Clark Center for Geospatial Analytics’ Post

University of San Francisco professors David Saah, Paul Nesbit, and Maria Fernanda Lopez Ornelas of USF´s Geospatial Analysis Lab (GsAL) recently attended the Esri User Conference and shared interesting insights into #GIS trends, the future of #GeoAI, and #environmentalmanagement opportunities. Check out our latest blog post for the inside scoop. 🛰 https://lnkd.in/gs-iPWGb #usfca #usfcamsem #usfmsem #geospatialanalysis #conference

I started the adventure of building a nationally recognized geospatial institute at Saint Louis University (SLU) in 2018 with a $50,000 Big Idea grant from the SLU Research Institute (thanks largely to Ken Olliff's inspiring and visionary leadership), which I used to establish the Geospatial Institute at SLU (GeoSLU) in a close partnership with Ness Sándoval and Enbal Shacham. We had ambitious, 10-year goals for GeoSLU from the start: 1) become a regional leader in geospatial science, 2) secure a sizeable gift or other funding to grow GeoSLU into a national leader in geospatial science, 3) employ 20+ full-time staff, and 4) recruit 25 top-notch faculty to SLU to position the region as a global center of excellence in geospatial science. As excitement gathered around geospatial in the STL region, GeoSLU evolved into the Taylor Geospatial Institute, a first-of-its-kind entity in the geospatial ecosystem designed to fuel research, collaboration, and impact. With a legacy investment from Andrew Taylor and the commitment of 8 institutions led by SLU, TGI is the cornerstone of establishing a global center of geospatial excellence in STL. With tremendous support from SLU leadership, Taylor, Robert Cardillo, the members of the TGI Governing and Research Councils, we accomplished those 10-year goals in 5 years. I helped launch and then led TGI with 3 full-time staff in its inaugural year. My accomplishments as Acting Director during TGI’s first year are enumerated at https://lnkd.in/eviaK4ec. When we embarked on this geospatial journey in 2018, it wasn’t assured that the original $50,000 seed funding would grow into anything at all. But thanks to the SLU Research Institute, which was established thanks to a generous gift from the Dr. Jeanne and Mr. Rex Sinquefield that bolstered GeoSLU, and visionary leaders in the STL Geospatial Ecosystem, we sparked a revolution in geospatial! Today we have a world-class leadership team at TGI supported by more than a dozen full-time staff members. I am stepping down from TGI’s leadership team to focus on research and my leadership roles as SLU’s Associate Vice President of Geospatial Science (research support, computing, talent recruitment, and geospatial faculty hiring). I will continue leading TGI’s Drone Data Services team, overseeing the TGI Academy, representing SLU on TGI Research Council, and supporting executive director Nadine Alameh and the TGI leadership team. I will continue to work closely with you all as TGI’s Chief Scientist for Food Security & Digital Agriculture. Though my title at TGI may be changing, my commitment to the organization and my investment in TGI’s success is not. Like many in TGI's orbit, I believe in the great potential of TGI, and the importance of its mission. I consider it a privilege to have led TGI in its early stages, and I am proud to continue to be a part of the wonderful journey of making the St. Louis region a globally recognized geospatial hub. 

Don't miss the latest USF MS in Environmental Management (MSEM) blog post covering this year's Esri User Conference. BayGeo's very own David Saah, Paul Nesbit, and Maria Fernanda Lopez Ornelas share their insights and key takeaways on #GIS trends and the exciting future of #GeoAI!

Hello Everyone, 🌟 Course Completed! 🌟 Excited to share that I've successfully completed the Classifying Objects Using Deep Learning in ArcGIS Pro course by Esri. 🎓 Through this course, I've honed my skills in using deep learning models for object classification, creating training samples, and analyzing spatial data. This further enhances my expertise in GIS and remote sensing technologies. Looking forward to applying these new techniques in future projects! 🌍🌱 #DeepLearning #GIS #SpatialAnalysis #ArcGIS #RemoteSensing #DataScience #ProfessionalDevelopment #Learning

🌍 Unlock the Power of Machine Learning for Land Use and Land Cover Classification! 🌍 Are you looking to advance your skills in Land Use and Land Cover (LULC) classification using cutting-edge technologies like Google Earth Engine and ArcMap? Join our upcoming online training program, starting on 15th November, where we’ll dive deep into: Using Machine Learning algorithms to classify LULC How to leverage Google Earth Engine for large-scale geospatial analysis ArcMap techniques for accurate and detailed mapping This training is perfect for: GIS professionals looking to enhance their technical toolkit Researchers working in environmental science, urban planning, and resource management Anyone passionate about applying AI and geospatial data for sustainable development! 🚨 Registration is now open! 🚨 Grab your spot today and enjoy a 50% discount. Don’t miss this opportunity to level up your geospatial analysis skills with real-world applications! 👉 Register now and secure your discounted seat: Registration info Link attached in the comment section 👇 #LandUse #LandCover #MachineLearning #GoogleEarthEngine #ArcMap #GIS #GeospatialAnalysis #SustainableDevelopment #OnlineTraining #GIScience #LULC #DataScience #RemoteSensing

🌍 Unlock the Power of Machine Learning for Land Use and Land Cover Classification! 🌍 Are you looking to advance your skills in Land Use and Land Cover (LULC) classification using cutting-edge technologies like Google Earth Engine and ArcMap? Join our upcoming online training program, starting on 15th November, where we’ll dive deep into: Using Machine Learning algorithms to classify LULC How to leverage Google Earth Engine for large-scale geospatial analysis ArcMap techniques for accurate and detailed mapping This training is perfect for: GIS professionals looking to enhance their technical toolkit Researchers working in environmental science, urban planning, and resource management Anyone passionate about applying AI and geospatial data for sustainable development! 🚨 Registration is now open! 🚨 Grab your spot today and enjoy a 50% discount. Don’t miss this opportunity to level up your geospatial analysis skills with real-world applications! 👉 Register now and secure your discounted seat: Registration info Link attached in the comment section 👇 #LandUse #LandCover #MachineLearning #GoogleEarthEngine #ArcMap #GIS #GeospatialAnalysis #SustainableDevelopment #OnlineTraining #GIScience #LULC #DataScience #RemoteSensing

Part 5: Advanced Spatial Analysis Techniques Welcome back to our GIS education series! In our previous installment, we delved into the fundamentals of spatial analysis, exploring techniques such as buffering, overlay analysis, network analysis, hotspot analysis, and geostatistics. Now, let's dive deeper into advanced spatial analysis methods that empower GIS professionals to extract richer insights from spatial data. Spatial Regression Analysis: This technique extends traditional regression analysis to incorporate spatial dependencies. It's invaluable for understanding how spatial relationships affect phenomena like housing prices, land use patterns, or environmental quality. By considering the spatial context, analysts can better model and predict outcomes. Machine Learning in GIS: Machine learning algorithms, such as decision trees, random forests, and neural networks, are increasingly integrated into GIS workflows. These algorithms excel at recognizing complex patterns and relationships in spatial data, enabling tasks like land cover classification, species distribution modeling, and image analysis. 3D Spatial Analysis: As GIS technology evolves, the ability to analyze and visualize data in three dimensions becomes crucial. 3D spatial analysis enables planners to assess urban landscapes, simulate the impacts of infrastructure projects, and analyze line-of-sight visibility. It's particularly useful in architecture, urban design, and disaster management. Temporal Analysis: Many spatial phenomena evolve over time, from population growth to land cover change to natural disasters. Temporal analysis techniques allow analysts to explore trends, detect anomalies, and forecast future scenarios. GIS professionals leverage temporal analysis for applications like climate change modeling, epidemiology, and historical research. Big Data Analytics: With the proliferation of sensor networks, social media platforms, and remote sensing technologies, GIS practitioners are grappling with vast amounts of spatial data. Big data analytics techniques, including parallel processing, distributed computing, and scalable algorithms, enable the efficient analysis of large-scale spatial datasets. By mastering these advanced spatial analysis techniques, GIS professionals can tackle complex challenges in diverse domains, from urban planning and environmental conservation to disaster response and beyond. If you found this article insightful, don't forget to like, share, and follow for more GIS education. Stay tuned for our next installment, where we'll explore real-world case studies showcasing the practical applications of advanced spatial analysis in GIS. #LearnWithShahrukhWasay #AdvancedGIS #SpatialAnalysis #MachineLearning #3DSpatialAnalysis #TemporalAnalysis #BigDataAnalytics #GISApplications

🚀 I am happy to share that my colleague Ruslan Huseynov and I have successfully trained a custom building detection model for the our country! Using the Mask R-CNN architecture, ArcGIS API, and ArcGIS Pro, we achieved over 70% accuracy on high-resolution satellite imagery (0.30 m). This project not only increases our capabilities in accurate building identification, but also brings us closer to using advanced deep learning models for effective geospatial applications. The results open up new possibilities for urban planning, infrastructure monitoring, and environmental management—demonstrating the power of artificial intelligence to meaningfully transform geospatial analysis. We extend our thanks to Rohit S. and Vinay Viswambharan for their incredible work in developing ESRI GeoAI models. Watch --- https://lnkd.in/eqp7QwRN What is Mask R-CNN and how is it applied in GIS? -- https://lnkd.in/euadrK-Y #GIS #DeepLearning #BuildingDetection #RemoteSensing #ArcGIS #AI #GeospatialTech #Innovation

Does the term GeoAI sound daunting to you? If so, you wouldn’t be the only one. Our latest blog Unlocking the power of GeoAI: Smarter Spatial Analysis with ArcGIS explores how you can begin harnessing the potential of GeoAI at any level of experience. Dive into the future of smarter spatial analysis and discover how you can integrate GeoAI into your ArcGIS projects. Backhand index 👉 https://lnkd.in/eNq6q2hc 🌍🔓  #GeoAI #Geospatial #EsriUK