {\it Multi-scale Decomposition Reconstruction} method, an equation-based model designed to derive width maps of interstellar medium…
Optical satellites, with their diverse band layouts and ground sampling distances, supply indispensable evidence for tasks ranging from ecosystem surveillance to emergency response. However, significant discrepancies in band composition and…
A serious problem in image classification is that a trained model might perform well for input data that originates from the same distribution as the data available for model training, but performs much worse for out-of-distribution (OOD)…
Detecting out-of-distribution (OOD) data has become a critical component in ensuring the safe deployment of machine learning models in the real world. Existing OOD detection approaches primarily rely on the output or feature space for…
Three-dimensional (3D) kinetic maps of the Milky Way interstellar medium are an essential tool in studies of its structure and of star formation. We aim to assign radial velocities to Galactic interstellar clouds now spatially localized…
As one of the most popular applications of lidar systems, the atmospheric visibility is defined to be inversely proportional to the atmospheric extinction coefficient at 0.55 um. Since the laser at 1.5 um shows the highest maximum…
Out-of-distribution (OOD) detection identifies test samples that differ from the training data, which is critical to ensuring the safety and reliability of machine learning (ML) systems. While a plethora of methods have been developed to…
In this paper, we present a case study that performs an unmanned aerial vehicle (UAV) based fine-scale 3D change detection and monitoring of progressive collapse performance of a building during a demolition event. Multi-temporal oblique…
Context: State of the art quantitative spectroscopy of OB-stars compares synthetic spectra (calculated by means of 1D, spherically symmetric computer codes) with observations. Certain stellar atmospheres, however, show strong deviations…
3D anomaly detection plays a crucial role in monitoring parts for localized inherent defects in precision manufacturing. Embedding-based and reconstruction-based approaches are among the most popular and successful methods. However, there…
We study the variability of major atmospheric absorption features in the disk-integrated spectra of the Earth with future application to Earth-analogs in mind, concentrating on the diurnal timescale. We first analyze observations of the…