相关论文: Site testing at astronomical sites: seeing evaluat…
The study of absorptions along the lines of sight to bright high-$z$ QSOs is an invaluable cosmological tool that provides a wealth of information on the inter-/circum-galactic medium, Dark Matter, primordial elements, reionization,…
High-resolution rainfall estimates from satellite and reanalysis sources (SRE) could play a major role in improving climate services for agriculture. This is particularly relevant in regions that rely on rain-fed farming but lack a dense…
Nighttime lights satellite imagery has been used for decades as a uniform, global source of data for studying a wide range of socioeconomic factors. Recently, another more terrestrial source is producing data with similarly uniform global…
The UN Sustainable Development Goals allude to the importance of infrastructure quality in three of its seventeen goals. However, monitoring infrastructure quality in developing regions remains prohibitively expensive and impedes efforts to…
We present a procedure for assessing the urban exposure and seismic vulnerability that integrates LiDAR data with aerial and satellite images. It comprises three phases: first, we segment the satellite image to divide the study area into…
Satellite data are increasingly used to measure economic activity, yet port-level trade remains largely unmeasured from space. This paper combines synthetic aperture radar imagery, nighttime lights, and port characteristics to measure…
Cosmic rays originating from extraterrestrial sources are permanently arriving at Earth atmosphere, where they produce up to billions of secondary particles. The analysis of the secondary particles reaching to the surface of the Earth may…
An attitude of satellite is not always static, sometimes it moves randomly and the antenna pointing of satellite is harder to achieve line of sight communication to other satellite when it is outage by tumbling effect. In order to determine…
Image matching is a fundamental problem in Computer Vision with direct applications in robotics, remote sensing, and geospatial data analysis. We present an analytical and experimental evaluation of classical local feature-based image…
Radio Astronomy is undergoing a renaissance, as the next-generation of instruments provides a massive leap forward in collecting area and therefore raw sensitivity. However, to achieve this theoretical level of sensitivity in the science…
Ahead-of-time forecasting of the output power of power plants is essential for the stability of the electricity grid and ensuring uninterrupted service. However, forecasting renewable energy sources is difficult due to the chaotic behavior…
Solar forecasting from ground-based sky images has shown great promise in reducing the uncertainty in solar power generation. With more and more sky image datasets open sourced in recent years, the development of accurate and reliable deep…
We developed a code that estimates distances to stars using measured spectroscopic and photometric quantities. We employ a Bayesian approach to build the probability distribution function over stellar evolutionary models given these data,…
The presented study is an eye tracking experiment for high-resolution satellite (HRS) images. The reported experiment explores the Area Of Interest (AOI) based analysis of eye fixation data for complex HRS images. The study reflects the…
The number of satellites on low orbit has dramatically increased over the past years, raising concerns among the astronomical community about their impact on observations. Spectroscopic observations represent a large fraction of…
Distributed fiber sensing based on correlation-aided phase-sensitive optical time domain reflectometry is presented. The focus is on correlation as an enabler for high spatial resolution. Results from different applications are presented.
Advanced knowledge of the detailed atmospheric properties of both the future sites of the Cherenkov Telescope Array is essential in preparation of the arrival of the first scientific data. Meteorological variables are studied using a…
A demanding challenge in atmospheric research is the night-time characterization of aerosols using passive techniques, that is, by extracting information from scattered light that has not been emitted by the observer. Satellite observations…
The recent advances in machine learning and the availability of free and open big Earth data (e.g., Sentinel missions), which cover large areas with high spatial and temporal resolution, have enabled many agriculture monitoring…
In this paper, we present an open-source measurement platform designed to characterize the performance of commercial cellular (Verizon, a major US provider) and LEO satellite (Starlink) networks through real-world flight tests in rural…