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By USH
In December 2024, reports began surfacing about strange events involving flashing streetlights house and building lights. These incidents, initially dismissed as isolated cases, have now been observed on a larger scale, spanning countries such as the U.S., Canada, and the UK.
Some observers theorize that drones or unidentified orbs might be responsible. These objects could emit electromagnetic interference, disrupting electrical systems and causing lights to flicker. However, no concrete evidence has linked these phenomena to drone activity.
Others suggest the lights could be a result of hackers targeting the power grid. Cybercriminals might be testing infrastructure vulnerabilities. While plausible, no definitive proof has emerged to support this explanation.
A more unconventional theory suggests that the flashing lights are a result of a phenomenon known as Streetlight Interference (SLI). Proponents argue that certain individuals, nicknamed "SLIders," possess psychic or psychokinetic abilities that unintentionally influence lighting systems. SLI remains scientifically unverified, with no successful replication in controlled settings.
Some experts believe it might be mechanical faults in the electrical systems or or fluctuations in the power supply. However, this theory seems unlikely due to the widespread and simultaneous nature of the phenomenon, which has been reported across multiple countries, suggesting it is not a localized issue.
Or is this phenomenon linked to extraterrestrial activity? Some argue that aliens might use electromagnetic propulsion systems, potentially interfering with electrical systems, akin to the effects portrayed in films like 'Close Encounters of the Third Kind'.
Could the cause of these flashing lights be a harbinger of an impending global or cosmic event, or might it stem from something entirely beyond our understanding?
The two videos below show, besides the on going mysterious drones/UFO/orb sightings, several locations where street lights are flashing.
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By NASA
6 Min Read NASA International Space Apps Challenge Announces 2024 Global Winners
The 2024 NASA Space Apps Challenge was hosted at 485 events in 163 countries and territories. Credits: NASA NASA Space Apps has named 10 global winners, recognizing teams from around the world for their exceptional innovation and collaboration during the 2024 NASA Space Apps Challenge. As the largest annual global hackathon, this event invites participants to leverage open data from NASA and its space agency partners to tackle real-world challenges on Earth and in space.
Last year’s hackathon welcomed 93,520 registered participants, including space, science, technology, and storytelling enthusiasts of all ages. Participants gathered at local events in 163 countries and territories, forming teams to address the challenges authored by NASA subject matter experts. These challenges included subjects/themes/questions in ocean ecosystems, exoplanet exploration, Earth observation, planetary seismology, and more.
The 2024 Global Winners were determined out of 9,996 project submissions and judged by subject matter experts from NASA and space agency partners.
“These 10 exceptional teams created projects that reflect our commitment to understanding our planet and exploring beyond, with the potential to transform Earth and space science for the benefit of all,” said Dr. Keith Gaddis, NASA Space Apps Challenge program scientistat NASA Headquarters in Washington. “The NASA Space Apps Challenge showcases the potential of every idea and individual. I am excited to see how these innovators will shape and inspire the future of science and exploration.”
You can watch the Global Winners Announcement here to meet these winning teams and learn about the inspiration behind their projects.
2024 NASA Space Apps Challenge Global Winners
Best Use of Science Award: WMPGang
Team Members: Dakota C., Ian C., Maximilian V., Simon S.
Challenge: Create an Orrery Web App that Displays Near-Earth Objects
Country/Territory: Waterloo,Canada
Using their skills in programming, data analysis, and visualization, WMPGang created a web app that identifies satellite risk zones using real-time data on Near-Earth Objects and meteor streams.
Learn more about WMPGang’s SkyShield: Protecting Earth and Satellites from Space Hazards project Best Use of Data Award: GaamaRamma
Team Members: Aakash H., Arun G., Arthur A., Gabriel A., May K.
Challenge: Leveraging Earth Observation Data for Informed Agricultural Decision-Making
Country/Territory: Universal Event, United States
GaamaRamma’s team of tech enthusiasts aimed to create a sustainable way to help farmers efficiently manage water availability in the face of drought, pests, and disease.
Learn more about GaamaRamma’s Waterwise project Best Use of Technology Award: 42 QuakeHeroes
Team Members: Alailton A., Ana B., Gabriel C., Gustavo M., Gustavo T., Larissa M.
Challenge: Seismic Detection Across the Solar System
Country/Territory: Maceió, Brazil
Team 42 QuakeHeroes employed a deep neural network model to identify the precise locations of seismic events within time-series data. They used advanced signal processing techniques to isolate and analyze unique components of non-stationary signals.
Learn more about 42 QuakeHeroes’ project Galactic Impact Award: NVS-knot
Team Members: Oksana M., Oleksandra M., Prokipchyn Y., Val K.
Challenge: Leveraging Earth Observation Data for Informed Agricultural Decision-Making
Country/Territory: Kyiv, Ukraine
The NVS-knot team assessed planting conditions using surface soil moisture and evapotranspiration data, then created an app that empowers farmers to manage planting risks.
Learn more about NVS-knot’s 2plant | ! 2plant project Best Mission Concept Award: AsturExplorers
Team Members: Coral M., Daniel C., Daniel V., Juan B., Samuel G., Vladimir C.
Challenge: Landsat Reflectance Data: On the Fly and at Your Fingertips
Country/Territory: Gijón, Spain
AsturExplorers created Landsat Connect, a web app that provides a simple, intuitive way to track Landast satellites and access Landsat surface reflectance data. The app also allows users to set a target location and receive notifications when Landsat satellites pass over their area.
Learn more about AsturExplorers’ Landsat Connect project Most Inspirational Award: Innovisionaries
Team Members: Rikzah K., Samira K., Shafeeqa J., Umamah A.
Challenge: SDGs in the Classroom
Country/Territory: Sharjah, United Arab Emirates
Innovisionaries developed Eco-Metropolis to inspire sustainability through gameplay. This city-building game engages players in making critical urban planning and resource management decisions based on real-world environmental data.
Learn more about Innovisionaries’ Eco-Metropolis: Sustainable City Simulation project Best Storytelling Award: TerraTales
Team Members: Ahmed R., Fatma E., Habiba A., Judy A., Maya M.
Challenge: Tell Us a Climate Story!
Country/Territory: Cairo, Egypt
TerraTales shared stories of how Earth’s changing climate affects three unique regions: Egypt, Brazil, and Germany. The web app also features an artificial intelligence (AI) model for climate forecasting and an interactive game to encourage users to make eco-friendly choices.
Learn more about TerraTale’s project Global Connection Award: Asteroid Destroyer
Team Members: Kapeesh K., Khoi N., Sathyajit L., Satyam S.
Challenge: Navigator for the Habitable Worlds Observatory (HWO): Mapping the Characterizable Exoplanets in our Galaxy
Country/Territory: Saskatoon, Canada
Team Asteroid Destroyer honed in on exoplanets, utilizing data processing and machine learning techniques to map exoplanets based on size, temperature, and distance.
Learn more about Asteroid Destroyer’s project Art & Technology Award: Connected Earth Museum
Team Members: Gabriel M., Luc R., Lucas R., Mattheus L., Pedro C., Riccardo S.
Challenge: Imagine our Connected Earth
Country/Territory: Campinas, Brazil
Team Connected Earth Museum created an immersive virtual museum experience to raise awareness of Earth’s changing climate. An AI host guides users through an interactive gallery featuring 3D and 2D visualizations, including a time series on Earth and ocean temperatures, population density, wildfires, and more.
Learn more about Connected Earth Museums’ project Local Impact Award: Team I.O.
Team Members: Frank R., Jan K., Raphael R., Ryan Z., Victoria M.
Challenge: Community Mapping
Country/Territory: Florianópolis, Brazil
Team I.O. bridges the gap between complex Geographic Information Systems data and user-friendly communication, making critical environmental information accessible to everyone, regardless of technical expertise.
Learn more about Team I.O.’s G.R.O.W. (Global Recovery and Observation of Wildfires) project Want to take part in the 2025 NASA Space Apps Challenge? Mark your calendars for October 4 and 5! Registration will open in July. At that time, participants will be able to register for a local event hosted by NASA Space Apps leads from around the world. You can stay connected with NASA Space Apps on Facebook, Instagram, and X.
Space Apps is funded by NASA’s Earth Science Division through a contract with Booz Allen Hamilton, Mindgrub, and SecondMuse.
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Last Updated Jan 16, 2025 Related Terms
STEM Engagement at NASA Earth View the full article
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By NASA
3 Min Read NASA Scientists Find New Human-Caused Shifts in Global Water Cycle
Cracked mud and salt on the valley floor in Death Valley National Park in California can become a reflective pool after rains. (File photo) Credits: NPS/Kurt Moses In a recently published paper, NASA scientists use nearly 20 years of observations to show that the global water cycle is shifting in unprecedented ways. The majority of those shifts are driven by activities such as agriculture and could have impacts on ecosystems and water management, especially in certain regions.
“We established with data assimilation that human intervention in the global water cycle is more significant than we thought,” said Sujay Kumar, a research scientist at NASA’s Goddard Space Flight Center in Greenbelt, Maryland, and a co-author of the paper published in the Proceedings of the National Academy of Sciences.
The shifts have implications for people all over the world. Water management practices, such as designing infrastructure for floods or developing drought indicators for early warning systems, are often based on assumptions that the water cycle fluctuates only within a certain range, said Wanshu Nie, a research scientist at NASA Goddard and lead author of the paper.
“This may no longer hold true for some regions,” Nie said. “We hope that this research will serve as a guide map for improving how we assess water resources variability and plan for sustainable resource management, especially in areas where these changes are most significant.”
One example of the human impacts on the water cycle is in North China, which is experiencing an ongoing drought. But vegetation in many areas continues to thrive, partially because producers continue to irrigate their land by pumping more water from groundwater storage, Kumar said. Such interrelated human interventions often lead to complex effects on other water cycle variables, such as evapotranspiration and runoff.
Nie and her colleagues focused on three different kinds of shifts or changes in the cycle: first, a trend, such as a decrease in water in a groundwater reservoir; second, a shift in seasonality, like the typical growing season starting earlier in the year, or an earlier snowmelt; and third a change in extreme events, like “100-year floods” happening more frequently.
The scientists gathered remote sensing data from 2003 to 2020 from several different NASA satellite sources: the Global Precipitation Measurement mission satellite for precipitation data, a soil moisture dataset from the European Space Agency’s Climate Change Initiative, and the Gravity Recovery and Climate Experiment satellites for terrestrial water storage data. They also used products from the Moderate Resolution Imaging Spectroradiometer satellite instrument to provide information on vegetation health.
“This paper combines several years of our team’s effort in developing capabilities on satellite data analysis, allowing us to precisely simulate continental water fluxes and storages across the planet,” said Augusto Getirana, a research scientist at NASA Goddard and a co-author of the paper.
The study results suggest that Earth system models used to simulate the future global water cycle should evolve to integrate the ongoing effects of human activities. With more data and improved models, producers and water resource managers could understand and effectively plan for what the “new normal” of their local water situation looks like, Nie said.
By Erica McNamee
NASA’s Goddard Space Flight Center, Greenbelt, Maryland
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Last Updated Jan 16, 2025 EditorKate D. RamsayerContactKate D. Ramsayerkate.d.ramsayer@nasa.gov Related Terms
Earth Global Precipitation Measurement (GPM) Goddard Space Flight Center Moderate Resolution Imaging Spectroradiometer (MODIS) Water & Energy Cycle Explore More
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By NASA
This map depicts global temperature anomalies for meteorological summer in 2024 (June, July, and August). It shows how much warmer or cooler different regions of Earth were compared to the baseline average from 1951 to 1980. (Credit: NASA/NOAA) Climate researchers from NASA and NOAA (National Oceanic and Atmospheric Administration) will release their annual assessments of global temperatures and discuss the major climate trends of 2024 during a media briefing at 12 p.m. EST Friday, Jan. 10.
NASA will share the briefing on the agency’s website at: https://www.nasa.gov/live.
Participants will include:
Gavin Schmidt, director, NASA’s Goddard Institute for Space Studies Russ Vose, chief, Monitoring and Assessment Branch, NOAA National Centers for Environmental Information Media interested in participating must RSVP to NOAA by the time of the event.
NASA and NOAA are stewards of global temperature data and independently produce a record of Earth’s surface temperatures and changes based on historical observations over land and ocean.
For more information about NASA’s Earth science programs, visit:
https://www.nasa.gov/earth
-end-
Liz Vlock
Headquarters, Washington
202-358-1600
elizabeth.a.vlock@nasa.gov
Peter Jacobs
Goddard Space Flight Center, Greenbelt, Maryland
301-286-0535
peter.jacobs@nasa.gov
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By NASA
4 min read
Expanded AI Model with Global Data Enhances Earth Science Applications
On June 22, 2013, the Operational Land Imager (OLI) on Landsat 8 captured this false-color image of the East Peak fire burning in southern Colorado near Trinidad. Burned areas appear dark red, while actively burning areas look orange. Dark green areas are forests; light green areas are grasslands. Data from Landsat 8 were used to train the Prithvi artificial intelligence model, which can help detect burn scars. NASA Earth Observatory NASA, IBM, and Forschungszentrum Jülich have released an expanded version of the open-source Prithvi Geospatial artificial intelligence (AI) foundation model to support a broader range of geographical applications. Now, with the inclusion of global data, the foundation model can support tracking changes in land use, monitoring disasters, and predicting crop yields worldwide.
The Prithvi Geospatial foundation model, first released in August 2023 by NASA and IBM, is pre-trained on NASA’s Harmonized Landsat and Sentinel-2 (HLS) dataset and learns by filling in masked information. The model is available on Hugging Face, a data science platform where machine learning developers openly build, train, deploy, and share models. Because NASA releases data, products, and research in the open, businesses and commercial entities can take these models and transform them into marketable products and services that generate economic value.
“We’re excited about the downstream applications that are made possible with the addition of global HLS data to the Prithvi Geospatial foundation model. We’ve embedded NASA’s scientific expertise directly into these foundation models, enabling them to quickly translate petabytes of data into actionable insights,” said Kevin Murphy, NASA chief science data officer. “It’s like having a powerful assistant that leverages NASA’s knowledge to help make faster, more informed decisions, leading to economic and societal benefits.”
AI foundation models are pre-trained on large datasets with self-supervised learning techniques, providing flexible base models that can be fine-tuned for domain-specific downstream tasks.
Crop classification prediction generated by NASA and IBM’s open-source Prithvi Geospatial artificial intelligence model. Focusing on diverse land use and ecosystems, researchers selected HLS satellite images that represented various landscapes while avoiding lower-quality data caused by clouds or gaps. Urban areas were emphasized to ensure better coverage, and strict quality controls were applied to create a large, well-balanced dataset. The final dataset is significantly larger than previous versions, offering improved global representation and reliability for environmental analysis. These methods created a robust and representative dataset, ideal for reliable model training and analysis.
The Prithvi Geospatial foundation model has already proven valuable in several applications, including post-disaster flood mapping and detecting burn scars caused by fires.
One application, the Multi-Temporal Cloud Gap Imputation, leverages the foundation model to reconstruct the gaps in satellite imagery caused by cloud cover, enabling a clearer view of Earth’s surface over time. This approach supports a variety of applications, including environmental monitoring and agricultural planning.
Another application, Multi-Temporal Crop Segmentation, uses satellite imagery to classify and map different crop types and land cover across the United States. By analyzing time-sequenced data and layering U.S. Department of Agriculture’s Crop Data, Prithvi Geospatial can accurately identify crop patterns, which in turn could improve agricultural monitoring and resource management on a large scale.
The flood mapping dataset can classify flood water and permanent water across diverse biomes and ecosystems, supporting flood management by training models to detect surface water.
Wildfire scar mapping combines satellite imagery with wildfire data to capture detailed views of wildfire scars shortly after fires occurred. This approach provides valuable data for training models to map fire-affected areas, aiding in wildfire management and recovery efforts.
Burn scar mapping generated by NASA and IBM’s open-source Prithvi Geospatial artificial intelligence model. This model has also been tested with additional downstream applications including estimation of gross primary productivity, above ground biomass estimation, landslide detection, and burn intensity estimations.
“The updates to this Prithvi Geospatial model have been driven by valuable feedback from users of the initial version,” said Rahul Ramachandran, AI foundation model for science lead and senior data science strategist at NASA’s Marshall Space Flight Center in Huntsville, Alabama. “This enhanced model has also undergone rigorous testing across a broader range of downstream use cases, ensuring improved versatility and performance, resulting in a version of the model that will empower diverse environmental monitoring applications, delivering significant societal benefits.”
The Prithvi Geospatial Foundation Model was developed as part of an initiative of NASA’s Office of the Chief Science Data Officer to unlock the value of NASA’s vast collection of science data using AI. NASA’s Interagency Implementation and Advanced Concepts Team (IMPACT), based at Marshall, IBM Research, and the Jülich Supercomputing Centre, Forschungszentrum, Jülich, designed the foundation model on the supercomputer Jülich Wizard for European Leadership Science (JUWELS), operated by Jülich Supercomputing Centre. This collaboration was facilitated by IEEE Geoscience and Remote Sensing Society.
For more information about NASA’s strategy of developing foundation models for science, visit https://science.nasa.gov/artificial-intelligence-science.
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Last Updated Dec 04, 2024 Related Terms
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