README

This code is designed to be run using the drake package, by running the code in the script make.R either via the command line (i.e., R CMD BATCH make.R), or from within an interactive R session. The outline of all project components (i.e., the drake plan) is available in the R/subplans directory.

The drake Github page page has a good overview of what drake does, and includes some code snippets. After running the make.R script, the drake::loadd function is the most helpful function for loading output.

The drake documentation itself is also a good resource for learning how to use the drake package.
Starting with the Walkthrough is a decent place to just jump in to some details.

   

Code and data from:
A Bayesian approach for predicting photogrammetric uncertainty in morphometric measurements derived from UAS
KC Bierlich, Robert Schick, Josh Hewitt, Julian Dale, Jeremy Goldbogen, Ari Friedlaender, David Johnston
Marine Ecology Progress Series
DOI: https://doi.org/10.3354/meps13814.

Data formats

The Error measurement model is implemented in the model_joint.R script. The model implementation is abstract, to allow multiple observations of any object. The data_plan.R script creates the necessary, raw data structures for the model. The flatten_data() function munges the data structures for use with the model’s implementation in nimble.

Training object information

Each training object must be documented in the same format as the training_obj object (below). The first two columns specify the training object, and the third column records its known length. The flatten_data() function will use the information in training_obj to associate known lengths with image and pixel measurements of the training objects.

Subject	Measurement	Length
Training object	Total length	1.480
WAP-180611	Total length	1.400
WAP-180305	Total length	1.330
CA-180906	Total length	1.270
CA-170813	Total length	1.525
NC-190626	Total length	1.480

Image data

Each image must be documented in the same format as the Mns_images object (preview below). The first column Image provides a unique identifier for the image and will be used to create an altitude variable, which will be estimated from the altitude sensor readings provided by AltitudeBarometer and AltitudeLaser in conjunction with training data. The remaining columns in Mns_images report the focal length (mm), image width (pixels), and camera sensor width (mm) associated with the image, which will be used to estimate the image’s ground sampling distance (GSD) per pixel.

Image	AltitudeBarometer	AltitudeLaser	FocalLength	ImageWidth	SensorWidth
190303_A_F5_DSC07951.JPG	17.45	16.72	35	6000	23.5
190305_A_F2_DSC08581.JPG	25.46	23.75	35	6000	23.5
190303_A_F1_DSC07542.JPG	24.08	23.91	35	6000	23.5
190224_L_F2_DSC04640.JPG	27.15	24.37	35	6000	23.5
190303_A_F4_DSC07613.JPG	25.13	24.79	35	6000	23.5

Pixel count “measurement” data

All pixel measurements must also be documented in the same format as the Mns_pixels object (preview below). The first two columns specify the measurement. One measurement variable, which will be estimated, will be associated with each unique combination of the first two columns. The Image column links the measurement to an image and it’s estimated GSD. Lastly, the PixelCount column records the pixel-length of the object as it appears in the image.

	Subject	Measurement	Image	PixelCount	EmpiricalLength	EmpiricalBarometerLength	EmpiricalLaserLength
3	Mn190303_A_F1-01	Total length	190303_A_F1_DSC07542.JPG	4434.894	11.866191	11.950560	11.866191
4	Mn190224_L_F2-04-mom	Total length	190224_L_F2_DSC04640.JPG	4800.000	13.090171	14.583429	13.090171
5	Mn190303_A_F4-09-mom1	Total length	190303_A_F4_DSC07613.JPG	4253.617	11.800040	11.961880	11.800040
6	Mn170204_A_F3_06-calf	Total length	170204_A_F3_DSC00964.JPG	3750.638	7.286240	9.119552	7.286240
7	Mn190226_L_F1-01-mom	Total length	190226_L_F1_DSC05462.JPG	4549.787	13.339543	13.135886	13.339543
8	Mn190224_L_F2-05-calf	Total length	190224_L_F2_DSC04569.JPG	2765.106	8.243177	8.540229	8.243177

Many-to-Many relationships

Storing Image and Pixel count data in separate structures allows multiple measurements to be estimated from a single image. For example, total length and maximum width can be measured from the same image through a pixel count table like the following:

Subject	Measurement	Image	PixelCount
Animal A	Total length	Image 1	1000
Animal A	Max. width	Image 1	100

Both PixelCount entries above relate to a different object being measured, but use the same estimated altitude and implied GSD for Image 1 when estimating lengths from pixel counts.

Similarly, the Image and Pixel count structures also allow one object to be estimated from multiple images. For example, total length can be estimated from multiple observations through a pixel count table like the following:

Subject	Measurement	Image	PixelCount
Animal A	Total length	Image 1	1000.0000
Animal A	Total length	Image 2	987.0678
Animal A	Total length	Image 3	988.1203
Animal A	Total length	Image 4	976.3668
Animal A	Total length	Image 5	1011.2227

Materials

Data:

APE-Dataset.csv - training/calibration data for different UAS platforms.

• Images = image used for measuring calibration object
• Aircraft = the UAS aircraft used to collect imagery of calibration object to measure
• Flight = the flight number/name
• Position = indicates if calibration object is in center of corner of image frame
• Focal.length = focal length of camera
• Pix.Dim = pixel dimensions (mm/px), which is the sensor width (mm) / image width (px) of the camera
• Baro_raw = the raw relative altitude recorded by the barometer
• Launch.Ht = the launch height of the drone, to be added to the BarAlt to get the absolute barometric altitude above the surface of the water
• Baro + Ht = the baro_raw + Launch.Ht to get the absolute barometer altitude
• Laser_Alt = the altitude recorded by the laser altimeter. Blanks spaces/NAs indicate no/false reading
• Alitude = altitude used in measurement, either Laser_Alt or Baro + Ht
• Alimeter = which altimeter was used for altitude in measurement; either barometer or laser
• Measurer = which analyst measured the calibration object (3 analysts total, measured each image once)
• RRR.pix = the length in pixels of the known sized object (calibration object)

calibration_object-measurements.csv - training/calibration data for the LemHex-44 and FreeFly Alta 6 to add to both Ecological Scenarios

• CO.ID = calibration object ID
• CO.Length = the true length of the CO.ID
• Image = image used for measuring calibration object
• Lab = the lab that collected the data
• Cruise = research expedicition ID
• Date = date that imagery was collected of calbiration object
• Flight = the flight number/name
• Pilot = pilot during data collection
• VO = visual observer
• Aircraft = the UAS aircraft used to collect imagery of calibration object to measure
• Focal_length = focal length of camera
• Iw = image width in pixels
• Sw = sensor width in mm
• pix.dim = pixel dimensions; Sw/Iw
• Pix.Dim = pixel dimensions (mm/px), which is the sensor width (mm) / image width (px) of the camera
• Baro_raw = the raw relative altitude recorded by the barometer
• Launch.Ht = the launch height of the drone, to be added to the BarAlt to get the absolute barometric altitude above the surface of the water
• Baro+Ht = the baro_raw + Launch.Ht to get the absolute barometer altitude
• Laser_Alt = the altitude recorded by the laser altimeter. Blanks spaces/NAs indicate no/false reading
• Alitude = altitude used in measurement, either Laser_Alt or Baro + Ht
• Alimeter = which altimeter was used for altitude in measurement; either barometer or laser
• Lpix = the length in pixels of the known sized object (calibration object)
• object_position = indicates if calibration object is in center of corner of image frame
• Analyst = analyst that performed the measurement

humpback_data.csv - testing data for Ecological Scenario 1, length-based maturity of humpback whales

• whale = numbered list of individuals
• Animal_ID = unique ID for individual whale
• Reproductive_Class = determined from biopsy sample or from drone images (mom and calf pairs)
• Species = the species of whale
• Image = the image ID used for measuring the whale
• Aircraft = which UAS platform collected the imagery
• Focal_Length = focal length (mm) of the camera used
• LaserAlt = the altitude recorded by the laser altimeter. Blanks spaces/NAs indicate no/false reading
• BaroAlt = the raw relative altitude recorded by the barometer
• Pixel_Dimension = (mm/px) the Sensor width (mm) / Image width (px) of the camera
• Launch_Ht = the launch height of the drone, to be added to the BarAlt to get the absolute barometric altitude above the surface of the water
• Altitude = altitude used in measurement, either LaserAlt or BaroAlt
  • Launch_Ht
• Altimeter = which altimeter was used for altitude in measurement; either barometer or laser
• TL = total length of the whale in meters

marrs_amws.csv - testing data for Ecological Scenario 2, population-lelve morphological relationship between rostrum to blowhole distance and total body length

• AID = unique ID for individual whale
• Species = the species of whale
• Image = the image ID used for measuring the whale
• Region = location of data collection (WAP = Western Antarctic Peninsula)
• Year = year of data collection
• Aircraft = which UAS platform collected the imagery
• TL = total length of the whale in meters
• RB = rostrum to blowhole distance in meters
• BaroAlt = the raw relative altitude recorded by the barometer
• Launch_Ht = the launch height of the drone, to be added to the BarAlt to get the absolute barometric altitude above the surface of the water
• LaserAlt = the altitude recorded by the laser altimeter. Blanks spaces/NAs indicate no/false reading
• Altitude = altitude used in measurement, either LaserAlt or BaroAlt
  • Launch_Ht
• Focal_Length = focal length (mm) of the camera used
• Iw = image width in pixels
• Sw = sensor width in mm
• perDif = percent difference between the altitude recorded by the barometer and laser altimeter

Steps

run ‘make.R’

This will generate an “output” folder that contains an ‘mcmc’ folder and a ‘reports’ folder.

• The ‘mcmc’ folder contains all the .rds outputs from the model (note that “fit_mns” refers to humpbacks in Ecological Scenario 1, while “fit_marrs” refers to Antarctic minke whales in Ecological Scenario 2), and a ‘diagnostics’ folder with .html files providing diagnostic comparisons between the different model outputs (e.g., barometer only, barometer and laser, uninformative priors, etc.).

• The ‘reports’ folder contains .html files to evaluate the results from the model

  • Sc1_output_figures explores outputs from Ecological Scenario 1.

  • fit_marrs refers to results from Scenario 2

  • Uncorrected_error_figures explores the APE dataset (training data) before applying the uncertainty model.

• Figures 3-6 and Supplementary FigS1 and FigS2 are automatically saved in the ‘figures’ folder of the main directory.

Contact

KC Bierlich, kevin.bierlich@oregonstate.edu
https://github.com/KCBierlich/Uncertainty_Model