Ground Truth
A blog by Nearmap
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Understanding deep learning in GIS
deep learning in GIS Understanding deep learning in GIS Jan 2025 Jan 2025 Geospatial data is vital for organizations across a range of industries, from urban planning to insurance underwriting and disaster relief. With deep learning, we can now analyze that data faster and more accurately, unlocking powerful insights that drive intelligent decisions. Whether you’re managing infrastructure projects or processing insurance claims , deep learning in GIS is changing the way we interact with the world around us. But what exactly is deep learning in GIS, and how can it benefit your organization? Let’s take a closer look. What is spatial data in deep learning? Geospatial data is any information about a location on Earth, like aerial maps , datasets, and even street addresses. It’s used for spatial analysis tasks from city planning to tracking environmental changes. Traditionally, analyzing spatial data meant manually interpreting aerial imagery . Deep learning can process this data automatically and with greater precision, spotting patterns and trends that humans might miss. What is deep learning in GIS? In simple terms, deep learning in GIS is the use of AI (specifically, neural networks) to analyze geospatial data. These deep learning models are designed to mimic the human brain, learning from massive datasets to recognize objects and trends in things like aerial imagery. For example, Nearmap uses high-resolution aerial images combined with deep learning to automatically detect features like buildings, vegetation, or roads. This allows organizations to reveal location features in seconds, track how these change over time, and make more informed decisions. AI Layers Building Med & High Vegetation Deep learning for mapping Mapping is one area where deep learning in GIS adds immense value. Creating maps with traditional methods required a lot of manual work, but now, with deep learning, much of that effort can be automated. Artificial intelligence can identify and label different features — like roads, buildings, and even land cover classification — through advanced object detection, making the mapping process faster and more accurate. At Nearmap, we pair deep learning with high-resolution aerial imagery to help industries make smarter decisions. Whether tracking urban growth or managing infrastructure, AI-powered mapping saves time and increases accuracy, allowing you to make better decisions faster. Applications of deep learning in GIS Deep learning’s real-world applications are already making an impact across several industries: Urban planning : Deep learning can help city planners understand land use, track development, and make more informed decisions about where to build next. Environmental monitoring : By analyzing changes in ecosystems, deep learning can help spot reductions in vegetation or even detect environmental hazards. Disaster response : After a disaster, deep learning algorithms can analyze aerial images to assess damage and identify risk factors like debris quickly and safely, helping responders act faster. Utilities management : Utility companies can use deep learning to monitor infrastructure like buildings, power lines, and pipelines, spotting potential problems before they become major issues. Insurance : For insurers, deep learning can speed up damage assessments, making it easier to process claims and evaluate risks using accurate, AI-powered imagery. Why Nearmap for deep learning in GIS? Nearmap combines deep learning with GIS to help businesses and governments make smarter decisions. With AI-powered tools that detect over 130 property features — like roof conditions and vegetation — and high-resolution aerial imagery covering up to 87% of the population , you’ll always have the latest data. Our solutions integrate seamlessly with platforms like ArcGIS, allowing you to analyze and visualize spatial data efficiently. Whether you’re in construction , utilities, or insurance, Nearmap gives you the insights to work smarter. Ready to see how our tools can transform your organization? Get in touch
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AI transforming utility asset management
Learn how to inspect over 680 miles of transmission lines in just 11 minutes with Nearmap AI: Automate inspections, reduce risk, and improve accuracy.
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Minimize cost blow-outs with automated EME change detection
Leverage the power of high-resolution aerial imagery and AI to reduce downtime, improve telecommunication network reliability, and minimize cost blow-outs.
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Plan for risk with an intelligent view
Asset managers can meet new fulfilment benchmarks with easy-to-use geospatial intelligence — accurate, shareable insights at a click.
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Nearmap & Betterview: One year later
later Jan 2025 David Tobias, GM of Insurance Jan 2025 David Tobias, GM of Insurance Play A year ago, Nearmap took a bold step by acquiring Betterview , a leader in property intelligence solutions for P&C insurance. At the time, CEO Andy Watt put it perfectly: “Integrating the Betterview platform and AI solutions into the Nearmap technology stack will enable better visualization of the truth on the ground with a richer, more powerful set of AI capabilities that combine the best of both companies.” It was a turning point for both companies — and the industry. Over the past year, we’ve worked together to achieve milestones that wouldn’t have been possible alone. As we look toward 2025, it feels like the perfect moment to reflect on where we’ve been and share a glimpse of where we’re headed. "Best user interface" “We picked the Betterview platform because we thought it was the best user interface for our underwriters to interact with. But when you see what Nearmap does with the frequency of imagery updates and potential in the AI space, it’s even better. These teams coming together to own the whole stack is exciting to see.” — Chad Combs, Vice President, Personal Lines Underwriting, Ohio Mutual Video Testimonial The first end-to-end solution Even before Nearmap acquired Betterview, our longstanding partnership delivered meaningful results for insurers. But it didn’t take long for both teams to see the bigger opportunity: joining forces. Together, we could tackle the industry’s most pressing challenges — like rising property losses, severe weather risks, and inflation — with solutions that went beyond what either company could achieve alone. That vision became a reality in early 2024 with the launch of the first true full-stack property intelligence platform for insurance . By integrating Nearmap high-resolution imagery and pre-processed AI-driven insights with Betterview’s advanced SaaS platform and AI models, we created something truly unique: a solution for faster, smarter insights that empower decision-making at every level. The result? The Betterview platform by Nearmap . Today, this platform provides insurers with unrivaled tools to detect property conditions, model risks, and act quickly with confidence. More than 200 carriers now depend on this unified platform to manage risk, predict and prevent losses, and provide a better experience for their customers. Gen6: An expanded library of AI insights At Nearmap, our focus has always been on one thing: delivering real, practical value to our customers. In 2024, we took a significant step forward with the launch of our 6th generation of AI insights , a milestone reflecting years of learning, iteration, and commitment to solving our customers’ toughest challenges. Why does this matter? This latest evolution of our AI in the Betterview platform empowers insurers to better detect, assess, and mitigate risk across their portfolios. With access to the largest library of property condition detections in the industry, insurers can see risk more clearly and act more decisively. Here’s what’s new: The largest AI detection library : With over 130 property condition detections — including peril-specific risk scores — insurers now have greater visibility into potential risks. Enhanced AI models : Improvements across the board mean higher accuracy and confidence for everything from roof condition to wildfire vulnerability. Validated peril scores : Covering wildfire , hurricane , hail , and wind , these scores are not only predictive of claims but also approved for use in rating plans in numerous states. With these tools, underwriters gain a more holistic understanding of each property’s risk profile. That means faster, more accurate decisions, streamlined workflows, and fewer surprises down the road—all critical to managing costs and improving outcomes. “Gain greater insights” “The advancements that Nearmap continues to make, like the investment in Betterview, help them become a stronger company with more machine learning and artificial intelligence. It is only going to help us gain greater insights into our exposures.” — Rob Jacobson, President & CEO, Rockford Mutual Video Testimonial Proven credibility: Delivering on what matters At Nearmap, trust and reliability aren’t industry buzzwords — they’re at the core of what we do. Over the past year, we focused on two critical goals that demonstrate our commitment to insurers: expanding our imagery coverage and validating our peril models with state regulators. First, we tackled imagery coverage. By integrating data from Hexagon’s Content Program into the Betterview platform, we extended our reach into rural areas, regions that have historically been plagued by infrequent and low-resolution imagery capture. Paired with Nearmap data, which already covers 87% of the U.S. population , insurers now have a clearer, more comprehensive view of properties nationwide, whether urban or rural. What does this mean for insurers? It’s about more than just having great imagery. By combining this expanded coverage with predictive risk scores, regional hazard data, and tools like permit data and replacement cost analysis, insurers can: Streamline underwriting decisions with greater confidence. Cut down on the time and cost of physical inspections. Offer policyholders meaningful mitigation advice. We didn’t stop there. Our second focus, validating AI-powered peril models, led to significant progress. To date, our AI-powered peril models have received regulatory approval in 30 states and Washington, D.C. These filings, completed in collaboration with Milliman Appleseed, allow insurers to quickly adopt advanced models to assess and price risk. Additionally, these models are proven to predict claims for wildfire, wind, hurricane, and hail, and serve as a lifeline for insurers navigating today’s volatile climate. They not only offer deep insights but also help insurers act faster and smarter, ensuring they stay ahead of the next big challenge. Real-world impact: Responding to severe storms 2024 was a year of relentless storms, testing insurers across the country. With one of the most active hurricane seasons on record, the need for rapid, accurate data became clearer. That’s where the Nearmap ImpactResponse System stepped in. The solution delivers rapid, actionable data to help insurers allocate resources effectively and support recovery efforts. Take Hurricane Milton, for example. When the storm devastated Florida on October 9, 2024, insurers needed to act fast. Nearmap delivered: Damage insights within 32 hours of landfall, giving insurers a near-instant view of the situation. Detailed analysis of 5.3 million buildings , identifying 39,000 structures that were majorly damaged or destroyed. Lightning-fast AI processing : A median time of just 2.6 hours, with 90% of damage data ready within 3.4 hours. The result? Insurers could quickly assess losses at the property level, allocate adjusters where they were needed most, and accelerate claims processing like never before. For policyholders, this meant faster payments and a quicker path to recovery. At its core, this isn’t just about technology — it’s about making a tangible difference when it matters most. By equipping insurers with the tools to respond effectively, we’re helping them deliver on their promise to protect and support their customers in their moments of greatest need. “An unparalleled solution” “The combination of Nearmap and Betterview really enhances the suite of products available on the platform. Nearmap’s breadth of imagery delivers an unparalleled solution for underwriters to make decisions.” — Peter Mahler, Vice President, Religious Markets Underwriting, Church Mutual Video Testimonial Looking ahead Year one of the Betterview acquisition has been nothing short of transformative — not just for us, but more importantly, for our insurance customers. By staying in constant dialogue with them, we’ve been able to ensure that every decision we make aligns with their unique business needs. The feedback has been very positive. But we’re not stopping here. With every enhancement to our technology, we’re helping insurers embrace a new era of proactive risk management. It’s about delivering measurable outcomes: better loss ratios, happier policyholders, and faster, smarter decisions across the board. The best part is there’s still much more we can do to serve the industry. With exciting innovations on the horizon in 2025, Nearmap remains committed to accelerating underwriting, streamlining claims response, and reducing loss ratios. Together, we’re not only addressing today’s challenges, we’re shaping the future of insurance.
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The 15 most viewed U.S. locations of 2024
We’re back with our list of the top 15 U.S. locations our users viewed from above in 2024.
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What is geospatial artificial intelligence (GeoAI)?
is geospatial artificial intelligence? What is geospatial artificial intelligence (GeoAI)? Jan 2025 Jan 2025 Imagine understanding locations of interest with just a few clicks — no more lengthy site visits or guesswork. That’s the power of geospatial artificial intelligence (GeoAI). By blending artificial intelligence with geographic information systems (GIS), GeoAI transforms how we analyze and interpret geospatial data . Automatically detecting materials, conditions, and spatial patterns, GeoAI speeds up decision-making and gives businesses the tools they need to act smarter and faster. For industries like insurance , government services, and urban planning, it’s a true game-changer that is reshaping how organizations approach spatial analysis. What is AI in GIS technology? AI in GIS is a way to take traditional geographic systems to the next level. By layering machine learning over vast spatial data, it’s no longer just about looking at maps but uncovering actionable insights from aerial imagery . With AI-powered location intelligence, you can instantly detect key features like solar panels, roof materials, or surface permeability. This means less manual work and more time focusing on what matters: making decisions based on accurate, up-to-date information. What is the role of AI in GIS? AI’s role in GIS is to completely transform how industries use geospatial data. Gone are the traditional methods of relying solely on static maps or historical geospatial data. Today, AI can analyze complex datasets across huge areas, automatically detect property features, and provide real-time insights. GeoAI-based solutions, for instance, can identify everything from roof pitch to vegetation, giving decision-makers the critical data they need for planning, asset management, and risk assessments. How can GIS use artificial intelligence? GeoAI offers practical ways to use AI in GIS: Automate mapping and feature detection: With AI, property features, such as building structures and yard objects, can be detected automatically, speeding up workflows and cutting out the need for manual inspections. Efficient workflow integration: GeoAI insights can seamlessly integrate its insights with existing GIS platforms through APIs or vector layers, enriching your data and making project management more efficient. Frequent updates: Say goodbye to outdated data. Aerial imagery is refreshed multiple times a year in urban areas, so you’re always working with current, accurate information. What are the benefits of GeoAI? GeoAI is changing the way industries operate by delivering faster, more accurate, and scalable solutions: Time savings: Automated AI insights eliminate the need for time-consuming onsite inspections, allowing users to assess property conditions remotely and make quick, informed decisions. Comprehensive analysis: GeoAI offers detailed analysis, instantly detecting features across 87% of the population . This gives you a complete picture of your site’s condition. Improved accuracy: Nearmap AI has been trained over 13 years on a massive dataset of 1.42 million images, powering greater reliability and accuracy Scalable solutions: Whether you’re analyzing a single building or an entire city, GeoAI scales to meet your needs, delivering the insights you need to tackle projects of any size. GeoAI for insurance: Transforming risk assessments and underwriting When it comes to insurance, GeoAI is particularly powerful. AI-powered imagery helps insurers quickly assess property risks , speed up claims processing, and improve underwriting accuracy. For example, by detecting roof condit i ons or solar panels from aerial imagery, insurers can evaluate a property’s risk profile without needing to visit the site. This leads to faster claims processing and more accurate decisions — benefiting both insurers and policyholders. Not just for insurance — GeoAI is also invaluable for government services. With precise, real-time data, government agencies can monitor infrastructure, plan public works, and manage transport systems more effectively. The benefits are clear, from maintaining compliance to improving service delivery. Nearmap GeoAI technologies offer precise, AI-powered insights that help companies understand locations more deeply without conducting labor-intensive on-site inspections. By automating the detection of over 130 property features, from roof conditions to vegetation, GeoAI is reshaping how industries approach spatial analysis. Ready to learn how you could maximize your insights with GeoAI? Get in Touch
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