Steven Thur’s Post

LIGHTNING: #Biden-#Harris Administration invests US$250,000 in #AI tool for wildland #firefighting The U.S. Department of Commerce and NOAA: National Oceanic & Atmospheric Administration have announced US$250,000 in funding to support the development of an #artificialintelligence model, which is expected to improve #fire weather forecasts through better #lightning prediction. This funding is part of a larger Bipartisan Infrastructure Law (BIL) investment to improve fire weather research from President Biden’s #InvestinginAmerica agenda. With the funding, the Center for Satellite Applications and Research, part of NOAA’s National Environmental Satellite, Data and Information Service (NESDIS), and the University of Wisconsin Cooperative Institute for Meteorological Satellite Studies (CIMSS) are creating a customized version of #LightningCast. “LightningCast is continuing to evolve to meet the demand for timely and actionable information,” said Mike Pavolonis, NESDIS Wildland Fire Program manager. "LightningCast is one of several new satellite-based tools NOAA is developing to address the increasing wildland fire challenge.” Read more here: https://lnkd.in/eWSKnJih #Meteorology #Climate #ClimateChange #Science #Weather #Data #Forecasts #Environment #Technology #MetTechExpo #MetTechExpoNA

🌍 Leveraging GIS for Wildfire Management and Climate Resilience 🌍 Recent wildfires in Northern California and across the Western U.S. and Canada are highlighting the urgent need for advanced tools and strategies to manage these devastating events. As climate change exacerbates the intensity and frequency of wildfires, Geographic Information Systems (GIS) play a crucial role in understanding and mitigating their impact. 🚒 GIS in Action: I recently created a short animation using QGIS, visualizing active fire data from NASA's FIRMS (Fire Information for Resource Management System) for Canada and the USA over the past week. This project underscores how GIS can provide valuable insights into wildfire behavior and trends. 🌡️ Key Insights from GIS: Visualizing Fire Spread: GIS allows us to map and animate the spread of wildfires, providing a clear visual representation of affected areas. Assessing Impact: By integrating various data layers, GIS helps in assessing the impact of fires on ecosystems, communities, and infrastructure. Informing Management Strategies: GIS supports the development of effective fire management strategies, including controlled burns and resource allocation. 🌲 Climate Change and Ecosystem Transformation: Monitoring Changes: GIS helps monitor the transformation of ecosystems due to severe fires, identifying areas where invasive species may replace native vegetation. Predicting Future Risks: GIS-based models can predict future wildfire risks by analyzing climate data and vegetation patterns. The integration of GIS with real-time data from sources like NASA's FIRMS is essential for enhancing our ability to respond to and manage wildfires. As we face increasing challenges from climate change, leveraging geospatial technology will be critical in building resilience and protecting our communities and natural landscapes. #GIS #QGIS #NASA #Wildfires #ClimateChange #Geospatial #RemoteSensing #EnvironmentalScience #FireManagement #USA #Canada

Accurate prediction of #wildfire is essential for improving fire #risk assessment and mitigating the impacts of the event. Unfortunately, wildfires #propagation is a complex phenomenon involving different physical and chemical processes, including the so-called fire-spotting phenomenon. Strongly influenced by #weather conditions and #vegetation type, fire-spotting occurs when firebrands are carried away from the original fire and ignite secondary fires (from hundreds of meters to kilometers away from the main fire front), called spot-fires, which can jeopardize firefighting operations. But operational fire-spread simulators may not account for #spotting events, thus neglecting their consequences. For this reason, our researchers Andrea Trucchia, Umberto Morra di Cella and Paolo Fiorucci, together with researchers from BCAM - Basque Center for Applied Mathematics and Molise Civil Protection Functional Center, conducted the study “Fire-spotting modelling in operational wildfire simulators based on Cellular Automata: A comparison study”, published in “Agricultural and Forest Meteorology” (vol. 350). In this work, three fire spotting parameterizations were integrated in the operational wildfire simulator #PROPAGATOR, a model developed by our Foundation researchers that offers, in probabilistic terms, indications on how a #fire can evolve under certain conditions and in a certain area, based on Cellular Automata (CA). A #forestfire that occurred in the summer of 2021 in the municipality of Campomarino (Molise, Italy), where spotting effects were clearly reported, was used as a case study. This case study paves the way for a framework for comparison of parameterized spotting models used in operational scenarios. 👉 Read the full article: https://lnkd.in/dNJHNb56

🔥🗺️ Introducing our new course: GIS for Wildfire Management! In this course, students are delving into the crucial role that #GIS plays in understanding, predicting, and mitigating the impacts of #wildfires on our communities and ecosystems while engaging with cutting-edge technologies like #FlamMap and #Planscape, to analyze real-world data, and develop practical skills that are essential in addressing the complex challenges posed by wildfires. #WildfireManagement #GIS #GeospatialTech #USFCA #MSEM #GsAL

Attention Environmental Professionals! Starting February 13, 2024, the E1527-21 Standard Practice will be the only recognized method for meeting the “All Appropriate Inquiry” (AAI) Rule for protection from liability for contamination under CERCLA. This means that it's more important than ever to ensure that your Phase I ESAs are up to date. That's where RiskFootprint(tm) Reports come in. Our reports incorporate Fathom flood maps, NOAA storm surge maps, NASA tidal flooding and sea level rise data, FEMA maps, USGS earthquake models, USFS wildfire maps, and more to show you exactly where Recognized Environmental Conditions (RECs) "pose a material threat of future release to the environment." Don't wait until it's too late - visit RiskFootprint(tm) dot com to learn more about how our reports can help you stay ahead of the game. #ESAPhase1 #EnvironmentalRiskOfficer #EnvironmentalSiteAssessment #hazardouswaste #CERCLA #allappropriateinquiry #AAI #CERCLALiability #EnvironmentalBankersAssociation #EBA

TGI-funded Project Uses Geospatial Tech to Study Permafrost, Plants, and Wildfire, read the full story: https://lnkd.in/edaBpA5F The arctic tundra is a surprisingly dynamic ecosystem that at first glance appears to be a windswept, frigid wasteland. But further investigation reveals that it hosts hundreds of plant species—mostly shrubs, mosses, and grasses— that jockey for space with lichens and other low-lying lifeforms in these mostly treeless expanses. Beneath the surface lies permanently frozen soil, called permafrost, storing huge amounts of carbon that may escape into the atmosphere as methane and carbon dioxide.

 Why I Chose Sentinel-1 with VV Polarization for Flood Mapping Why Sentinel-1? Sentinel-1, part of the European Space Agency - ESA Programme, is a radar imaging satellite equipped with a synthetic aperture radar (SAR) sensor. SAR sensors are advantageous for flood mapping because they operate in the microwave spectrum, allowing them to capture images regardless of weather conditions or daylight. This is crucial in flood scenarios, which often coincide with heavy rainfall and cloudy conditions. VV Polarization Polarization refers to the orientation of the electromagnetic waves emitted by the radar. Sentinel-1 offers different polarization modes, including Vertical-Vertical (VV) and Vertical-Horizontal (VH). For this project, VV polarization was chosen for several reasons: 1. Surface Interaction: VV polarization is sensitive to surface roughness and water surfaces. Water bodies typically appear dark in VV polarized radar images due to the specular reflection, which helps in distinguishing flooded areas from the surrounding terrain.    2. Data Consistency: VV polarization provides consistent backscatter signals over water surfaces, making it easier to identify changes over time. This consistency is essential for accurate flood mapping and monitoring. 3. Data Availability: Sentinel-1 provides frequent revisit times and global coverage, ensuring timely data acquisition. This is particularly beneficial for flood mapping, where rapid response is necessary to assess the situation and plan interventions. Application in Flood Mapping In the provided script and visualization, Sentinel-1 data with VV polarization was used to map flood extents on Google Earth Engine. The script processes the radar images to identify areas of standing water, which are then highlighted in the output map. This method allows for precise identification of flooded regions, even in areas with dense vegetation or urban infrastructure. The choice of Sentinel-1 with VV polarization for flood mapping is driven by its ability to provide reliable, weather-independent data, sensitivity to water surfaces, and consistent backscatter signals. These features make it an invaluable tool for timely and accurate flood assessment, helping to mitigate the impact of floods on communities and infrastructure. By leveraging Sentinel-1’s capabilities, this project aims to enhance flood mapping accuracy and support effective flood management strategies. _code available on request_ #RemoteSensing #FloodMapping #Sentinel1 #GoogleEarthEngine #VVPolarization #FloodManagement #GIS #SAR #Copernicus #EnvironmentalMonitoring #DisasterManagement

Continuing with what we've gone over with hydrometric and climate data collection, the next 2 weeks will focus on geomatics data collection. #nhceducation #geomatics

From GIS Lounge: Understanding the Increase in PyroCbs: Wildfire Thunderstorms https://lnkd.in/eZmmygQv #GeographicInformationSystems #LocationIntelligence #GeospatialData #Mapping #GISAnalysis #SpatialData #GISMapping #GeospatialTechnology #GISConsulting #GISSoftware #GISServices #GISApplications #GISData #GISMappingServices #GeospatialAnalysis #GISMappingSoftware #GISMappingSolutions #GISMappingTools #GISMappingTechnology #GISMappingData #GISProfessional #GISExpert #GISCommunity #GISMappingExpert #GISSpecialist #GISMappingConsultant #GISIndustry #GISInsights #GISDataAnalysis #GISDataManagement

📊 Excited to share my latest publication in the Paddy and Water Environment Journal via Springer! 📚 Titled "Application of topographic elevation data generated by remote sensing approaches to flood inundation analysis model", this paper delved into the innovative application of self-developed high resolution DTM in low-lying flood-prone regions worldwide. 🌏 🔍 By leveraging open source SAR and optical satellite imageries, our research aimed to revolutionize flood modeling studies, particularly in lowland and river delta areas. Not only did this approach offer cost-effective advantages by reducing labor-intensive efforts and eliminating the need for extensive fieldwork, but it also made streamlines workflow and reduced financial burden, making flood modeling more accessible, especially in developing countries with limited access to high-resolution DTMs. 🌊 📖 Interested in learning more about how remote sensing techniques can enhance flood management strategies worldwide? Check out the full paper here: https://lnkd.in/gr9TJGCc #FloodManagement #RemoteSensing #ResearchPublication #WaterEngineering #FloodModeling