Related papers: Developing a Thailand solar irradiance map using H…
Pedestrian heat exposure is a critical health risk in dense tropical cities, yet standard routing algorithms often ignore micro-scale thermal variation. Hot H\'em is a GeoAI workflow that estimates and operationalizes pedestrian heat…
Urban heat islands (UHIs) are often accentuated during heat waves (HWs) and pose a public health risk. Mitigating UHIs requires urban planners to first estimate how urban heat is influenced by different land use types (LUTs) and drivers…
When a territory is poorly instrumented, geostationary satellites data can be useful to predict global solar radiation. In this paper, we use geostationary satellites data to generate 2-D time series of solar radiation for the next hour.…
Several passive microwave satellites orbit the Earth and measure rainfall. These measurements have the advantage of almost full global coverage when compared to surface rain gauges. However, these satellites have low temporal revisit and…
We present lightweight and efficient architectures to detect weather conditions from RGB images, predicting the weather type (sunny, rain, snow, fog) and 11 complementary attributes such as intensity, visibility, and ground condition, for a…
Monitoring vegetation dynamics is crucial for addressing global environmental challenges like degradation and deforestation, but traditional remote sensing methods are often complex and resource-intensive. To overcome these barriers, we…
The global transition towards cleaner and more sustainable energy production is a major challenge. We present an innovative solution by utilizing smartphone light sensors to measure direct normal solar irradiance, the primary component of…
We present sensitivity estimates for point and resolved astronomical sources for the current design of the InfraRed Imaging Spectrograph (IRIS) on the future Thirty Meter Telescope (TMT). IRIS, with TMT's adaptive optics system, will…
Many remote sensing applications employ masking of pixels in satellite imagery for subsequent measurements. For example, estimating water quality variables, such as Suspended Sediment Concentration (SSC) requires isolating pixels depicting…
Solar flare prediction plays an important role in understanding and forecasting space weather. The main goal of the Helioseismic and Magnetic Imager (HMI), one of the instruments on NASA's Solar Dynamics Observatory, is to study the origin…
Accurate background estimation is essential for spectral and temporal analysis in astrophysics. In this work, we construct the in-orbit background model for the High-Energy Telescope (HE) of the Hard X-ray Modulation Telescope (dubbed as…
Solar radio flux along with geomagnetic indices are important indicators of solar activity and its effects. Extreme solar events such as flares and geomagnetic storms can negatively affect the space environment including satellites in…
We introduce GAIA (Geospatial Artificial Intelligence for Atmospheres), a hybrid self-supervised geospatial foundation model that fuses Masked Autoencoders (MAE) with self-distillation with no labels (DINO) to generate semantically rich…
A study for the comprehensive information of current UV exposure for the area of Germany, based on the method for near real time calculation of UV Index maps used in the framework of the Austrian UV Monitoring Network, is presented. For the…
Deep learning is revolutionizing the mapping industry. Under lightweight human curation, computer has generated almost half of the roads in Thailand on OpenStreetMap (OSM) using high-resolution aerial imagery. Bing maps are displaying 125…
Recent observations by the Event Horizon Telescope (EHT) of supermassive black holes M87* and Sgr A* offer valuable insights into their spacetime properties and astrophysical conditions. Utilizing a library of model images (~2 million for…
The forecast accuracy of machine learning (ML) weather prediction models is improving rapidly, leading many to speak of a "second revolution in weather forecasting". With numerous methods being developed and limited physical guarantees…
This paper presents initial values of global and diffuse luminous efficacy at Saint-Pierre (Reunion Island). Firstly, data used were measured for a period of 6 months, from February to June 2008. During this period, all defined day-types…
Advancing probabilistic solar forecasting methods is essential to supporting the integration of solar energy into the electricity grid. In this work, we develop a variety of state-of-the-art probabilistic models for forecasting solar…
Incomplete satellite-based precipitation presents a significant challenge in global monitoring. For example, the Global Satellite Mapping of Precipitation (GSMaP) from JAXA suffers from substantial missing regions due to the orbital…