Bibliographic Details
| Title: |
Mountain Degradation Mechanisms on Io Based on Geologic Mapping of the Cocytus Montes Region From JunoCam Imagery. |
| Authors: |
Seeger, C. H.1 (AUTHOR) cseeger@rice.edu, de Kleer, K.1 (AUTHOR), Williams, D. A.2 (AUTHOR), Perry, J. E.3 (AUTHOR), Davies, A. G.4 (AUTHOR), Nelson, D. M.2 (AUTHOR) |
| Source: |
Journal of Geophysical Research. Planets. Jan2026, Vol. 131 Issue 1, p1-24. 24p. |
| Subject Terms: |
*Erosion, *Volcanology, Geological mapping |
| Abstract: |
Periodic high‐resolution imagery of Io is essential for understanding its surface evolution, from volcanic eruptions to tectonic deformation to large‐scale mass wasting. Juno flybys in 2023 and 2024 obtained imagery of the surface with the JunoCam imager at 1.8 km/pixel spatial resolution, comparable to global observations from the Galileo spacecraft (1996–2001). Areas of Io's north pole were imaged for the first time, with low emission (46°–61°), high incidence angle conditions revealing several‐kilometers‐tall mountains. We are unable to identify detailed changes in Io's mountain features due to the limited overlap in the high‐resolution coverage between the Galileo and Juno data sets. However, the improved lighting conditions in the JunoCam imagery allow us to refine our understanding of previously mapped features, including an extension of the rifting relationships previously proposed at Shamshu Patera. Cocytus Montes, a newly identified trio of mountains centered at 60°N 330°W, exhibit intermediate erosional stages with morphologies grading from sharp ridges to eroded hummocks along their slopes, providing a new perspective on the pace and processes of erosion on Io. We present a regional geologic map of this region, and examine the relationships between mountain units and the underlying layered plains which connect them on a raised plateau. Unique crustal blocks strewn across the plateau have sparse analogs elsewhere on Io, and prompt questions about the erosional mechanisms that may have emplaced them. We propose several formation mechanisms and conclude that while we cannot definitively determine which is responsible, regolith creep‐modified cliff collapse is the most likely. Plain Language Summary: Jupiter's innermost large moon Io is the most volcanically active body in the Solar System, with a surface that is continually modified by eruptions (lava flows and gas‐ and dust‐rich plumes) and tectonism (fault motion and erosion via events like landslides). The Juno spacecraft made close approaches to Io in 2023 and 2024, obtaining images of the surface at high resolution and low sun angle—conditions that produce the long shadows necessary to see Io's topography. Though the new images do not overlap with the high‐resolution images obtained 20 years prior by the camera on the Galileo spacecraft, they do capture parts of the north polar region in detail for the first time. We closely examined the northern region to create a geologic map highlighting the different volcanic, mountain, and plains units visible. We present several possible formation mechanisms for a newly defined geologic unit (blocks made of kilometer‐scale chunks of crustal material), favoring a cliff‐collapse mechanism. We also identify several localities where sharper, less eroded mountain types gradually transition into slumped and eroded mountain types, capturing intermediate stages of erosion not typically visible on Io, with implications for the overall pace and process of erosion on a very active surface. Key Points: JunoCam images reveal Io's north polar region in unprecedented detail with favorable lighting conditions to interpret topographyA regional geologic map highlights a new geologic unit (defined as blocks), which may have several possible formation mechanismsRelationships between mountain and plains units capture intermediate erosional stages and complex surface evolution [ABSTRACT FROM AUTHOR] |
|
Copyright of Journal of Geophysical Research. Planets is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
GreenFILE |