A Multi-Annotator Survey of Sub-km Craters on Mars

Alistair Francis,Reuben Crawford Clarke,Meg Savage,Viran Patel,Alice Whelan,Panagiotis Sidiropoulos,Arianne Puttock,Thomas Cameron,Jasmine Nowakowska,Romilly Dodd,Jan-Peter Muller,Jonathan Brown,Oliver Redmond,Matthew Neave,Jennifer Hurdle,Aaron Ruban,Wiggert Vermeer,Damien Ruban

doi:10.3390/data5030070

Alistair Francis, Reuben Crawford Clarke + Show 16 more

Open Access

https://doi.org/10.3390/data5030070

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Journal: Data	Publication Date: Aug 3, 2020
Citations: 7	License type: CC BY 4.0

Affiliation: Richard Carter and Associates (United Kingdom)

Abstract

We present here a dataset of nearly 5000 small craters across roughly 1700 km2 of the Martian surface, in the MC-11 East quadrangle. The dataset covers twelve 2000-by-2000 pixel Context Camera images, each of which is comprehensively labelled by six annotators, whose results are combined using agglomerative clustering. Crater size-frequency distributions are centrally important to the estimation of planetary surface ages, in lieu of in-situ sampling. Older surfaces are exposed to meteoritic impactors for longer and, thus, are more densely cratered. However, whilst populations of larger craters are well understood, the processes governing the production and erosion of small (sub-km) craters are more poorly constrained. We argue that, by surveying larger numbers of small craters, the planetary science community can reduce some of the current uncertainties regarding their production and erosion rates. To this end, many have sought to use state-of-the-art object detection techniques utilising Deep Learning, which—although powerful—require very large amounts of labelled training data to perform optimally. This survey gives researchers a large dataset to analyse small crater statistics over MC-11 East, and allows them to better train and validate their crater detection algorithms. The collection of these data also demonstrates a multi-annotator method for the labelling of many small objects, which produces an estimated confidence score for each annotation and annotator.

Highlights

A Multi-Annotator Survey of Sub-km Craters on MarsAlistair Francis 1,2, * , Jonathan Brown 2,† , Thomas Cameron 2,† , Reuben Crawford Clarke 2,† , Romilly Dodd 2,† , Jennifer Hurdle 2,† , Matthew Neave 2,† , Jasmine Nowakowska 2,† , Viran Patel 2,† , Arianne Puttock 2,† , Oliver Redmond 2,† , Aaron Ruban 2,† , Damien Ruban 2,† , Meg Savage 2,† , Wiggert Vermeer 2,† , Alice Whelan 2,† , Panagiotis Sidiropoulos 1,3 and and Jan-Peter Muller 1
Craters are formed by the impact of meteorites on a planet’s surface
The score cannot factor in craters that were not found by any other annotators, it does describe the consistency of detection within the group of annotators, and it tells us about the positional accuracy of markings

Summary

A Multi-Annotator Survey of Sub-km Craters on Mars

Alistair Francis 1,2, * , Jonathan Brown 2,† , Thomas Cameron 2,† , Reuben Crawford Clarke 2,† , Romilly Dodd 2,† , Jennifer Hurdle 2,† , Matthew Neave 2,† , Jasmine Nowakowska 2,† , Viran Patel 2,† , Arianne Puttock 2,† , Oliver Redmond 2,† , Aaron Ruban 2,† , Damien Ruban 2,† , Meg Savage 2,† , Wiggert Vermeer 2,† , Alice Whelan 2,† , Panagiotis Sidiropoulos 1,3 and and Jan-Peter Muller 1.

Introduction

Data Description

Collection

Validation

Discussion

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