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محتوای ارائه شده توسط Matt Forrest. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط Matt Forrest یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal
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Why We’re Still Bad at Predicting Wildfires
Manage episode 468460214 series 3646168
محتوای ارائه شده توسط Matt Forrest. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط Matt Forrest یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal
📩 Get every update from my newsletter ➡️ https://forrest.nyc ⬅️
Wildfires are getting more intense, yet many people in Los Angeles had no idea the fire was near them—until they saw the smoke. Despite all our advancements in geospatial technology, disaster response still struggles with timely alerts, real-time data access, and predictive modeling.
In this episode, I sit down with Mina Nada, a remote sensing specialist, to explore what went wrong during the recent LA wildfires and how geospatial tools like satellite imagery, fire modeling, and risk mapping can improve future disaster response. We break down why current wildfire alerts are failing, what GIS professionals can do to fix it, and how earth observation data plays a critical role in mitigating fire disasters.
If you’re in GIS, remote sensing, emergency management, or just curious about the future of fire detection, this conversation is packed with insights you don’t want to miss.
🔥 Topics Covered:
✔️ Why wildfire alerts failed during the LA fires
✔️ How satellite imagery tracks wildfires in real-time
✔️ The role of GIS in predicting and responding to fires
✔️ Challenges in making wildfire data more accessible
✔️ What we need to do to prevent future wildfire disasters
16 قسمت
اشتراک گذاریManage episode 468460214 series 3646168
محتوای ارائه شده توسط Matt Forrest. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط Matt Forrest یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal
📩 Get every update from my newsletter ➡️ https://forrest.nyc ⬅️
Wildfires are getting more intense, yet many people in Los Angeles had no idea the fire was near them—until they saw the smoke. Despite all our advancements in geospatial technology, disaster response still struggles with timely alerts, real-time data access, and predictive modeling.
In this episode, I sit down with Mina Nada, a remote sensing specialist, to explore what went wrong during the recent LA wildfires and how geospatial tools like satellite imagery, fire modeling, and risk mapping can improve future disaster response. We break down why current wildfire alerts are failing, what GIS professionals can do to fix it, and how earth observation data plays a critical role in mitigating fire disasters.
If you’re in GIS, remote sensing, emergency management, or just curious about the future of fire detection, this conversation is packed with insights you don’t want to miss.
🔥 Topics Covered:
✔️ Why wildfire alerts failed during the LA fires
✔️ How satellite imagery tracks wildfires in real-time
✔️ The role of GIS in predicting and responding to fires
✔️ Challenges in making wildfire data more accessible
✔️ What we need to do to prevent future wildfire disasters
16 قسمت
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Spatial Stack with Matt Forrest
📩 Get every update from my newsletter ➡️ https://forrest.nyc ⬅️ 💨 Sign up for the Spatial Lab Community ➡️ https://forrest.nyc/spatial-lab ⬅️ What if the way we map the Earth is reinforcing the very inequalities we aim to solve? In this episode of The Spatial Stack, I sit down with Dr. Nadine Alameh, one of the most influential voices in geospatial and AI for Earth. With a background spanning NASA, the United Nations, and the Open Geospatial Consortium, Nadine brings a unique systems-level perspective to the urgent question: Who gets to define the map? We dive into: How AI models can fail without local context and community input The tensions between global institutions and grassroots data efforts The importance of open tools, inclusive standards, and rethinking what “ground truth” really means What it will take to make Earth intelligence equitable, actionable, and trustworthy Whether you’re building geospatial systems, training machine learning models, or working on climate and land use policy, this conversation will reshape how you think about data, power, and place.…
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Spatial Stack with Matt Forrest
📩 Get every update from my newsletter ➡️ https://forrest.nyc ⬅️ 💨 Sign up for the Spatial Lab Community ➡️ https://forrest.nyc/spatial-lab ⬅️ What if the future of AI depends on understanding where, not just what? In this episode, I’m joined by Justus Killian, partner at Space Capital, one of the only VC firms focused entirely on geospatial and space-based tech. We dive into why geospatial data is no longer niche, how satellites became billion-dollar businesses, and why the next wave of AI breakthroughs could come from those who understand location. We also unpack the evolving venture landscape, the rise of geo-embeddings, and how spatial data is finally moving beyond the map into real-time decision-making. Whether you're building LLMs, funding the next Planet Labs, or just curious about how Earth is being mapped in ways you’ve never seen, this one's for you.…
📩 Get every update from my newsletter ➡️ https://forrest.nyc ⬅️ 💨 Sign up for the Modern GIS Accelerator ➡️ https://forrest.nyc/accelerator ⬅️ In this episode, we dive into one of the biggest challenges holding back GIS professionals today: the technician trap . Sparked by a real-world job posting from one of the world’s richest tech companies—offering just $20–$22 an hour for a GIS contract role—we explore what this means for the broader industry. Why are highly skilled spatial professionals being underpaid, and what separates a $45K contractor from a $300K geospatial data engineer? The answer lies in how you position yourself—and whether your work is seen as project-based execution or strategic value creation. We’ll unpack: The pay disparity across GIS roles and what it reveals How entry-level positions can set the wrong trajectory Why spatial skills alone aren’t enough without systems thinking The mindset shift needed to break free from being "just a mapmaker" How to move from being a button-pusher to a strategic stakeholder Whether you're just entering the GIS field or feeling stuck in your current role, this episode offers a candid look at how to grow your career by aligning technical skills with business impact—and why it's time to expect more from GIS roles. 🎧 Plus: Learn about the Modern GIS Accelerator , a program designed to help you scale your skills and reframe your career path.…
📩 Get every update from my newsletter ➡️ https://forrest.nyc ⬅️ 💨 Sign up for the Modern GIS Accelerator ➡️ https://forrest.nyc/accelerator ⬅️ Feeling stuck in your GIS career? You're not alone. In this episode, we dive deep into the common challenges GIS professionals face and how to break free from the "technician trap." Discover actionable strategies to transition from a support role to a strategic contributor, adding greater value to your organization. We'll explore how to shift your mindset from focusing solely on deliverables to emphasizing outcomes. Learn how to identify your technical passions, specialize effectively, and position yourself as a leader in your field. Whether you're aiming to build a standout portfolio, land a promotion, or pivot into a new GIS role, this episode offers practical insights to help you achieve your goals. Plus, hear real-world examples of how GIS professionals have transformed their careers by applying these principles. Tune in and start unlocking the next level in your GIS journey!…
📩 Get every update from my newsletter ➡️ https://forrest.nyc ⬅️ What if you could stop wrangling geospatial data, and just get to the good part? In this episode, I sit down with Rob Fletcher, Chief Science Officer at Seer AI, to talk about one of the biggest blockers in geospatial today: accessing and integrating the right data, at the right time, in the right format. Rob shares his journey from doing particle physics at CERN to pioneering spatial data infrastructure, and how Seer AI is building what he calls a “CDN for geospatial data.” We dive into: 🌍 Why the biggest challenge in GIS isn’t analysis—it's finding and formatting data 💡 The danger of agreeing to analytics projects without knowing what's possible 🛠️ Why Seer AI chose graph technology to organize spatial data across sources ⚡ How a "side project" dashboard became essential to real-time disaster response 📊 Bridging the gap between GIS teams and business analysts Whether you're working in local government, disaster response, sustainability, or just tired of managing messy spatial data, this episode will change how you think about building modern GIS workflows. 🔗 Learn more about Seer AI: https://seer.ai 🎧 Subscribe for more episodes on the future of geospatial…
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Spatial Stack with Matt Forrest
In this episode, we sit down with David Price, GIS Project Manager for Wood County, Ohio, to explore the evolving landscape of modern GIS. David’s journey into geospatial wasn’t a traditional one—he started in data analytics before discovering GIS, a shift that completely changed his career trajectory. We dive into: 🔹 Why GIS education is falling behind and how universities are missing the mark 🔹 The critical skills GIS professionals need today (Hint: It’s more than just mapping) 🔹 The debate: Do you really need to learn to code to stay competitive? 🔹 Open-source vs. Esri: Why a hybrid approach is the future of GIS 🔹 The power of real-time data, automation, and APIs in GIS workflows David shares his experiences managing an enterprise GIS system, adapting to new geospatial technologies, and why he believes learning SQL and Python can future-proof your GIS career. If you’re a GIS professional, student, or just someone interested in the future of geospatial technology, this is an episode you don’t want to miss!…
Is there a future in GIS? How can you break past the salary ceilings and position yourself for long-term success? In this episode, we dive into the realities of GIS careers, salaries, and strategies to help you grow. 🔹 Why GIS salaries often lag behind similar data roles 🔹 The Technician Trap —how GIS is often seen as a support role rather than a strategic function 🔹 Skills that matter —Python, SQL, and cloud-native GIS for career flexibility 🔹 How to position yourself as a problem-solver, not just an executor 🔹 Tangible steps to accelerate your career without switching jobs GIS is an exciting field, but to truly thrive, you need to think beyond maps and spatial analysis—you need to be strategic . Tune in to learn how to showcase your skills, position yourself for growth, and maximize your career growth.…
📩 Get every update from my newsletter ➡️ https://forrest.nyc ⬅️ Wildfires are getting more intense, yet many people in Los Angeles had no idea the fire was near them—until they saw the smoke. Despite all our advancements in geospatial technology, disaster response still struggles with timely alerts, real-time data access, and predictive modeling. In this episode, I sit down with Mina Nada, a remote sensing specialist, to explore what went wrong during the recent LA wildfires and how geospatial tools like satellite imagery, fire modeling, and risk mapping can improve future disaster response. We break down why current wildfire alerts are failing, what GIS professionals can do to fix it, and how earth observation data plays a critical role in mitigating fire disasters. If you’re in GIS, remote sensing, emergency management, or just curious about the future of fire detection, this conversation is packed with insights you don’t want to miss. 🔥 Topics Covered: ✔️ Why wildfire alerts failed during the LA fires ✔️ How satellite imagery tracks wildfires in real-time ✔️ The role of GIS in predicting and responding to fires ✔️ Challenges in making wildfire data more accessible ✔️ What we need to do to prevent future wildfire disasters…
For years, geospatial professionals have been forced to download massive datasets—only to discard most of the data. It’s an outdated, inefficient process that slows down analysis and limits scalability. But a major shift is happening. Cloud-native geospatial is transforming how we store, access, and process spatial data, making it faster, more efficient, and accessible to everyone. In this episode, I sit down with Jed Sundewald, Executive Director of Radiant Earth , to explore how the Cloud-Native Geospatial Forum is shaping the future of GIS, the evolution of cloud-optimized formats like COGs and STAC, and what this means for GIS professionals, developers, and decision-makers. Whether you're new to cloud-native geospatial or looking to optimize your data workflows, this conversation will give you a front-row seat to the future of geospatial technology . 📩 Get every update from my newsletter ➡️ https://forrest.nyc ⬅️ 🏔️ Attend the Cloud Native Geospatial Forum in April ➡️ https://2025-ut.cloudnativegeo.org/ ⬅️ 🔑 Topics Covered: ✔️ Why traditional geospatial workflows are inefficient ✔️ The rise of cloud-native geospatial formats (COGs, STAC, and more) ✔️ How cloud-native GIS benefits both small and large-scale users ✔️ The role of the Cloud-Native Geospatial Forum and upcoming events ✔️ How to integrate cloud-native principles into your geospatial stack…
📩 Get every update from my newsletter ➡️ https://forrest.nyc ⬅️ 🔑 Sign up for Placekey here: https://placekey.io Merging and cleaning location data is one of the biggest headaches in GIS, real estate, and business intelligence. Duplicate addresses, inconsistent formats, and messy datasets can derail even the most sophisticated analysis. But what if there was a universal identifier that made all of those problems disappear?In this episode, I sit down with Hayden Mortimer, President of PlaceKey, to uncover why traditional addresses aren’t enough and how PlaceKey is revolutionizing the way we connect place-based data. We dive into the challenges of entity resolution, the pitfalls of fuzzy matching, and how a simple, open-source identifier is making spatial joins seamless.Whether you work in GIS, data science, or any field that relies on location data, this conversation will change how you think about addressing and spatial relationships. Don’t miss it!✔️ Why addresses alone aren’t reliable for data integration✔️ The hidden challenges of matching places across datasets✔️ How PlaceKey works and why it’s different from other solutions✔️ Real-world use cases for small businesses and enterprise-level applications✔️ The future of location data and entity resolution🎧 Listen now and learn how to fix your messy location data for good!…
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Spatial Stack with Matt Forrest
Matt returns to discuss the future of Spatial Stack —what it is, where it’s headed, and how it will evolve into a go-to platform for exploring the intersection of geospatial technology and real-world impact. From its origins as a live-stream experiment to a full-fledged video-first podcast, this episode lays out the vision for breaking the geospatial echo chamber, identifying new opportunities, and working together to expand the field. Expect a mix of solo deep dives, expert conversations, and practical discussions on geospatial trends, Earth observation, and the growing role of spatial data across industries. Whether you're a seasoned GIS professional or just curious about geospatial’s future, this episode sets the stage for what’s to come.…
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Spatial Stack with Matt Forrest
Apache Sedona has been a core element of the geospatial analytics space for several years now, and in this live stream we will explore how Wherobots is taking this to the next level with different advancements in visualization, powerful geospatial data engineering, and AI.
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Spatial Stack with Matt Forrest
Standardizing spatial data for specific verticals or use cases has been tried many times throughout the history of geospatial. But now we're at a point where things might actually be taking a turn and having a standard format for different use cases be it agriculture, socio-demographics, or any other number of problems might be within sight. We'll talk with Chris Holmes to hear his opinions about why this is changing and why now is the right time to take this on and taking a look at a first use case of this for agricultural field data with fiboa.…
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Spatial Stack with Matt Forrest
How do you get access to just the data you need? And what if that data isn't in large datasets or traditional mapping services? And can AI make this data accessible to those without a background in geospatial? Get answers to these questions and more in this live stream with Hantz Févry, CEO of Stoovo!…
In this conversation with Kyle Barron from Development Seed, we will learn lonboard, a new Python package that solves the problem of visualizing massive geospatial datasets in Python. Learn about the motivations behind the project, some of the tech under the hood, and of course a demo! Sign up for TLDR for free here!…
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