Lunar Reconnaissance Orbiter Data In Support Of Characterizing Future Landing Sites

Author: 
Noah Petro
Abstract Title: 
Lunar Reconnaissance Orbiter Data In Support Of Characterizing Future Landing Sites
Recording: 
Presentation PDF: 
Abstract Type: 
Oral
Abstract Body: 
Introduction: Launched in 2009, the Lunar Reconnaissance Orbiter (LRO) has collected more data than any prior NASA planetary science mission to date [1]. In its first year of operations LRO focused on characterizing the Moon and its environment in preparation for future exploration. It was during this first year that targeting of the NASA Constellation Program’s Regions of Interest [2] was conducted in earnest, demonstrating a systematic approach to characterizing geologically diverse sites and enabling LRO to support a variety of landed mission objectives. Now with seven additional years beyond the Exploration phase of LRO, we have continued to characterize the lunar surface and environment in exquisite detail, with all measurements made by LRO supporting not only cutting-edge science, but also with an eye towards future exploration. Here we detail a portion of the data products developed by the LRO science teams that may support future exploration. LRO Support for Future Lunar Missions: LRO data is critical for future surface missions and several outstanding science questions derived from LRO observations could be addressed by future missions. Several derived data products are available that can support future surface exploration. These tools enable safe exploration of the lunar surface [3-5], and with continued operations LRO can continue to collect targeted observations of potential landing sites, a resource unavailable from any other existing asset. Here we describe a few of the resources available for landing site characterization. While we recognize that each site or mission may have its own set of needs, there are likely a core set of data that is required to validate any given location on the lunar surface. High-resolution imaging: The LRO Camera Narrow Angle Camera (NAC) can image the lunar surface at a resolution commensurate with the altitude of the spacecraft (e.g., 50 cm/pixel from an altitude of 50 km) [6]. Based on the local lunar time of day an image is acquired one may be able to identify small (~1.5 m diameter) craters or boulders at the scale of resolution. While a significant portion of the lunar surface is already imaged, there may not be images at low sun angles, useful for identifying such hazards. From these high resolution images, other derived products are produced: 1) Digital Terrain Model’s, high resolution topographicmaps of areas of interest. These maps require multiple images acquired, typically on successive orbits, with optimal lighting conditions [4]. The illumination requirement places limits on when such images of any particular location can have such data collected. 2) Featured mosaics: When multiple adjacent images are acquired, a mosaic of NAC Left and Right images can be generated, producing a seamless image of a larger region [7]. Diviner Rock Abundance: A critical question in assessing a landing site is the number of rocks/blocks at the surface. While the rock abundance at any particular location on the lunar surface can be verified by visually identifying rocks [8], a derived data product from the Diviner instrument provides a unique dataset for quickly identifying relatively-block free regions [9]. This product provides a quick method for assessing regions which may be more, or less, suitable for landing sites. LRO will continue to deliver data to the PDS at a three-month cadence. Currently over 800 Tb of data has been delivered to the PDS, the largest data volume of any NASA Planetary Science Division mission. A number of higher-level data products are in the PDS archive, including mosaics, topographic products, and derived products (e.g., rock abundance from Diviner, local slope). These products are available on the LRO PDS archive (http://pds-geosciences.wustl.edu/missions/lro/) and on individual instrument team websites.
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Co-Authors: 
John Keller