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

Common Leveling Mistakes and Errors01:17

Common Leveling Mistakes and Errors

63
A survey team is tasked with determining the elevation difference between points Point A and Point B, separated by uneven terrain. They use a leveling instrument and a leveling rod.Common MistakesMisreading the Rod: During a backsight reading at Point A, the instrumentman observes the rod partially obscured by tall grass. Instead of reading 1.135 m, they mistakenly record 1.735 m due to the misalignment of the crosshair with the wrong graduation. This error adds 0.600 m to all subsequent...
63
Survival Tree01:19

Survival Tree

63
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
63
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

26
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...
26
Distance Corrections01:15

Distance Corrections

26
To achieve precise distance measurements, especially in surveying and construction, certain corrections must be applied to account for potential sources of error like the standardization errors, temperature variations, and slope adjustments.Standardization error emerges when measurement equipment undergoes changes, such as wear, repairs, or weather impacts. To address this, surveyors compare the equipment’s readings to a standard. This process identifies any deviation that might lead to...
26

You might also read

Related Articles

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

Sort by
Same author

Association between exposure to perfluoroalkyl ether sulfonate F-53B and cervical cancer risk and its mechanisms of cervical toxicity in Chinese women.

Ecotoxicology and environmental safety·2026
Same author

Advances in epigenetic regulation of potassium channels in chronic pain.

Molecular biology reports·2026
Same author

Conserved cellular signals and mechanisms accompany the reproductive shutdown of honey bee (Apis mellifera) queens for dispersal.

Communications biology·2026
Same author

Detrimental impacts of ammonia exposure during marine heatwaves on the starry flounder (Platichthys stellatus).

Journal of environmental sciences (China)·2026
Same author

An epigenetically enhanced whole-cell vaccine in a stimulatory hydrogel for robust antitumor immunity.

Biomaterials·2026
Same author

Natural photosynthetic system for restoring homeostasis of animal organelle interaction network.

Nature communications·2026

Related Experiment Video

Updated: Jun 11, 2025

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.3K

LightGBM hybrid model based DEM correction for forested areas.

Qinghua Li1, Dong Wang1, Fengying Liu1

  • 1College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao, Shandong, China.

Plos One
|October 7, 2024
PubMed
Summary

This study introduces a novel CNN-LightGBM model, enhanced with the FA-SSA algorithm, to significantly improve the accuracy of digital elevation models (DEMs) in forested areas. The advanced model demonstrates superior performance in correcting elevation errors for better canopy height monitoring and ecological analysis.

More Related Videos

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

1.3K
Leaf Area Index Estimation Using Three Distinct Methods in Pure Deciduous Stands
00:09

Leaf Area Index Estimation Using Three Distinct Methods in Pure Deciduous Stands

Published on: August 29, 2019

13.5K

Related Experiment Videos

Last Updated: Jun 11, 2025

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.3K
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

1.3K
Leaf Area Index Estimation Using Three Distinct Methods in Pure Deciduous Stands
00:09

Leaf Area Index Estimation Using Three Distinct Methods in Pure Deciduous Stands

Published on: August 29, 2019

13.5K

Area of Science:

  • Geosciences and Remote Sensing
  • Forestry and Ecological Monitoring
  • Artificial Intelligence in Geospatial Analysis

Background:

  • Digital Elevation Models (DEMs) are crucial for forest canopy height monitoring and ecological studies.
  • Existing DEMs exhibit significant errors in forested regions due to canopy occlusion and terrain complexity.
  • Accurate DEMs are essential for reliable environmental analysis and topographic mapping.

Purpose of the Study:

  • To develop and validate a hybrid Convolutional Neural Network (CNN)-LightGBM model for correcting DEM errors in diverse forest types.
  • To enhance the model's optimization using a novel Firefly Algorithm-based Sparrow Search Optimization (FA-SSA) algorithm.
  • To assess the model's performance against existing methods using high-accuracy ground truth data.

Main Methods:

  • A CNN-LightGBM hybrid model utilizing Densenet architecture was developed.
  • The model was optimized using an improved Sparrow Search Algorithm incorporating the Firefly Algorithm (FA-SSA).
  • Elevation data from ICESat-2 and airborne LiDAR were used for validation across tropical, coniferous, mixed, and broad-leaved forests.

Main Results:

  • The CNN-LightGBM model demonstrated a significant improvement in R-squared values (>0.05) compared to standalone LightGBM, CNN-SVR, and SVR models.
  • The FA-SSA-CNN-LightGBM model achieved the highest accuracy, with a Root Mean Square Error (RMSE) of 1.09 meters, reducing RMSE by over 30%.
  • Accuracy improvements exceeded 50% compared to other widely used DEMs like FABDEM and GEDI in forested areas.

Conclusions:

  • The FA-SSA-CNN-LightGBM model offers a highly accurate and feasible solution for correcting DEM errors in complex forested environments.
  • This method significantly advances the quality of DEMs for applications in global topographic mapping and ecological research.
  • The study highlights the potential of advanced AI techniques for improving geospatial data accuracy in challenging terrains.