Quantcast
ZME Science
  • News
  • Environment
  • Health
  • Future
  • Space
  • Features
    Menu
    Natural Sciences
    Health
    History & Humanities
    Space & Astronomy
    Technology
    Culture
    Resources
    Natural Sciences

    Physics

    • Matter and Energy
    • Quantum Mechanics
    • Thermodynamics

    Chemistry

    • Periodic Table
    • Applied Chemistry
    • Materials
    • Physical Chemistry

    Biology

    • Anatomy
    • Biochemistry
    • Ecology
    • Genetics
    • Microbiology
    • Plants and Fungi

    Geology and Paleontology

    • Planet Earth
    • Earth Dynamics
    • Rocks and Minerals
    • Volcanoes
    • Dinosaurs
    • Fossils

    Animals

    • Mammals
    • Birds
    • Fish
    • Reptiles
    • Amphibians
    • Invertebrates
    • Pets
    • Conservation
    • Animals Facts

    Climate and Weather

    • Climate Change
    • Weather and Atmosphere

    Geography

    Mathematics

    Health
    • Drugs
    • Diseases and Conditions
    • Human Body
    • Mind and Brain
    • Food and Nutrition
    • Wellness
    History & Humanities
    • Anthropology
    • Archaeology
    • Economics
    • History
    • People
    • Sociology
    Space & Astronomy
    • The Solar System
    • The Sun
    • The Moon
    • Planets
    • Asteroids, Meteors and Comets
    • Astronomy
    • Astrophysics
    • Cosmology
    • Exoplanets and Alien Life
    • Spaceflight and Exploration
    Technology
    • Computer Science & IT
    • Engineering
    • Inventions
    • Sustainability
    • Renewable Energy
    • Green Living
    Culture
    • Culture and Society
    • Bizarre Stories
    • Lifestyle
    • Art and Music
    • Gaming
    • Books
    • Movies and Shows
    Resources
    • How To
    • Science Careers
    • Metascience
    • Fringe Science
    • Science Experiments
    • School and Study
    • Natural Sciences
    • Health
    • History and Humanities
    • Space & Astronomy
    • Culture
    • Technology
    • Resources
  • Reviews
  • More
    • Agriculture
    • Anthropology
    • Biology
    • Chemistry
    • Electronics
    • Geology
    • History
    • Mathematics
    • Nanotechnology
    • Economics
    • Paleontology
    • Physics
    • Psychology
    • Robotics
  • About Us
    • About
    • The Team
    • Advertise
    • Contribute
    • Privacy Policy
    • Contact
No Result
View All Result
ZME Science

No Result
View All Result
ZME Science

Home → Science

Researchers use machine learning to build 3D maps from historical maps

Literally adding a new dimension to old maps.

Mihai Andrei by Mihai Andrei
May 5, 2021
in History, News, Science, Technology

Historical maps are an important tool for analyzing changes in urban development. But these maps only provide 2D information, and oftentimes not much is known about building height.

With this in mind, a research team from Skoltech (Russia) and FBK (Italy) developed a machine learning algorithm that can assess building height from historical maps, which could help researchers better understand the forces that shaped cities to what we see today.

Image credits: Farella E.M, et al./ MDPI Applied Sciences.

Nowadays, we’ve become pretty used to having 3D maps at our disposal, but this is a luxury we take for granted too easily. For the vast majority of our history, maps and urban imagery were restricted to 2D information.

A team of researchers led by Elisa Mariarosaria Farella from the Fondazione Bruno Kessler (FBK) in Trento, Italy, wanted to see how the height of buildings in historical maps can be inferred. They developed a machine learning algorithm that was first trained on sample data, and then asked it to predict buildings’ heights.

The algorithm’s assessment is based on several “predictors” — variables that are assumed to have some connection (not necessarily a direct or causal connection) to the objective (in this case, the building height). Researchers used things like a building area, its type (whether it was residential, historical, etc), its distance to other buildings, and so on.

They then ground-truthed the model predictions and finessed it with historical photos (where available) and improved mathematical algorithms, using four historical maps of Trento (years 1851, 1887, 1908, and 1936) and Bologna (years 1884 and 1945),

3D view of the inferred building heights (orange) with respect to the ground truth data (white) for the city of Trento. Despite metrics indicating acceptable accuracy, towers seem to produce the most anomalies. Image credits: Farella E.M, et al./ MDPI Applied Sciences.

Overall, the results were good, researchers write in the study.

“The reliability of the proposed approach was verified, testing the method on different datasets and epochs. The achieved results proved to be consistent with our accuracy targets and the complexity of such historical urban contexts. The implemented method is flexible and extendable, relying mainly on geometric and neighbour characteristics derivable from the datasets and adaptable categorical data.”

Image credits: Farella E.M, et al./ MDPI Applied Sciences.

They are now looking at ways to improve the process even further and generalize the method, which could make it much easier to digitize historical maps from all around the world and enhance them to 3D.

“The implemented learning and predictive procedure tested on historical data has proved to be effective and promising for many other applications. Based on few attributes for the prediction, it will soon be expanded to diverse real-life contexts with missing elevation data. The resulting models will be a great help in bridging the geospatial knowledge gap in past or remote situations” Emre Ozdemir, a Skoltech and FBK Trento PhD student, explains.

The study was published in MDPI Applied Sciences.

Was this helpful?
Thanks for your feedback!
Related posts:
  1. Researchers use machine learning algorithm to detect low blood pressure during surgery
  2. Could machine learning help us develop next-generation materials? These researchers believe so
  3. Time travel is proven possible — but we’ll likely never be able to build the machine, author says
  4. Machine learning could solve the US’s police violence issue
  5. Machine learning is paving the way towards 3D X-rays

ADVERTISEMENT
  • News
  • Environment
  • Health
  • Future
  • Space
  • Features
  • Reviews
  • More
  • About Us

© 2007-2021 ZME Science - Not exactly rocket science. All Rights Reserved.

No Result
View All Result
  • News
  • Environment
  • Health
  • Future
  • Space
  • Features
    • Natural Sciences
    • Health
    • History and Humanities
    • Space & Astronomy
    • Culture
    • Technology
    • Resources
  • Reviews
  • More
    • Agriculture
    • Anthropology
    • Biology
    • Chemistry
    • Electronics
    • Geology
    • History
    • Mathematics
    • Nanotechnology
    • Economics
    • Paleontology
    • Physics
    • Psychology
    • Robotics
  • About Us
    • About
    • The Team
    • Advertise
    • Contribute
    • Privacy Policy
    • Contact

© 2007-2021 ZME Science - Not exactly rocket science. All Rights Reserved.

Don’t you want to get smarter every day?

YES, sign me up!

Over 35,000 subscribers can’t be wrong. Don’t worry, we never spam. By signing up you agree to our privacy policy.

✕
ZME Science News

FREE
VIEW