High-resolution satellite imagery is now accessible to everyone. This guide explains what high-resolution data really means, where to download free or paid satellite images, and how to choose the right resolution for your project.
Discover what “live satellite imagery” really means, explore near real-time satellite data options, and learn how to access the freshest Earth observation images using free platforms and modern tools like Copernicus and OnGeo Intelligence.
Discover how frequently Google Maps updates its satellite imagery and why it may not meet the needs of time-sensitive projects. Learn alternatives for accessing fresh, high-resolution data on demand.
Learn how to add, visualize, and analyze satellite imagery in QGIS using free, beginner-friendly methods. This guide covers XYZ tiles, WMS/WMTS services, and local raster files, plus practical tips for better rendering and analysis. Discover how tools like OnGeo streamline imagery selection, helping you move faster from raw data to actionable geospatial insights.
This guide shows you where to find the best free satellite imagery , how to download it , how to use it in QGIS , where to get near–real-time images, and what matters when choosing the right dataset. You’ll also see how OnGeo simplifies the whole process by providing ready-made satellite reports with no accounts, no subscriptions, and zero technical skills required.
What Is Satellite Imagery? Satellite imagery refers to pictures of Earth captured by sensors mounted on satellites orbiting the planet. These sensors detect reflected light, emitted radiation, or other wavelengths to record what is happening on the surface below. The result is data—often visual, sometimes multispectral or thermal—that can be analyzed to understand land use, vegetation, infrastructure, water bodies, environmental change, and much more.
This article explains the differences between Digital Elevation Models (DEMs), Digital Terrain Models (DTMs), and Digital Surface Models (DSMs) in satellite Earth observation. It covers their definitions, applications, and data sources, including optical satellites, radar, and LiDAR. By clarifying these concepts and their specific uses, readers will better understand how to select the right elevation model for urban planning, forestry, hydrology, renewable energy, and disaster management.
Satellite image resolution determines how much detail a satellite can capture—from broad environmental patterns to fine-scale urban features. Understanding the differences between low and high resolution helps professionals choose the right data for climate monitoring, urban planning, agriculture, and disaster response.