Fundamentals of Capturing and Processing Drone Imagery and Data

Cover
Half Title
Title Page
Copyright Page
Table of Contents
Preface
Acknowledgments
Editors
Contributors
Acronyms and Abbreviations
Part I: Getting Started with Drone Imagery and Data
Chapter 1: Introduction to Capturing and Processing Drone Imagery and Data
Introduction
Book Structure
Drone Terminology
Flying and Safe Operations
Platforms
Fixed-Wing Platforms
Rotary-Wing Platforms
Which Platform to Choose?
Payload
Cameras and Non-imagery Sensors
Drone Applications
Agriculture
Wildlife Surveys
Geomorphology
Historical and Cultural Heritage Preservation
Atmospheric Studies
Other Applications (Table 1.1)
Ethics and Privacy
References
Chapter 2: An Introduction to Drone Remote Sensing and Photogrammetry
Introduction
Remote Sensing with Drones
A Brief History of Aerial Photography and Photogrammetry
Origins of Photography
Origins of Aerial Photography
Photogrammetry and Modern Mapping
Modern Photogrammetry Using Drone Imagery
General Considerations for Capturing Images with Drones
Radiometric Errors and Effects
Radiometric Correction
Geometric Errors and Effects
Georeferencing and Geometric Correction
Doming and Dishing
Data Products Derived from Drone Images
Georeferenced Point Clouds
Digital Elevation Models
Orthophotos and Orthomosaics
Image Enhancement and Classification
Radiometric Enhancement
Spatial Enhancement
Spectral Enhancement
Image Classification
Summary
References
Suggested Readings
Chapter 3: Choosing a Sensor for UAS Imagery Collection
Introduction
Passive and Active Sensors
Passive Sensors
Pushbroom versus Frame Cameras
Active Sensors
Discrete Return versus Full-Waveform Lidar
Sensor Characteristics
Sensor Size and Resolution
Focal Length
Shutter Type
Lens Type
Gimbals
Additional Considerations
Geometric Camera Calibration
Boresight Calibration
Radiometry and Radiometric Calibration
Radiometric Calibration
Common Passive Sensors used with Drones
RGB Cameras
Multispectral Sensors
Hyperspectral Sensors
Thermal Cameras
Radiometric Accuracy
Resolution and Frame Rate
Summary
References
Chapter 4: Mission Planning for Capturing UAS Imagery
Introduction
Defining Product Specifications and Accuracy Requirements
Researching Operational Site Restrictions
Topographic Maps
Sectional Aeronautical Charts
Selecting an Imaging Sensor and Computing Image Geometry
The Digital Sensor (Camera)
Focal Plane and CCD Array
Lens Cone and Camera Lens
Shutters
Filters
Diaphragm
Geometry of Vertical Imagery
Scale of Vertical Imagery
Imagery Overlap
Image Ground Coverage
Planning Aerial Imagery Collection
Design a Flight Plan
Project Geometry and Flying Direction
Camera Mounting
Computing the Number of Flight Lines
Computing the Number of Images
Computing the Flying Altitude
UAS Flight Speed for Image Collection
Computing the Time between Consecutive Images
Waypoints
Exercise to Design a Flight Plan and Layout
Estimating Costs and Developing a Delivery Schedule
Delivery Schedule
Solution to Design a Flight Plan and Layout
Chapter 5: Drone Regulations: What You Need to Know before You Fly
The U.S. Code of Federal Regulations
The Most Recent Drone Regulations: 14 CFR Part 107
Regulation versus Guidance: Safe Operations Are More than a One-Stop Shop
History of Drone Regulations: The Field Is Older than You Might Think
The Evolution of CFR 14 (And Its Many Acronyms!)
Public Operations: Not as Simple as They May Seem
333 Exemption: A Stopgap Measure
Recreational Operations: Disruptive Regulation
14 CFR Part 107…Finally!
The Final Word for Now: FAA Reauthorization Act of 2018
Key Components for Safe Operations: Checklists and Emergency Procedures
Solutions to Hands-On Activities
Box 5.1 Hands-On Activity - Can You Find the Helicopter?
Box 5.4 Safe Operations Activity
UM Phantom 4 Pro field preflight checklist
UM Phantom 4 Pro field post-flight checklist
References
Chapter 6: Structure from Motion (SfM) Workflow for Processing Drone Imagery
Introduction
Image Processing with Structure from Motion (SfM)
Georeferencing
Multi-View Stereo
Data Products
Digital Elevation, Terrain, and Surface Models
Orthophotos
SfM Considerations
Image Capture
Camera Calibration
Image Characteristics
Multispectral and Hyperspectral Imaging Data
Software
Applications
Outlook
References
Software Resources
Chapter 7: Aerial Cinematography with UAS
Introduction
Quantitative Mapping versus Qualitative Videos
Geographic Communication with Aerial Cinematography
Abstracted Views and Phantom Rides
Communicating through UAS Aerial Cinematography
Camera Angle
Navigation
Narration
Planning and Executing a Successful UAS Aerial Cinematography Mission
Selecting a Platform and Accessories
Techniques for Capturing Great Videos
Example Applications for UAS Aerial Cinematography
Environmental and Social Impact Assessments
Tourism
Journalism
Community Engagement
Participatory Methods and Mapping
References
Other Useful Links
Open-source Hollywood
Part II: Hands-On Applications Using Drone Imagery and Data
Chapter 8: Planning Unoccupied Aircraft Systems (UAS) Missions
Learning Objectives
Hardware and Software Requirements
Part 1: Overview of Mission Planner
Exercise 1.1: Downloading and Installing Mission Planner
Exercise 1.2: Navigating Mission Planner
Part 2: Mission Planning in a Familiar Landscape
Exercise 2.1: Exploring the Area of Interest
Exercise 2.2: Defining the Boundaries of the Area of Interest
Exercise 2.3: Creating the UAS Mission
Part 3: Mission Planning for the Unfamiliar Landscape
Exercise 3.1: Exploring the Area of Interest
Exercise 3.2: Defining a UAS Mission within an Area of Interest
Exercise 3.3: Creating the UAS Mission
Optional Exercise: Collect Study Area GPS Data Yourself
Discussion and Synthesis Questions
Acknowledgments
References
Chapter 9: Aligning and Stitching Drone-Captured Images
Learning Objectives
Hardware and Software Requirements
Introduction
Workflow for Stitching Drone-captured Images
General Considerations for High-quality Image Stitching
Exercise: Creating a Stitched Orthomosaic from Drone-captured Images
Discussion and Synthesis Questions
Acknowledgments
References
Chapter 10: Counting Wildlife from Drone-Captured Imagery Using Visual and Semi-Automated Techniques
Learning Objectives
Software and Hardware Requirements
Introduction
Methods for Computer-aided Image Interpretation
Study Area and Data
Workflow and Exercises
Exercise 1: Visually Interpreting Drone Images for Counting Greater Crested Terns
Exercise 2: Semi-automated Wildlife Counting
Exercise 3: Evaluating Performance and Accuracy
Discussion and Synthesis Questions
Acknowledgments
References
Chapter 11: Terrain and Surface Modeling of Vegetation Height Using Simple Linear Regression
Learning Objectives
Hardware and Software Requirements
Datasets
Introduction
Part 1: Developing a Digital Elevation Model (DEM)
Exercise 1.1: Building the SfM Point Cloud
Exercise 1.2: Classifying Ground Points for the SfM Point Cloud
Exercise 1.3: Creating a DEM Using Classified Ground Points
Part 2: Mapping Vegetation Height using 3D Data
Exercise 2.1: Importing SfM Points into a GIS and Calculating Their Height above Ground
Exercise 2.3: Performing Simple Linear Regression and Applying Height Estimate Models to the Entire Study Area
Acknowledgments
References
Chapter 12: Assessing the Accuracy of Digital Surface Models of an Earthen Dam Derived from SfM Techniques
Learning Objectives
Hardware and Software Requirements
Introduction
Study Area and Data Collection
Part 1: Evaluating 3D Model Accuracy using only the Geotagged Images
Exercise 1.1: Evaluate the Accuracy of a 3D Model Derived from Flight 1
Exercise 1.2: Evaluate the Accuracy of a 3D Model Derived from Flight 2 and Flight 3
Part 2: Evaluating the Impact of GCP Density and Distribution on DSM Accuracy
Exercise 2: Evaluate the Vertical Accuracy of the DSM Generated Using Flights 2 and 3 with a Variable Number of GCPs
Summary and Wrap-Up
Discussion And Synthesis Questions
Collecting the Data Yourself (Optional)
Acknowledgments
References
Chapter 13: Estimating Forage Mass from Unmanned Aircraft Systems in Rangelands
Learning Objectives
Hardware and Software Requirements
Introduction
Study Area
Part 1: Processing UAS Imagery into a DSM and Orthomosaic
Part 2: Linear Regression: Volumes and Forage Mass
Part 3: Forage Mass Estimation
Discussion and Synthesis Questions
Acknowledgments
References
Other Resources
Chapter 14: Applications of UAS-Derived Terrain Data for Hydrology and Flood Hazard Modeling
Learning Objectives
Hardware and Software Requirements
Part 1: Getting to Know the Terrain and Hydrology of the Study Area
Introduction
Study Area
Exercise 1: Visualize and Examine Digital Elevation Models of the Study Area
Exercise 2: Analyze Terrain with Neighborhood Functions
Part 2: Modeling Flood Hazard with Drone Data
Exercise 2.1: Load UAS Terrain Data into HEC-RAS
Exercise 2.2: Model Flow Area Setup
Exercise 2.3: Modeling Unsteady Flow
Exercise 2.4: Visualizing the Modeling Results
Discussion and Synthesis Questions
Collecting the Data Yourself (OPTIONAL)
Acknowledgments
Notes
References
Chapter 15: Comparing UAS and Terrestrial Laser Scanning Methods for Change Detection in Coastal Landscapes
Learning Objectives
Hardware and Software Requirements
Objectives and Key Concepts
Introduction
Coastal Foredune Systems
Geomorphic Change Detection (GCD)
Exercise: Terrain Modeling and Geomorphic Change Detection in a Dynamic, Vegetated Coastal Dune Landscape
Exercise 1: Simple Geomorphic Change Detection Comparison Using UAS-Derived DSMs
Exercise 2: Examining Geomorphic Change Detection Differences between UAS and TLS-Derived Datasets
Exercise 3: Spatial-Temporal Geomorphic Change Detection Using Repeat DEMs to Analyze Landscape Morphodynamics
Discussion and Synthesis Questions
Collecting the Data Yourself (Optional)
Gradual Selection
Tie Point Quality Control:
Weighing Observations
Outlier Observations of GCPs
Build Dense Cloud
Ground Point and Vegetation Classification
Build Mesh
Build Texture
Build Digital Elevation Model (DEM)
Build Orthomosaic
Note
References
Chapter 16: Digital Preservation of Historical Heritage Using 3D Models and Augmented Reality
Learning Objectives
Hardware and Software Requirements
Datasets
Introduction
Considerations when Capturing Drone Imagery for Digital Preservation
Regulations and Sensitivities
Representation of Area of Interest
Time of Data Acquisition
Camera Angle
Historical Context: The Old Athens Cemetery
Part 1: Image Collection and Generation of 3D Models and Orthomosaic
Ground Level Image Collection
Exercise 1.1: Building a 3D Model of a Historical Landscape
Exercise 1.2: Building a Detailed 3D Model of a Historical Object
Exercise 1.3: Product Integration and 3D Model Visualization Using a Geographic Information System
Part 2: Using Augmented Reality to Explore Computer Vision-Derived 3D Models
Discussion and Synthesis Questions
Acknowledgments
References
Chapter 17: Identifying Burial Mounds and Enclosures Using RGB and Multispectral Indices Derived from UAS Imagery
Learning Objectives
Hardware and Software Requirements
Introduction
Indices Computed from RGB Imagery
Indices Computed from Multispectral Imagery
Part 1: Generating an Orthomosaic from UAS-Derived RGB Imagery
Exercise 1.1: Building a Sparse Point Cloud and Mesh
Exercise 1.2: Optimizing the Sparse Point Cloud
Exercise 1.3: Building a 3D Model (Mesh)
Exercise 1.4: Generating an Orthomosaic
Part 2: Generating Spectral Indices from UAS-Derived Orthomosaics
Exercise 2.1: Setting Up R & RStudio
Exercise 2.2: Working with the RGB Orthomosaic
Exercise 2.2.1: Convert the RGB Orthomosaic to the Desired Resolution and Projection
Exercise 2.2.2: Crop the RGB Orthomosaic to the Desired Extent
Exercise 2.2.3: Calculate Spectral Indices Using the RGB Orthomosaic
Exercise 2.3: Working with the Multispectral Orthomosaics
Exercise 2.3.1: Change the Multispectral Orthomosaics to the Desired Resolution and Projection
Exercise 2.3.2: Crop the Multispectral Orthomosaics to the Desired Extent
Exercise 2.3.3: Reset the Origin of the Multispectral Orthomosaics
Exercise 2.3.4: Calculate Indices from the Multispectral Orthomosaics
Discussion and Synthesis Questions
Acknowledgments
References
Chapter 18: Detecting Scales of Drone-Based Atmospheric Measurements Using Semivariograms
Learning Objectives
Hardware and Software Requirements
Introduction
Traditional Atmospheric Measurement Technologies
Using Drones to Collect Atmospheric Measurements
Spatial Statistics and Geostatistics
Spatial Dependence and the Semivariogram
Exercises
Data and Code
Exercise 1: Computing a Sample Variogram and Fitting a Model
Exercise 2: Analyzing Scale Changes in Different Atmospheric Situations
Discussion and Synthesis Questions
Collecting the Data Yourself (Optional)
Acknowledgments
References
Chapter 19: Assessing the Greenhouse Gas Carbon Dioxide in the Atmospheric Boundary Layer
Learning Objectives
Hardware and Software Requirements
Introduction
Exercise 1: Post-Processing UAS Atmospheric Data
EXERCISE 2: Visualizing Meteorological and CO 2 Boundary Layer Data
Discussion and Synthesis Questions
Collecting the Data Yourself (Optional)
References
Glossary
Index