相关论文: Detecting Rainfall Onset Using Sky Images
Rainfall prediction at the kilometre-scale up to a few hours in the future is key for planning and safety. But it is challenging given the complex influence of climate change on cloud processes and the limited skill of weather models at…
Effective environmental planning and management to address climate change could be achieved through extensive environmental modeling with machine learning and conventional physical models. In order to develop and improve these models,…
The possibilities of organizing an observation service for solar activity in order to provide space weather forecasting are considered. The most promising at this stage is the creation of a ground-based observation network. Such a network…
The increasing number of Photovoltaic (PV) systems connected to the power grid are vulnerable to the projection of shadows from moving clouds. Global Solar Irradiance (GSI) forecasting allows smart grids to optimize the energy dispatch,…
Sky-image-based solar forecasting using deep learning has been recognized as a promising approach in reducing the uncertainty in solar power generation. However, one of the biggest challenges is the lack of massive and diversified sky image…
High-resolution climatic data are essential to many applications in environmental research. Here we develop a new semi-mechanistic downscaling approach for daily precipitation that incorporates high resolution (30 arc sec) satellite-derived…
Cosmic rays arriving at Earth collide with the upper parts of the atmosphere, thereby inducing extensive air showers. When secondary particles from the cascade arrive at the ground, they are measured by surface detector arrays. We describe…
Lidar sensors are often used in mobile robots and autonomous vehicles to complement camera, radar and ultrasonic sensors for environment perception. Typically, perception algorithms are trained to only detect moving and static objects as…
Rainfall prediction is one of the challenging and uncertain tasks which has a significant impact on human society. Timely and accurate predictions can help to proactively reduce human and financial loss. This study presents a set of…
Recently, as many studies of autonomous vehicles have been achieved for levels 4 and 5, there has been also increasing interest in the advancement of perception, decision, and control technologies, which are the three major aspects of…
Joint evaluation of different meteor observation types support the better understanding of both the meteor phenomenon and the terrestrial atmosphere. Two types of examples are presented in this work, linking ionospheric effects to specific…
A significant source of noise for Imaging Atmospheric Cherenkov Telescopes (IACTs), which are designed to measure air showers caused by astrophysical gamma rays, is optical light emitted from the night sky. This Night Sky Background (NSB)…
Recent advances in Computer Vision and Deep Learning have enabled astonishing results in a variety of fields and applications. Motivated by this success, the SkyCam Dataset aims to enable image-based Deep Learning solutions for short-term,…
We develop an improved sky background estimator which employs optimal filters for both spatial and pixel intensity distributions. It incorporates growth of masks around detected objects and a statistical estimate of the flux from undetected…
An all-sky cloud monitoring system that generates relative opacity maps over many of the world's premier astronomical observatories is described. Photometric measurements of numerous background stars are combined with simultaneous sky…
Knowing the actual precipitation in space and time is critical in hydrological modelling applications, yet the spatial coverage with rain gauge stations is limited due to economic constraints. Gridded satellite precipitation datasets offer…
In this paper we present results from the NEFOCAST project, funded by the Tuscany Region, aiming at detecting and estimating rainfall fields from the opportunistic use of the rain-induced excess attenuation incurred in the downlink channel…
Clouds play a significant role in the fluctuation of solar radiation received by the earth's surface. It is important to study the various cloud properties, as it impacts the total solar irradiance falling on the earth's surface. One of…
The knowledge of type of precipitating cloud is crucial for radar based quantitative estimates of precipitation. We propose a novel model called CloudSense which uses machine learning to accurately identify the type of precipitating clouds…
Very high energy gamma-ray astronomy based on the measurement of air shower particles at ground-level has only recently been established as a viable approach, complementing the well established air Cherenkov technique. This approach…