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

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

417
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...
417
Field Application of Global Positioning System01:28

Field Application of Global Positioning System

334
The Global Positioning System (GPS) has become an indispensable tool in fieldwork, offering unparalleled precision and efficiency for surveying, navigation, and infrastructure development. By harnessing signals from a constellation of satellites, GPS receivers determine the location of objects with remarkable speed and accuracy, often completing calculations within a second.Advantages of Modern GPS TechnologyContemporary GPS receivers are designed to meet the practical demands of field...
334
Types of Global Positioning System Surveys01:30

Types of Global Positioning System Surveys

381
GPS surveying methods vary in application, accuracy, and data collection techniques, catering to diverse surveying and mapping needs. Static GPS, kinematic GPS, and real-time kinematic (RTK) surveying are widely used. Each technique offers distinct advantages.Static GPS involves placing one receiver at a known reference point and another at the target point. It collects exact positional data by observing multiple satellite ranges over an extended period, achieving centimeter-level accuracy for...
381
Methods of Obtaining Topography01:25

Methods of Obtaining Topography

342
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,...
342
Introduction to Surveying, Plane Surveying and Geodetic Surveys01:27

Introduction to Surveying, Plane Surveying and Geodetic Surveys

1.1K
Surveying is the art and science of mapping the earth's surface. It involves measuring distances, angles in horizontal or vertical directions, and levels to understand the shape and size of land features. Surveying techniques are essential for various tasks, such as identifying the levels of a land area with reference to a specific point, and mapping undulations and water bodies.There are two main types of surveying: plane surveys and geodetic surveys. Plane surveys assume the earth is flat,...
1.1K
Application of Linearization and Approximation01:29

Application of Linearization and Approximation

105
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...
105

You might also read

Related Articles

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

Sort by
Same author

Object Detection for Agricultural Vehicles: Ensemble Method Based on Hierarchy of Classes.

Sensors (Basel, Switzerland)·2023
Same author

Anomaly Detection for Agricultural Vehicles Using Autoencoders.

Sensors (Basel, Switzerland)·2022
Same author

Weed Classification Using Explainable Multi-Resolution Slot Attention.

Sensors (Basel, Switzerland)·2021
Same author

Robust Species Distribution Mapping of Crop Mixtures Using Color Images and Convolutional Neural Networks.

Sensors (Basel, Switzerland)·2021
Same author

A Novel Locating System for Cereal Plant Stem Emerging Points' Detection Using a Convolutional Neural Network.

Sensors (Basel, Switzerland)·2018
Same author

Weed Growth Stage Estimator Using Deep Convolutional Neural Networks.

Sensors (Basel, Switzerland)·2018

Related Experiment Video

Updated: Feb 18, 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

Designing and Testing a UAV Mapping System for Agricultural Field Surveying.

Martin Peter Christiansen1, Morten Stigaard Laursen2, Rasmus Nyholm Jørgensen3

  • 1Department of Engineering, Aarhus University, Finlandsgade 22, 8200 Aarhus N, Denmark. mpc@eng.au.dk.

Sensors (Basel, Switzerland)
|November 24, 2017
PubMed
Summary

This study demonstrates how Unmanned Aerial Vehicle (UAV)-mounted Light Detection and Ranging (LiDAR) can map winter wheat fields. LiDAR data accurately estimates crop biomass and volume, correlating with nitrogen treatments.

Keywords:
aerial roboticscanopy estimationcrop monitoringpoint cloudwinter wheat mapping

More Related Videos

Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images
11:49

Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images

Published on: February 2, 2019

9.9K
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

666

Related Experiment Videos

Last Updated: Feb 18, 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
Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images
11:49

Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images

Published on: February 2, 2019

9.9K
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

666

Area of Science:

  • Agricultural Engineering
  • Remote Sensing
  • Geospatial Analysis

Background:

  • Accurate crop biomass estimation is crucial for precision agriculture.
  • Unmanned Aerial Vehicles (UAVs) equipped with Light Detection and Ranging (LiDAR) offer a promising method for high-resolution environmental mapping.
  • Integrating data from Global Navigation Satellite System (GNSS) and Inertial Measurement Unit (IMU) sensors enhances the accuracy of UAV-based mapping.

Purpose of the Study:

  • To develop and evaluate a sensory UAV setup for detailed mapping and analysis of agricultural fields.
  • To correlate LiDAR-derived crop height measurements with varying nitrogen treatments in winter wheat.
  • To assess the impact of different flight patterns on LiDAR-based crop volume estimation.

Main Methods:

  • LiDAR data acquisition using a UAV, combined with GNSS and IMU sensor data.
  • Environment mapping and point cloud generation utilizing the Robot Operating System (ROS) and Point Cloud Library (PCL).
  • Crop volume estimation using a voxel grid with a spatial resolution of 0.04 × 0.04 × 0.001 m.

Main Results:

  • Crop height estimates (0.35-0.58 m) showed a correlation with nitrogen application rates (0-300 kg N ha⁻¹).
  • LiDAR mapping successfully characterized the winter wheat field, providing detailed point cloud data.
  • Analysis indicated that flight patterns influence the accuracy of crop volume estimations.

Conclusions:

  • UAV-LiDAR systems provide a viable tool for precise agricultural field mapping and biomass assessment.
  • The proposed methodology enables accurate correlation between crop characteristics and agricultural inputs like nitrogen.
  • Further optimization of flight patterns can enhance the reliability of UAV-based crop volume estimations.