Geolabe’s Post

In an era where technology and environmental sustainability converge, satellites are becoming pivotal in our fight against climate change. 🛰️🌍 🛰️ Satellite Data Revolution 🛰️ Satellite technology is now at the forefront of monitoring greenhouse gas emissions globally. Unlike traditional methods, which often lack real-time accuracy, satellite data provides comprehensive, up-to-date insights into emission sources and trends. 🌎✨ 📊 Real-Time Monitoring 📊 One of the most remarkable advantages of satellite data is its real-time monitoring capability. 🌐 Traditional ground-based measurements can be sporadic and limited in scope. However, satellites orbiting the Earth capture continuous data, offering a bird's-eye view of emissions. This constant stream of information helps policymakers and scientists respond swiftly to emerging trends and hotspots. 🚀📡 🌱 Accuracy and Transparency 🌱 The precision of satellite data is transforming how we understand and address greenhouse gas emissions. With advanced sensors and imaging technology, satellites can detect even minute changes in atmospheric composition. 🔍 Identifying Emission Hotspots 🔍 Satellites can pinpoint emission hotspots with unprecedented accuracy. Whether it's a bustling industrial city or a remote area impacted by deforestation, satellite data identifies the exact locations contributing to greenhouse gas emissions. This targeted approach allows for tailored interventions, maximizing the efficiency of mitigation efforts. 🌆🌲 🤝 Global Collaboration 🤝 The universal reach of satellite data fosters international collaboration. 🌍 Countries can share insights and strategies, working together towards a common goal. Initiatives like the World Bank’s efforts to harness satellite technology are paving the way for collective action, ensuring no region is left behind in the fight against climate change. 🌐🌱 🔮 The Future of Climate Action  With innovations like AI and machine learning, the analysis of satellite data will become even more sophisticated, driving more effective climate policies and actions. #ClimateChange #Sustainability #SatelliteTechnology #GreenhouseGasEmissions #Innovation #TechForGood #GlobalCollaboration https://lnkd.in/gpRQ_cZ6

Kayrros have done it again – this time taking the top spot in TechRound’s AITech35 for 2024. It's a competition that celebrates the companies leading the way in AI, and Kayrros is certainly one of them. They make use of artificial intelligence in a highly original and effective way: processing the terabytes of raw data captured every day by satellites orbiting the planet. By processing those images, they can draw precise climate insights on everything from methane emissions to wildfires. They've set a powerful example of what can be achieved when space tech is combined with AI. Well done to the whole team! Find out more about the AITech35 here: https://lnkd.in/evpEhx82 #awards #space #newspace #innovation #ai #climate #sustainability #energytransition #aitech35

"The NASA Science Mission Directorate (SMD) instituted the Entrepreneurs Challenge to identify innovative ideas and technologies from small business start-ups with the potential to advance the agency’s science goals. Geolabe—a prize winner in the latest Entrepreneurs Challenge—has developed a way to use artificial intelligence to identify global methane emissions... The Geolabe team has developed a deep learning architecture that automatically identifies methane signatures in existing open-source spectral satellite data and deconvolves the signal from the noise. This AI method enables automatic detection of methane leaks at 200kg/hour and above, which account for over 85% of the methane emissions in well-studied, large oil and gas basins." #satellitedata #earthobservation #deeplearning #methane

🌍 Meta's nuclear project paused by a rare bee. What's more important—progress or preservation? 🐝 A tiny bee forces Meta to rethink environmental priorities. 🔋 Tech advances must consider 14% projected energy use by 2040. 🤝 Sustainability can enhance customer retention by 13%. Dive into the full story: https://buff.ly/4fmeaVG #SustainableTech #EnvironmentalImpact #TechInnovation #AILeadership

Global Atmospheric Methane (CH₄) | NASA Earth Observatory FriendsofNASA.org: Methane (CH₄) is a powerful greenhouse gas that traps heat 28 times more effectively than carbon dioxide over a 100-year timescale. Concentrations of methane have increased by more than 150% since industrial activities and intensive agriculture began. After carbon dioxide, methane is responsible for about 20% of climate change in the twentieth century. Methane is produced under conditions where little to no oxygen is available. About 30% of methane emissions are produced by wetlands, including ponds, lakes and rivers. Another 20% is produced by agriculture, due to a combination of livestock, waste management and rice cultivation. Activities related to oil, gas, and coal extraction release an additional 30%. The remainder of methane emissions come from minor sources such as wildfires, biomass burning, permafrost, termites, dams, and the ocean. Scientists around the world are working to better understand the budget of methane with the ultimate goals of reducing greenhouse gas emissions and improving prediction of environmental change. The NASA SVS visualization presented here shows the complex patterns of methane emissions produced around the globe and throughout the year from the different sources described above. The visualization was created using output from the Global Modeling and Assimilation Office (GMAO), GEOS modeling system, developed and maintained by scientists at NASA. Wetland emissions were estimated by the LPJ-wsl model, which simulates the temperature and moisture dependent methane emission processes using a variety of satellite data to determine what parts of the globe are covered by wetlands. Other methane emission sources come from inventories of human activity. Video Credit: NASA Scientific Visualization Studio Visualizations: Helen-Nicole Kostis Scientific Consulting: Lesley Ott, Brad Weir Duration: 2 minutes Release Date: July 1, 2024 Zepherina Darcy #NASA #Space #Satellites #Science #Planet #Earth #Atmosphere #Methane #GlobalMethaneEmissions #ClimateModels #ClimateChange #GlobalHeating #Climate #Environment #GreenhouseGases #GHG #EarthObservation #RemoteSensing #JPL #Caltech #UnitedStates #STEM #Education #Visualization #HD #Video

Publication alert! Understanding the role of #atmospheric #aerosols has been challenging due to a lack of long-term, consistent observations. This issue is especially significant in the #IGP, a major global emission hotspot. In our study, we used a new method to address these gaps by combining weather data, satellite observations, and #MachineLearning. We focus on three key aerosol properties: AOD, SSA, and Asymmetry Parameter, which are crucial for understanding how aerosols affect climate and radiation. We looked into two decades of aerosol measurements from an #AERONET station in the #IGP and used #ML to fill observational gaps in the data. We trained the #ML model using weather data and satellite information, carefully tuning it for best performance. Our tuned #ML model showed it could predict #AOD, #SSA, and AP with moderate accuracy, comparable to existing #satellite and #reanalysis data errors. Including #MODIS #AOD as a predictor in the #ML model improved its accuracy, reducing the #AOD error to 0.14 and explaining 84% of the variability. Overall, we reduced the observational gaps by about 10% for #AOD, 23% for #SSA, and 21% for #AP. Our study shows that an optimized #ML model can effectively fill measurement gaps and improve our understanding of aerosols' effects on #climate. This approach could be useful for studying other pollutants and regions with scarce data in South and Southeast Asia. Read more about the findings and methodology in the full-text article: https://lnkd.in/dwTdk9xS #AhmedabadUniversity #AirandClimateResearchLab Narendra Ojha

Congratulations to the Leeds and ESA team, Its worrying to consider what would have happened if this leak had continued, but also wonderfully highlights the importance of real time data and how it can benefit us on the ground. This was achieved with only one data source GHGSat. Now think what would have been possible with multiple data sources, the detection, location and repair could be reduced from 4 months to 3 weeks or less. This is what we are working to achieve at Astro Dynamic, getting teams like this the data they need as quickly as possible and from as many sources as possible. https://lnkd.in/ey6vWYVi.

Completed ARSET Training on CO2 Studies Using OCO-2 and OCO-3 Satellite Data I’m excited to share that I have successfully completed NASA’s ARSET (Applied Remote Sensing Training) on carbon dioxide (CO2) studies, utilizing data from the OCO-2 (Orbiting Carbon Observatory-2) and OCO-3 (Orbiting Carbon Observatory-3) satellites. This specialized training provided comprehensive insights into monitoring global CO2 levels, helping to improve our understanding of greenhouse gas concentrations and their relationship with climate change. OCO-2: Launched in 2014, OCO-2 was designed to monitor atmospheric carbon dioxide with high precision. It measures the global distribution of CO2 levels in Earth's atmosphere, providing scientists with critical data to track sources and sinks of CO2, such as forests, oceans, and urban areas. OCO-3: Installed on the International Space Station (ISS) in 2019, OCO-3 is equipped with a similar instrument as OCO-2 but has enhanced capabilities. It can measure CO2 from multiple angles and observe how it varies over time and space, particularly in urban areas, helping researchers understand how cities contribute to CO2 emissions. 1. Data Analysis: Gained hands-on experience using OCO-2 and OCO-3 data for tracking and mapping CO2 sources and sinks, and interpreting how these changes impact global climate. 2. CO2 Measurement Techniques: Learned about the different methods these satellites use to measure atmospheric CO2, such as spectrometry, which helps detect CO2 absorption in different wavelengths of sunlight. 3.Applications: Explored various applications of OCO data, from climate change monitoring to policy-making and sustainable development efforts. These data sets are crucial for validating carbon inventories, supporting climate models, and guiding emission reduction strategies. 4.Urban Emissions Monitoring: Understanding how OCO-3’s snapshot mapping mode enables high-resolution monitoring of CO2 concentrations in urban environments, making it a powerful tool for studying city-level carbon footprints. This training has provided me with valuable expertise in analyzing satellite data for environmental applications, which I plan to leverage in future research and projects focusing on climate change, carbon cycle dynamics, and sustainability. I’m eager to apply these skills in real-world scenarios, contributing to global efforts in mitigating the impact of CO2 emissions. #ARSET #NASA #RemoteSensing #OCO2 #OCO3 #CO2Monitoring #ClimateChange #Sustainability #EnvironmentalScience #SatelliteData #CarbonEmissions #ClimateAction #CarbonCycle #DataAnalysis #EarthObservation #AtmosphericScience

Weather Innovation, Smart Energy, and Resilience (WISER) is an NSF Industry-University Cooperative Research Center (IUCRC). 🌪️🌍 In the U.S., damaging wind events like derechos, microbursts, and tornadoes cause significant loss of lives and property, including disruptions to power grids. With the rise of renewable energy, better forecasting is crucial. Current mesoscale meteorological models (MMMs) often lack accuracy due to computational limitations. Advancements in deep learning (DL) techniques, such as Fourier neural operators and vision transformers, offer a chance to develop faster, more accurate Next-Gen MMMs. Our project aims to create DeepExWind, a DL-based model for reliable 3-hour wind forecasts on a basic workstation. This innovation could enable engineers at utility companies to forecast extreme wind conditions more accurately, enhancing grid reliability and mitigating climate change impacts. 🌱 #RenewableEnergy #ClimateChange #DeepLearning #WindForecasting #Meteorology