Photogrammetry Statistics


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Photogrammetry Statistics 2023: Facts about Photogrammetry outlines the context of what’s happening in the tech world.

LLCBuddy editorial team did hours of research, collected all important statistics on Photogrammetry, and shared those on this page. Our editorial team proofread these to make the data as accurate as possible. We believe you don’t need to check any other resources on the web for the same. You should get everything here only 🙂

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Top Photogrammetry Statistics 2023

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Photogrammetry “Latest” Statistics

  • Photos taken in a sequence should overlap by at least 60% – if there is meager overlap, the model will not develop correctly or at all.[1]
  • Four points representing 17.4% of the H-dataset data in the DAM slope were deleted from the total of 23 points utilized for validation.[2]
  • From 2020 to 2030, the employment of cartographers and photogrammetrists is anticipated to increase by 5%, which is a slower rate than the national average for all professions.[2]
  • The kinetic energy of the fragments is comprised of 12% –24% of the absorbed energy, and the fraction climbs as the strain rate increases.[2]
  • The slope was greater than 40% and the checkpoints placed in the model’s border occurred at low precision due to the interpolation methods during the photogrammetric reconstruction.[2]
  • Camera positions are assessed by matching related features in pairs of images involving 60% to 80% of scene overlap and less than 30º between the images.[2]
  • From 2021 to 2031, the employment of cartographers and photogrammetrists is anticipated to increase by 3%, albeit more slowly than the average for all professions.[3]
  • SfM has significant promise for forest mapping in underdeveloped nations since more than half of the world’s forest-covered regions have a canopy cover of 50%.[4]
  • Given a confidence level of 5% and 22 degrees of freedom, the findings suggest that there is a trend in the E-N discrepancies, suggesting systemic mistakes that may be investigated further using circular statistic approaches.[5]
  • Due to the interpolation techniques used during the photogrammetric reconstruction, the slope was larger than 40%, and the checkpoints situated in the model’s boundary produced poor accuracy.[5]
  • With at least 90% confidence and 22 degrees of freedom, the ortho mosaic fit in Class D on a scale of 1:2,000 and in Class B on a scale of 1:5000.[5]
  • Accuracy-checking standards presume that at least 90% of the data goes down within a range of the mean plus two times the standard deviation.[5]

Also Read

How Useful is Photogrammetry

One of the key advantages of photogrammetry is its ability to capture detailed and accurate data without the need for expensive equipment or specialized training. All that is required is a camera, whether a professional DSLR or a simple smartphone, and software that can process the images. This means that anyone with access to these tools can perform photogrammetry, making it an accessible and versatile technology.

In the field of engineering, photogrammetry can be used to map and monitor construction sites, create topographical maps, and assess the condition of infrastructure. By collecting data with photographs, engineers can accurately measure distances, angles, and volumes, which is crucial for planning and executing construction projects. This not only improves the efficiency and accuracy of engineering processes but also reduces the risk of errors and costly mistakes.

In geology, photogrammetry is used to analyze the surface of the earth and identify geological features such as faults, folds, and fractures. By capturing detailed images of the terrain from different angles, geologists can create 3D models that reveal hidden structures and patterns. This information is invaluable for understanding the geological history of an area, predicting natural disasters, and planning conservation efforts.

Archaeologists also rely on photogrammetry to document and analyze historical sites and artifacts. By photographing ancient ruins, monuments, and artifacts, archaeologists can reconstruct digital models that preserve these cultural treasures for future generations. This technology has been instrumental in uncovering new discoveries, piecing together shattered relics, and providing insights into the past.

What makes photogrammetry so useful is its ability to capture data in a non-invasive manner. Unlike traditional methods that require physical contact with an object or site, photogrammetry allows for remote data collection, which is particularly important in sensitive environments or historical sites. This minimizes the risk of damage and disturbance, ensuring the preservation of valuable resources for future research.

Furthermore, photogrammetry can be performed quickly and efficiently, saving time and resources compared to traditional surveying methods. With the advent of drones and other aerial platforms, photogrammetry can now be used to map large areas and provide high-resolution data in a matter of hours. This capability is especially beneficial in disaster response, where quick and accurate assessments are crucial for coordinating emergency efforts.

In conclusion, the utility of photogrammetry cannot be overstated. Its ability to capture precise measurements and detailed models from photographs has transformed the way we collect and analyze data in various fields. From engineering and geology to archaeology and disaster response, photogrammetry offers a cost-effective, non-invasive, and efficient solution for gathering critical information. It is a tool that continues to push the boundaries of what is possible, offering endless possibilities for innovation and discovery.

Reference

  1. wiley – https://onlinelibrary.wiley.com/doi/10.1111/phor.12299
  2. webinarcare – https://webinarcare.com/best-photogrammetry-software/photogrammetry-statistics/
  3. bls – https://www.bls.gov/ooh/architecture-and-engineering/cartographers-and-photogrammetrists.htm
  4. mdpi – https://www.mdpi.com/1999-4907/8/3/68
  5. tandfonline – https://www.tandfonline.com/doi/full/10.1080/22797254.2020.1717998

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