Figure 7. Comparison of MBARS results (circles) to manual measurements (solid lines) in subsets of PSP_007718_2350, with a 50-m wide portion of Test Area 3 shown on the right. Three images (10, 20, and 30) counted manually in prior work, and area A was manually counted as part of this work. Both sets of manual analyses had the greatest match with the same MBARS boundary parameter (Table S1). Inset of Area 3 is also included with MBARS-identified boulders (green outlines) over the image. As the inset shows, several bright objects lack apparent shadows in this image. Those may be mostly-buried boulders that do not fully protrude from the subsurface, or simply boulders that deviate significantly from the expected shape. Either scenario likely caused the discrepancy between the methods, as the manual methods would have counted these as boulders while they are functionally invisible to MBARS.
Both the prior manual measurements and our manual measurements produce boulder size-distributions that fit well to expected CFA curves (Table S1), suggesting that there are not systematic issues with the prior manual analyses. In all cases, MBARS underestimates the abundance of smaller boulders (<2 m) and overestimates the population of larger boulders, especially in Area 1. This overestimate of larger boulders appears to be a systematic issue (Section 4.4), but it is particularly pronounced in this image. Significantly, when using either the prior manual measurements, or our new manual measurements, the best-fit boundary parameter of MBARS is the same (Table S1). The change in manual measurement strategy did not significantly impact the choice of MBARS boundary parameter, suggesting that using existing manual measurements to calibrate MBARS is as effective as generating new manual measurements.
In these images, the tendency of MBARS to over-predict the CFA of larger boulders is particularly pronounced. In the three priorly-measured areas, bright spots that lack shadows are abundant and visible in the image subset shown (Fig. 7). In the prior manual analysis (Sholes et al., 2017), bright spots were counted by users as boulders, but the cast shadows are often either small or missing entirely. Boulders that lack shadows or have small shadows would interfere with the measuring methodology of MBARS. The solar incidence angle in the image is 48° from zenith, so 1 m boulders may be undetectable due to short shadows (Section 2.1). However, several ~2m wide bright spots are visible that lack significant shadows (Fig 7), and a boulder of that size and with an h/D ~0.5 (Sec. 2.3) would be expected cast a shadow at this incidence angle. In this image there are then two factors challenging MBARS: A low incidence angle, and an abundance of short, wide boulders. Despite these challenges, MBARS can recreate RA values within ~10-20% of the manually estimated values (Table S1) and calibration to manual analyses provides in situquantification of these biases and uncertainties.

4.3. Comparison to Previous Algorithms

As a third comparison, we compare MBARS to both the G-H method and N-M methods of boulder detection (Golombek et al., 2008; Nagle-McNaughton et al., 2020). The three subsets of TRA_000828_2495 (A,B,C) isolated in previous work (Fig. 17 in Golombek et al., 2008) were manually measured as an independent evaluation and used as the test areas for calibration purposes.
4.3.1. Comparison to G-H Method
Similar to MBARS, the G-H method detects boulders based on their shadows and uses these shadows to determine boulder morphology. Fig. 8 shows results for the test image from MBARS, the G-H method, the N-M method, and two sets of manual analyses within test areas A and B (Fig. 9). These same results are shown for a portion of Test Area B in Fig. 4. A third area (Area C) was previously analyzed (Golombek et al., 2008), though both our manual and automated analyses of area C found fewer than 5 boulders above 1.5 m in diameter, making the comparison of statistics in this area unreliable.