Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Application of Linearization and Approximation01:29

Application of Linearization and Approximation

127
A drone flying through complex terrain often relies on more than one sensing method to estimate small changes in altitude. Along with direct measurements, air pressure provides a useful indirect indicator of vertical movement. Atmospheric pressure decreases as altitude increases, and this relationship is commonly described using an exponential model. Although accurate, converting pressure measurements into altitude values requires calculations that are too complex to perform repeatedly during...
127
Methods of Obtaining Topography01:25

Methods of Obtaining Topography

397
Topography involves measuring and mapping land elevations, natural features, and artificial structures to create accurate representations of the terrain. Topographic surveying relies on traditional and modern methods, each with distinct advantages and limitations.Traditional Surveying Methods:Transit stadia surveys and plane table surveys were widely used traditional surveying methods. These techniques relied on instruments like theodolites and stadia rods for measuring distances and angles,...
397
Topographic Surveying and Contours01:29

Topographic Surveying and Contours

1.2K
Topographic surveying is critical for documenting the Earth's surface, focusing on capturing elevations, slopes, and natural and man-made features. It is essential in construction planning, water resource management, and land-use analysis. The primary outcome of such surveys is a topographic map, which uses contour lines to visually represent the shape and slope of the terrain, providing valuable insights into the landscape's characteristics.Contour lines are fundamental to understanding the...
1.2K
Levels of Use of a GIS01:29

Levels of Use of a GIS

431
Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...
431
Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device01:30

Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device

438
Surveyors use Global Positioning System (GPS) technology to measure the precise location and elevation of points on Earth. In a recent survey, GPS receivers were used to determine the coordinates and elevations of two park monuments. The process involved careful mission planning, data collection, and correction to ensure accuracy. The survey began with mission planning to identify optimal satellite visibility and minimize Position Dilution of Precision (PDOP). A geodetic control point...
438
Plotting of Topographic Maps01:29

Plotting of Topographic Maps

678
Topographic maps represent the Earth's surface features using contour lines, which connect points of equal elevation to create a two-dimensional representation of three-dimensional terrain. Creating a topographic map requires a systematic approach.Begin by plotting a scaled grid and marking intersections corresponding to the survey's elevation data points. Assign elevation values at these intersections to build the base map. Next, determine contour levels using a consistent contour interval,...
678

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

mRNA and protein expression of fetal insulin receptor in breast cancer cell lines and tissues.

Breast cancer research and treatment·2026
Same author

Highlighting best practices to advance next-generation risk assessment of cosmetic ingredients.

NAM journal·2026
Same author

Diagnostic impact of tau versus amyloid PET in patients with cognitive symptoms.

Brain : a journal of neurology·2026
Same author

Brain Metabolic Signatures of Amyloid-β and Tau Pathology in Corticobasal Syndrome: A Multimodal Biomarker Study.

Movement disorders : official journal of the Movement Disorder Society·2026
Same author

[Study on optimal temperature-wavelength parameters of moxibustion simulator intervention at "Neixiyan" (EX-LE4) and "Waixiyan" (ST35) acupoints for knee osteoarthritis in rats].

Zhen ci yan jiu = Acupuncture research·2026
Same author

Ultrafast, nonblinking single-photon sources from perovskite quantum dots in plasmonic nanocavities.

Science advances·2026

Related Experiment Video

Updated: Mar 11, 2026

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

2.1K

Multi-temporal analysis of mountainous terrain changes based on UAV images and point cloud data.

Tsung-Chin Hou1, Thanh Bao Nhut Trinh2, Tzu-Yi Yang2

  • 1Department of Civil Engineering, National Cheng Kung University, Tainan, Taiwan. tchou@mail.ncku.edu.tw.

Scientific Reports
|March 10, 2026
PubMed
Summary

This study introduces an automated 2D-3D framework for terrain change detection in mountains. The integrated approach enhances accuracy in monitoring landslides and managing environmental changes.

Keywords:
Deep learningMulti-temporal analysisPoint cloud dataTerrain change detectionUAV images

More Related Videos

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging
09:19

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging

Published on: April 18, 2025

1.6K
Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring
08:16

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring

Published on: October 24, 2025

791

Related Experiment Videos

Last Updated: Mar 11, 2026

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

2.1K
Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging
09:19

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging

Published on: April 18, 2025

1.6K
Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring
08:16

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring

Published on: October 24, 2025

791

Area of Science:

  • Geosciences
  • Remote Sensing
  • Computer Vision

Background:

  • Accurate multi-temporal terrain change detection is vital for disaster monitoring and environmental management in mountainous regions.
  • Challenges include complex topography, dense vegetation, and occlusion, hindering traditional methods.
  • Existing 2D methods struggle with shadows and occlusion, limiting their effectiveness.

Purpose of the Study:

  • To develop an integrated, automated framework for reliable terrain change detection in complex mountainous environments.
  • To combine 2D semantic segmentation and 3D geometric analysis for improved accuracy.
  • To support post-disaster assessment, landslide monitoring, and infrastructure management.

Main Methods:

  • Utilized Unmanned Aerial Vehicle (UAV) imagery and point cloud data.
  • Employed DeepLabV3 for multi-class semantic segmentation of orthophotos.
  • Integrated Fast Point Feature Histograms (FPFH), Random Sample Consensus (RANSAC), and Iterative Closest Point (ICP) for geometric analysis.
  • Quantified geometric changes using the Multiscale Model-to-Model Cloud Comparison (M3C2) metric.

Main Results:

  • Achieved a mean Intersection over Union (mIoU) of 87.05% for semantic segmentation.
  • Obtained a root-mean-square error (RMSE) of 4.2 cm for geometric registration of rigid structures.
  • Demonstrated strong generalization with R² = 0.9251 against independent validation data.
  • The 2D-3D fusion detected physical displacements averaging 2.12 m, outperforming 2D-only methods in complex zones.

Conclusions:

  • The proposed 2D-3D fusion framework reliably detects terrain changes in challenging mountainous areas.
  • This integrated approach significantly improves upon 2D-only methods by overcoming occlusion and shadow issues.
  • The framework provides a robust tool for crucial applications in disaster management and environmental monitoring.