Welcome back, fellow photogrammetry enthusiasts! In our previous blog post, we explored the transformative capabilities of photogrammetry, which turns ordinary images into extraordinary 3D models. Today, let’s delve into the exciting methods of data collection in photogrammetry.
Photogrammetry is a powerful technology that extracts valuable information from images, particularly in the field of geospatial data collection. It opens up a whole new dimension of possibilities. In this blog post, we will explore the methods and techniques professionals use to collect data using photogrammetry. From ground-based image capture to aerial platforms, we’ll discuss optimal shooting techniques, camera settings, and the importance of image overlap and coverage.
Join us on this fascinating journey through the world of geospatial data collection with photogrammetry. Together, we’ll uncover the power and versatility of these approaches and explore their real-world applications.
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When it comes to collecting geospatial data through photogrammetry, there are several methods that utilize different technologies or tools, depending on the desired data outputs and project objectives.
When capturing images for photogrammetry, the technique for image acquisition can vary depending on the specific application and the desired outcome. Here are some common techniques for capturing images on the ground or from the air:
Info source from TOPS
When it comes to sourcing photogrammetry data, there are several avenues you can explore. Consider the following options:
The data required for photogrammetry depends on the specific project and the desired level of detail and accuracy. Generally, the more data you have, the better the results will be. Here are the key types of data needed for the photogrammetry process:
To ensure accurate processing, each point on your object should be visible in at least two photos. Generally, you’ll need around 20 to 250 photos to capture an object well. For a basic 3D model, a minimum of 20 to 30 well-overlapping images is recommended, providing a decent level of accuracy and detail. However, the required number of images can vary based on factors like subject complexity, desired detail level, and the software or algorithm used.
While it’s possible to create a basic 3D model with fewer than 20 images, having more images usually leads to better outcomes. Additional images offer more data points and better coverage, enhancing accuracy and robustness. Taking images from different angles and viewpoints further improves the overall quality and completeness of the 3D model.
Image (1) shows a better 3D model compared to image (2) due to higher number of overlapping images. Image (1) has less distortion and provides greater details of the model compared to image (2).
The number of images needed for 3D modeling depends on whether you’re using orthographic (top-down) or oblique (captured at an angle) imagery. Oblique images generally provide more information and coverage, enabling more accurate and detailed 3D reconstructions.
Flight plans for orthographic images (1), oblique images (2), and an optional set of oblique images at a higher altitude (3) (Skycatch)
Orthographic imagery, captured from a top-down perspective, lacks depth information. To compensate for this, a greater number of well-overlapping images is required, capturing the subject from different angles and viewpoints to reconstruct the missing depth information.
Oblique imagery, captured at an angle, naturally contains more depth information. Consequently, a smaller number of well-overlapping oblique images can be sufficient for creating a 3D model compared to orthographic imagery. However, using a higher number of oblique images still improves accuracy and detail in the final 3D reconstruction.
In summary, a minimum of 20 to 30 well-overlapping images is generally suitable for basic 3D reconstruction with both orthographic and oblique imagery. Oblique images require fewer images due to their richer depth of information. Nevertheless, using more images, regardless of the type, enhances the quality and accuracy of the resulting 3D model.