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Spacecraft observations may conceal how particles really move through near-Earth space

Researchers reveal that spacecraft observations can conceal the true movement of particles in near-Earth space, challenging traditional assumptions about radiation belt dynamics. The study highlights a fundamental challenge for space scientists: different physical processes can produce similar observational evidence.

SourceUniversity of Birmingham·JournalPhysical Review Research·TypeObservational study·DateAug 5, 2026

Regional drought prediction from Sentinel-2 time series using Random Forest, DNN, and 1D-CNN: a case study in Marchfeld, Austria

A study proposes an operational framework combining machine learning models with Sentinel-2 data to estimate agricultural drought conditions in irrigated and non-irrigated maize fields. Deep Neural Network (DNN) achieved the best performance, showing higher prediction accuracy and lower error metrics for non-irrigated fields.

SourceBig Earth Data·JournalBig Earth Data·TypeData/statistical analysis·DateJul 26, 2026

[Research Article] Context-aware landmark recognition in location-based augmented reality: A switching framework with a MobileNet backbone for cultural heritage engagement

A new study proposes a switching-based pervasive augmented reality framework that integrates location-based AR, deep learning, and context-awareness to improve landmark recognition. The framework significantly enhanced detection accuracy compared with conventional LBAR systems, while demonstrating high user satisfaction.

SourceBig Earth Data·JournalBig Earth Data·TypeData/statistical analysis·DateJul 13, 2026

[Research Article] Uncertainty quantification in geospatial AI/ML applications: methods, metrics, and open-source support with an air quality use case

The study systematically evaluates popular Uncertainty Quantification (UQ) methods and metrics for AI/ML-based geospatial applications. It demonstrates that Deep Ensembles and Bayesian Neural Networks achieved the best performance, while highlighting framework-specific differences between TensorFlow and PyTorch.

SourceBig Earth Data·JournalBig Earth Data·TypeData/statistical analysis·DateMay 20, 2026

Horizon Europe’s SWIFTT project concludes with Copernicus-based forest management tool to map, mitigate, and prevent the main threats to EU forests

The SWIFTT platform uses Copernicus Sentinel satellite data and machine learning models to identify tree health changes, detect anomalies, and predict threats like spruce bark beetle outbreaks and wildfires. Foresters can access timely alerts, prioritize inspections, and coordinate clearing of dead wood to protect forests.

If the Laschamps geomagnetic excursion happened today, aviation radiation exposure would be radically altered – with “shielded pockets” in the north

Researchers modelled the structure of the magnetic field and cosmic radiation throughout the Laschamps excursion. The results show that cosmic radiation penetrated the atmosphere at record levels, with regions where it could freely enter irradiating a major fraction of the Earth's atmosphere.

Call for papers: 10th anniversary special issue of Big Earth Data

The Big Earth Data journal is launching a special issue to reflect on its decade-long impact and showcase cutting-edge advancements in big data research. The journal focuses on Earth-related big data, emerging as a flagship platform at the intersection of Earth science, space science, information science, and sustainability science.

SourceBig Earth Data·JournalBig Earth Data·DateFeb 4, 2026

Review article | Towards a Global Ground-Based Earth Observatory (GGBEO): Leveraging existing systems and networks

The study presents a comprehensive roadmap for building an integrated GGBEO to meet the United Nations' Sustainable Development Goals and advance climate science. The system would integrate regional and global ground-based in situ and remote sensing systems, marine, and airborne observational data.

SourceBig Earth Data·JournalBig Earth Data·TypeLiterature review·DateDec 15, 2025

Chemical evidence of ancient life detected in 3.3 billion-year-old rocks: Carnegie Science / PNAS

A team of scientists has discovered chemical evidence of ancient life in 3.3 billion-year-old rocks, doubling the window of time for detecting organic molecules that reveal information about original organisms. The study also found molecular signs of photosynthesis dating back over 800 million years earlier than previously documented.

SourceCarnegie Institution for Science·JournalProceedings of the National Academy of Sciences·TypeData/statistical analysis·DateNov 17, 2025

First observations by the Total Anthropogenic and Natural emissions mapping SpectrOmeter-3 (TANSO-3) onboard the Global Observing SATellite for Greenhouse gases and Water cycle “IBUKI GW” (GOSAT-GW)

The GOSAT-GW satellite has successfully launched with the TANSO-3 sensor, confirming its proper operation. The first observation by TANSO-3 provided spectral absorption data for carbon dioxide, methane, and nitrogen dioxide, enabling the calculation of greenhouse gas concentrations in the atmosphere.

All of the biggest U.S. cities are sinking

A new study reveals that 25 of the 28 most populous US cities are sinking, with some areas subsiding at rates of over 5 millimeters per year. The primary cause is massive ongoing groundwater extraction, which can lead to stresses on infrastructure and buildings.

SourceColumbia Climate School·JournalNature Cities·TypeImaging analysis·DateMay 8, 2025

Global sea level very likely to rise between 0.5 and 1.9 meters by 2100 under a high-emissions scenario, finds NTU Singapore-led study using new projection method

A new study projects global sea-level rise between 0.5 and 1.9 meters by 2100 under a high-emissions scenario, with the very likely range being 90% probability for the event to occur. The fusion approach combines strengths of existing models with expert opinions, offering a clearer picture of future sea-level rise.

SourceNanyang Technological University·JournalEarth's Future·TypeComputational simulation/modeling·DateJan 26, 2025

Innovation in land use and land cover classification for landslide analysis

A new method combining Random Forest and Compound Maximum a Posteriori algorithms reduces invalid transitions and improves LULC classification, correcting 99.92 km2 of errors. The study outperforms traditional methods, especially in detecting changes in mountainous regions.

SourceEscuela Superior Politecnica del Litoral·JournalRemote Sensing Applications Society and Environment·TypeComputational simulation/modeling·DateDec 18, 2024

Going ‘back to the future’ to forecast the fate of a dead Florida coral reef

Researchers reconstructed a Late Holocene-aged subfossil coral death assemblage and compared it to modern reefs in Southeast Florida. The study reveals significant differences in coral composition between the two periods, suggesting that modern reefs may not be able to support range expansions of temperature-sensitive species.

SourceFlorida Atlantic University·JournalCommunications Earth & Environment·TypeObservational study·DateMar 28, 2024

Earth as a test object

The study, published in The Astrophysical Journal, tested the future LIFE mission's capabilities on real spectra using data from NASA's Aqua Earth observation satellite. It demonstrated that a space telescope like LIFE could detect signs of a temperate, habitable world on Earth-like exoplanets.

SourceETH Zurich·JournalThe Astrophysical Journal·DateFeb 27, 2024

Integrated design of Global Ocean Observing System essential to monitor climate change

The study found that different instrumental systems in the Global Ocean Observing System (GOOS) complement each other and are essential for accurately monitoring ocean warming. The GOOS, which includes platforms such as free drifting instrumented floats, mooring buoys, and autonomous pinniped data, provides a comprehensive view of ocea...

SourceOcean-Land-Atmosphere Research (OLAR)·JournalOcean-Land-Atmosphere Research·TypeObservational study·DateJan 29, 2024

In many major crop regions, workers plant and harvest in spiraling heat and humidity

A global study reveals that farmworkers in major crop regions are facing increasing exposure to extreme heat and humidity, which can impair their ability to function. The most affected crops are rice and maize, with nearly half of the world's rice cropland already experiencing extreme conditions during the planting and harvest seasons.

SourceColumbia Climate School·JournalEnvironmental Research Communications·TypeMeta-analysis·DateNov 20, 2023