Review of methodological considerations and recommendations for mapping remote glaciers from aerial photography surveys in suboptimal conditions

Medrzycka, Dorota; Copland, Luke; Thomson, Laura; Kochtitzky, William; Smeda, Braden

doi:https://doi.org/10.5194/gi-2024-10

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https://doi.org/10.5194/gi-2024-10

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21 Oct 2024

| 21 Oct 2024

Status: this preprint is currently under review for the journal GI.

Review of methodological considerations and recommendations for mapping remote glaciers from aerial photography surveys in suboptimal conditions

Dorota Medrzycka, Luke Copland, Laura Thomson, William Kochtitzky, and Braden Smeda

Abstract. Structure from motion (SfM) photogrammetry coupled with multiview stereo (MVS) techniques are widely used for generating topographic data for monitoring change in surface elevation. However, study sites on remote glaciers and ice caps often offer suboptimal conditions, including large survey areas, complex topography, changing weather and light conditions, poor contrast over ice and snow, and reduced satellite positioning performance. Here, we provide a review of methodological considerations for conducting aerial photography surveys under challenging field conditions. We generate topographic reconstructions, outlining the entire workflow, from data acquisition to SfM-MVS processing, using case studies focused around two small glaciers in Arctic Canada. We provide recommendations for the selection of photographic and positioning hardware and guidelines for flexible survey design using direct measurements of camera positions, thereby removing the need for ground control points. The focus is on maximising hardware performance despite inherent limitations, with the aim of optimising the quality and quantity of the source data, including image information and control measurements, despite suboptimal conditions.

Received: 20 Sep 2024 – Discussion started: 21 Oct 2024

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.

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Dorota Medrzycka, Luke Copland, Laura Thomson, William Kochtitzky, and Braden Smeda

Status: final response (author comments only)

RC1: 'Comment on gi-2024-10', Anonymous Referee #1, 11 Nov 2024

The paper presents many important aspects in order to achieve optimal results

in photogrammetric surveys from the planning stage to the final results. These

aspects are mostly reviewed from a theoretical point view. The paper ends

with two practical examples presenting the work and outcome for two flights

at high latitude (~ 80° North).
The paper is a bit of a mixed bag. The first part (approx. 11 pages) summarizes

many aspects of modern day photogrammetry, including MTF, diffraction, motion blur,

rolling shutter, GNSS specifics, etc.
Actually, everything is true for any photogrammetric endeavor -- irrespective of the

terrain type (glacier or not).
The 2nd part (also 11 pages) presents the work and outcome for two flights

at high latitude (~ 80° North).
Following the very detailed description in the first part, one might expect that the practical

part then showcases how the theory of the first part is considered in the planning stage

of the two flights, and/or that it is demonstrated that neglecting certain aspects from the theory section produces

certain errors in the results. But that's not the case. Both flights appear to be executed without

having had many options.
E.g. what could have been investigated:

- different apertures

- effect of flight speed on blur

- shooting not in raw; or bad Adobe Lightroom settings when "developing" the raw images

- impact of these settings on the different surface types: glacier (which is also part of the title) and non-glacier

- impact of changing the oblique viewing angle

- different flight patterns

- etc.
Of course, the possibilities of changing the parameters and investigations are almost endless, but in the present form

the photogrammetric results are obtained in <<one>> way. Apparently, the outcome fulfilled the requirements,

but it remains a bit unclear if less strict settings would have let to similar acceptable results.
Still, the paper is very well and understandable written. The theoretical part gives a great theoretical summary

on many aspects. And the description of the two flights shows the reality of conducting

photogrammetric data acquisitions in such high altitude.

In order to accept the paper I would ask the authors to provide a few more details in the theoretical and practical parts:
row 78

"Along with focal length, sensor size also defines the ground sampling distance (GSD) and therefore"

-->

This is not correct, equ (1) for the GSD has no sensor size, just the pixel size (pixel pitch).
Table 1

"cy per in" should be "cy per mm". How is the Nyquist limit calculated?
Fig. 1+2+3

The paper should include the formulae that went into creating these figures.
row 148

"the diffraction limit decreases with smaller apertures"

-->

"the diffraction limit decreases with smaller apertures (f-numbers)"
row 149

"1/lambad N" should be "1/(lambad*N)".
row 175-180

"more visible as the size of the Airy pattern"

"the distance between the centers of two disks is equal to their radius"

"when the circle of confusion reaches a size of twice the pixel pitch"

--> I would welcome that every time it is clearly specified if you mean diameter or radius (like in the 2nd quote).
Equation 2

"GSD", which is not the resolution of the image, is a well defined term (your equation 1).

Thus I object against introducing the term "diffraction limited GSD" in equation 2,

because any later mentioning of GSD creates confusion whether you mean really "GSD" or use it as a short for "diffraction limited GSD".

And, indeed, in the caption of Fig. 3 you write "Diffraction limited ground sampling distance (GSD)" which is ambiguous in the

way that there GSD might refer only to "ground sampling distance" or the whole term "diffraction limited ground sampling distance".

In the end of that caption you also mention another term: "theoretical GSD".

Furthermore, later, you refer to equ.2 as circle of confusion (which I think is better).

Any term that really refers to the resolution (instead of the sampling = GSD) should by clearly discernable. Some authors

use the term "GRD" (ground resolved resolution). Although, that term itself leaves open what effects are considered (just

diffraction, or even the full point spread function), it still means obviously something else than GSD.

row 202

"Wide angle lenses exhibit negative (barrel) distortions which present as decreasing

image magnification from the center of the frame towards the edges, while positive (pincushion)

distortions are characteristic of telephoto lenses (70 mm or above)."

--> This is opposite to my experience which is:

1. That the sign of the radial distortion is not predictable from the angle of the camera.

2. The longer the focal length the more the lens shows no distortion at all.

Admitted, this is my personal experience, but currently, the quote is without reference. So, please,

either provide a reference, or rephrase.
(On row 197 you write "the downside being that short focal lengths are more prone to distortions", if this

is inverted to "longer focal lengths are likely to have less distortion", it fits to my experience.)

Fig 2.

I am not sure, if (a) and (b) are derived from the very same RAW image, or only (a); and (b) is a

direct JPG from the camera (and thus in principle a different photograph than the RAW for (a))?
row 250

"Including the affinity and non-orthogonality coefficients

in the camera calibration matrix at the image alignment stage should partially compensate for this effect."

-->

This works only (or the more) the flight speed is constant and the terrain is flat. You may wish to add/clarify that.
Remark 1:

(Again from my experience) affine parameters need to be introduced per image (and not per camera).

Remark 2:

The developers of Pix4D have a paper about their method on rolling shutter compensation, which is better than the affinity in

image space as it directly works on the change of the exterior orientation parameters per image:

https://s3.amazonaws.com/mics.pix4d.com/KB/documents/isprs_rolling_shutter_paper_final_2016.pdf
row 254

"including" --> "included" (?)

row 266

"0.43" --> "4.3"
row 280

"The direct georeferencing method ... similar precision to the ground-based approach where

camera position information is acquired with multi-frequency survey-grade GNSS equipment"

-->

Does this last part ("where camera position ...") refer to the ground-based approach?
Remark:

A photogrammetric survey that fully relies on direct georeferencing using GNSS, and thus

without a single GCP, is prone to deliver results with a large height bias. Because if the camera

calibration is considered unknown and thus is estimated during the bundle block adjustment, then any small

bias in the estimated focal length causes a large height offset. This is especially true for vertical

images, and may be mitigated using oblique images.

General comment to the theory (section 2):

Interestingly, the problem of depth of field is completely neglected.

Although, its importance increases with smaller viewing (focus) distance, it belongs into this theory part.

Actually, you refer to defocus in row 591.

Especially, the hyperfocal distance would be an interesting feature maybe not known to everybody of the target audience.

page 14/15

I am a bit confused regarding your "off-nadir" images. On row 365 you say "">5°" and on row 372 "30-50°".

Why use these rather different definition thresholds, and not just provide some information on the off-nadir

angles your two sites used; e.g. 5th and 95th percentile, and add that info to table 2.
Additionally, it is not clear in which direction the off-nadir angle is applied; as pitch or as roll, or something between?

Here it would be super helpful to include the viewing direction in Fig. 5 for every 50th image or so.
In table 2 further some info on the GSD would be interesting to get some idea. I know with oblique angles

and variable terrain there is no straight forward way to come up with a representative value, but currently

there is no mentioning at all.

row 392

You took pictures through the front passenger window. It would be interesting to know how the camera calibration

was effected by that (in comparison to the other data set).
row 413

"PPP" is mentioned here the first time, please, add a reference.
row 443

Here and elsewhere you mention an aperture of "f/5". Although, such value is possible in principle, it would be very

unusual, because the usual f-stop numbers are the powers of sqrt(2), the closest being thus 4 and 5.6, which you also

have in Fig. 2+3.
row 456

"at or below the size of the circle resulting from diffraction"

-->

you mean "diameter"? Also add a reference to the equation in the theoretical part.
row 478

"Lastly, a variable exposure gain was automatically applied to all

images to brighten underexposed areas and match total exposure of successive images."

-->

Can your provide a bit more information on how this exposure gain is controlled?
row 486

"the most time-intensive task in post-production is masking extensive swaths of sky and any terrain beyond the area of interest."

-->

What would have happened if you would not have done this masking? Would the bundle block adjustment have completely failed for

all images, or just for the affected images? Or would the adjustment have worked, but the subsequent dense point cloud extraction

would have failed (if so, why not simply define a bounding box prior to deriving the dense point cloud)?
General comment on the bundle block adjustment in Metashape:

- What accuracies were assumed for the GNSS image positions?

- What GNSS residuals were obtained after the adjustment?

- What reprojection error was obtained?
row 575

"Ideally, horizontal accuracy should be higher or equivalent to the spatial resolution of the final gridded products.

Here, both DEMs and orthomosaics were gridded at 0.5 m resolution and horizontal checkpoint misalignment errors remain

below that level for both reconstructions."

-->

I never heard of this rule and, actually, do not subscribe to it. The gridding of the results (DEM from dense image

matching and orthomosaic) should fit to

the image resolution, i.e. the finest details in the image should also be included in these results, independently of the spatial

accuracy of the georeferencing. Even if accuracy and grid width do not match, as in your case, the results provide valuable

information about these fine details, however, you only are able to derive the location with a certain limited accuracy. For

that reason, the accuracy always should be communicated together with the results. Furthermore, the error in the georeferencing

is usually a global one, meaning that your result could be improved simply by shifting in 3D to obtain a much better georeferencing.

The latter can be done even on the results themselves; e.g. in case of time series where one epoch (with the best georeferencing

quality) serves as reference (and enough corresponding stable areas are present, of course).

Thus it would be a waste of potential to set the gridding of the result to the obtained georeferencing accuracy.

Last not least, photogrammetry works even without GCPs and GNSS (one only needs a known distance for scaling). In this case

no meaningful (absolute) georeferencing accuracy can be obtained, but the resolution of the images still serves as a guide.
As you outlined in the theory the actual resolution of the images is not easily determinable, because it depends on so many

factors. However, the GSD is well defined and easily obtainable (at least in case of nadir images over "flat" terrain). So the

usual way in photogrammetry is to adopt the GSD as gridding value for the DEM and the orthophoto.

In your case I am not sure what the GSD is, but from the given point density values of around 15 pts/m², we see that the average

distance between these points is 1/sqrt(15) = 26 cm. Thus you could at least create your DEM and the orthomosaic with 25 cm grid width

and should thus be able to get a bit more out of your results than compared to the chosen 50 cm (provided the images were not dramatically

effected by blur).
I could imagine, that the orthomosaic could be created with an even smaller pixel size, because with dense image matching only in

optimal cases one really gets a 3D point per image pixel. Furthermore, in your case, you will have a high variability of the GSD, and

in order to get the details even in the images with the smallest GSD, one thus could base the orthomosaic pixelsize not on the average

GSD but some smaller statistical value, like the 10th percentile.

row 665

"Due to data gaps, 28 cameras from the 10 Hz EF survey were disabled (∼5 %), compared to 129 cameras (or

13 %) from the 15 s TF survey."

-->

Here you use the wrong terminology from Metashape. You mean 28 and 129 "images" not "cameras".

Actually, here do you mean that the entire images were disabled, or that the GNSS locations were disabled (due

to big interpolation error)?

(Actually, Metashape should be able to link images without GNSS location information to their neighboring

images (with GNSS location), provided the image content allows for enough feature points.)

It would be interesting to list the numbers of images regarding: originally taken vs. disabled images (classified for

whatever reasons (e.g. blur)).

Finally, a general comment:

If you cite a book of several hundreds of pages, then please include the page number in the quotes; e.g. Rowlands, 2017.

Citation: https://doi.org/10.5194/gi-2024-10-RC1
RC2: 'Comment on gi-2024-10', Anonymous Referee #2, 02 Dec 2024

In this paper, the authors have provided a thorough overview of the technological and survey design considerations that impact the usability and accuracy of photogrammetric surveys and derived products. The authors then compare these considerations to the results of two prior surveys made on remote glaciers in Arctic Canada. I found the first "half" of the paper to be very well put-together and easy to read, which is no small feat for such a technical subject!
Because the surveys were (presumably) made before the start of the PhD that this work comes out of, it feels as though there is a slight disconnect between the review of the first half and the discussion in the second half - there isn't much indication that the lessons learned from the review informed the design of the field surveys, or that these lessons were "tested" by comparing the results of different approaches. This is entirely understandable, but I think that some additional critical reflection about how the surveys might have been improved would help to bridge this gap.
Obviously, additional surveys are not feasible, but "simulation" of different settings after the fact (using ETTR images by shifting the histogram, using JPG instead of RAW images, not correcting chromatic aberrations, etc.) might be possible and give some indication of what impact these different choices have on the final product. This would help to solidify the connection between some of your proposed recommendations and the final results, though I only suggest doing this if it is easy to do - if not, some additional comparison to literature that has reviewed the impact of these different design choices is more than enough.
Another consideration that I think could be better explored is the minimum feasible design. Obviously, a number of studies obtain usable results, even with less ideal camera setups (e.g., Welty et al., 2013; Girod et al., 2017), so at least some part of survey design depends on the needs or application. Given how rare the "ideal" situation is, some additional thought/reflection on what the "minimum" settings (or the non-negotiable choices) should be in order to achieve a useful output would be useful here.
Specific comments

---------------------------
line 16: add "e.g." to Mölg and Bolch reference
line 67: why are helicopters preferred here? Can you explain the motivation/reasoning why this would be so? I would think that this will depend on the particular study area (size, remoteness), the available camera setup, and perhaps the prevailing weather conditions, but it's not clear to me why helicopters would be preferred in all cases.
Table 1: can you provide, in either the caption or the text, an explanation of "high" and "low"?
line 153: do you mean "stepping" instead of "stopping" here?
line 165: perhaps "a combination" is a better word choice than "the product" to avoid confusion with the mathematical meaning of "product" - unless this is the meaning that is intended here.
line 206-7: I think this again depends on the needs of the study and equipment availability; it is possible to get usable results from "unsuitable" cameras.
Figure 4: it might be useful to indicate the outline of (a2, b2) in (a1, b1) .
line 359: insert space between "a.s.l." and "The"
line 530: remove stray "s"

References

----------------

Girod, L., Nuth, C., Kääb, A.M., Etzelmüller, B., Kohler, J., 2017. Terrain changes from images acquired on opportunistic flights by SfM photogrammetry. The Cryosphere 11, 827–840. https://doi.org/10.5194/tc-11-827-2017

Welty, E.Z., Bartholomaus, T.C., O’Neel, S., Pfeffer, W.T., 2013. Cameras as clocks. Journal of Glaciology 59, 275–286. https://doi.org/10.3189/2013JoG12J126

Citation: https://doi.org/10.5194/gi-2024-10-RC2

Dorota Medrzycka, Luke Copland, Laura Thomson, William Kochtitzky, and Braden Smeda

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Short summary

This work explores the use of aerial photography surveys for mapping glaciers, specifically in challenging environments. Using examples from two glaciers in Arctic Canada, we discuss the main factors which can affect data collection, and review methods for capturing and processing images to create accurate topographic maps. Key recommendations include choosing the right camera and positioning equipment, and adapting survey design to maximise data quality even under less-than-ideal conditions.


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