West Palm Beach, Florida | June 26, 2025 - Earth Systems has launched its new Remote Sensing and AI Solutions service, which they say will specialize in delivering geospatial intelligence through the integration of satellite imagery and artificial intelligence. The offering is designed to support environmental analysis and monitoring across industries such as land management, oil and gas, mining, and coastal resource planning.
The new service combines imagery from satellites and aerial platforms to analyze large geographic areas and monitor changes over time. Their multi-resolution approach for satellite imagery analysis enables both broad-scale and detailed assessments, allowing for tailored analyses based on specific client needs.
In addition to remote sensing data, Earth Systems is applying AI and machine learning techniques to improve the efficiency and accuracy of geospatial analysis. These methods support automated classification, object detection, and trend prediction, allowing the team to process large datasets and identify patterns in land cover, environmental conditions, and resource distribution.
“With Earth Systems’ Remote Sensing and AI Solutions, we will deliver scalable, data-driven insights that empower decision-making across environmental and resource management,” said Rick Ofsanko, founder of Earth Systems.
Key features of the new service include:
- Integration of high-, moderate-, and low-resolution imagery to balance detail and coverage of areas of interest
- Repeated observations to track trends, detect anomalies, and assess impacts over time
- AI-driven analytics for automated classification, object detection, and predictive modeling
- Tailored solutions that address specific operational, regulatory, or research objectives
The company says the solution is suited for a range of uses including environmental monitoring, due diligence assessments, water and coastal management, and natural resource exploration. By combining satellite data with AI-powered analysis, Earth Systems aims to reduce the time and cost typically associated with large-scale spatial intelligence projects.
