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