Human and Robotic Mission to Small Bodies: Mapping, Planning and Exploration

This study investigates the requirements, performs a gap analysis and makes a set of recommendations for mapping products and exploration tools required to support operations and scientific discovery for near- term and future NASA missions to small bodies. The mapping products and their requirements are based on the analysis of current mission scenarios (rendezvous, docking, and sample return) and recommendations made by the NEA Users Team (NUT) in the framework of human exploration. The mapping products that sat- isfy operational, scienti c, and public outreach goals include topography, images, albedo, gravity, mass, density, subsurface radar, mineralogical and thermal maps. The gap analysis points to a need for incremental generation of mapping products from low (flyby) to high-resolution data needed for anchoring and docking, real-time spatial data processing for hazard avoidance and astronaut or robot localization in low gravity, high dynamic environments, and motivates a standard for coordinate reference systems capable of describing irregular body shapes. Another aspect investigated in this study is the set of requirements and the gap analysis for exploration tools that support visualization and simulation of operational conditions including soil interactions, environment dynamics, and communications coverage. Building robust, usable data sets and visualisation/simulation tools is the best way for mission designers and simulators to make correct decisions for future missions. In the near term, it is the most useful way to begin building capabilities for small body exploration without needing to commit to specific mission architectures

Maximizing the value of Solar System data through Planetary Spatial Data Infrastructures

Planetary spatial data returned by spacecraft, including images and higher-order products such as mosaics, controlled basemaps, and digital elevation models (DEMs), are of critical importance to NASA, its commercial partners and other space agencies. Planetary spatial data are an essential component of basic scientific research and sustained planetary exploration and operations. The Planetary Data System (PDS) is performing the essential job of archiving and serving these data, mostly in raw or calibrated form, with less support for higher-order, more ready-to-use products. However, many planetary spatial data remain not readily accessible to and/or usable by the general science user because particular skills and tools are necessary to process and interpret them from the raw initial state. There is a critical need for planetary spatial data to be more accessible and usable to researchers and stakeholders. A Planetary Spatial Data Infrastructure (PSDI) is a collection of data, tools, standards, policies, and the people that use and engage with them. A PSDI comprises an overarching support system for planetary spatial data. PSDIs (1) establish effective plans for data acquisition; (2) create and make available higher-order products; and (3) consider long-term planning for correct data acquisition, processing and serving (including funding). We recommend that Planetary Spatial Data Infrastructures be created for all bodies and key regions in the Solar System. NASA, with guidance from the planetary science community, should follow established data format standards to build foundational and framework products and use those to build and apply PDSIs to all bodies. Establishment of PSDIs is critical in the coming decade for several locations under active or imminent exploration, and for all others for future planning and current scientific analysis.Comment: 8 pages, 0 figures. White paper submitted to the Planetary Science and Astrobiology Decadal Survey 2023-203

Surface processes recorded by rocks and soils on Meridiani Planum, Mars: Microscopic Imager observations during Opportunity's first three extended missions

The Microscopic Imager (MI) on the Mars Exploration Rover Opportunity has returned images of Mars with higher resolution than any previous camera system, allowing detailed petrographic and sedimentological studies of the rocks and soils at the Meridiani Planum landing site. Designed to simulate a geologist's hand lens, the MI is mounted on Opportunity's instrument arm and can resolve objects 0.1 mm across or larger. This paper provides an overview of MI operations, data calibration, and analysis of MI data returned during the first 900 sols (Mars days) of the Opportunity landed mission. Analyses of Opportunity MI data have helped to resolve major questions about the origin of observed textures and features. These studies support eolian sediment transport, rather than impact surge processes, as the dominant depositional mechanism for Burns formation strata. MI stereo observations of a rock outcrop near the rim of Erebus Crater support the previous interpretation of similar sedimentary structures in Eagle Crater as being formed by surficial flow of liquid water. Well-sorted spherules dominate ripple surfaces on the Meridiani plains, and the size of spherules between ripples decreases by about 1 mm from north to south along Opportunity's traverse between Endurance and Erebus craters

USGS High-Resolution Topomapping of Mars with Mars Orbiter Camera Narrow-Aangle Images

KEY WORDS: Mars, topographic mapping, photogrammetry, photoclinometry, softcopy, extraterrestrial mapping We describe our initial experiences producing controlled digital elevation models (DEMs) of Mars with horizontal resolutions of ≤10 m and vertical precisions of ≤2 m. Such models are of intense interest at all phases of Mars exploration and scientific investigation, from the selection of safe landing sites to the quantitative analysis of the morphologic record of surface processes. Topomapping with a resolution adequate to address many of these issues has only become possible with the success of the Mars Global Surveyor (MGS) mission. The Mars Orbiter Laser Altimeter (MOLA) on MGS mapped the planet globally with absolute accuracies <10 m vertically and ~100 m horizontally but relatively sparse sampling (300 m along track, with gaps of>1 km between tracks common at low latitudes). We rely on the MOLA data as the best available source of control and process images from the narrow-angle Mars Orbiter Camera (MOC-NA) with stereo and photoclinometric (shape-from-shading) techniques to produce DEMs with significantly better horizontal resolution. The techniques described here enable mapping not only with MOC but also with the high-resolution cameras (Mars Express HRSC, Mars Reconnaissance Orbiter HiRISE) that will orbit Mars in the next several years. 1

Framework for the development of a Europa planetary spatial data infrastructure

Spatial data infrastructure (SDI) is the framework composed of spatial data users, data interoperability agreements, policies and standards, data access mechanisms, and the spatial data themselves. Spatially enabled planetary science data are any data with a spatial component such as remotely sensed orbital data or geotagged sample data (e.g., Apollo samples). As described previously, the goal of SDIs is to make spatial data discoverable, accessible, interoperable, and usable by non-spatial data experts. We note that the term is used to describe both the framework of ideas that support spatial data usage and as an umbrella term for the implemented systems. Herein, we describe the use of the SDIframework, coupled with an implementation strategy to developer a Europa centric SDI-implementation. SDI-frameworks are an area of active research within the terrestrially focused geography and Earth science communities given the large volumes and rapid data collection velocities of spatial data. Likewise, academic, government, and non-government organizations research and implement SDIs to fulfill the spatial data utilization goals previously enumerated. It is from these bodies of work that the planetary science community can develop a Europa or Jovian focused SDI implementation. Considerable sections of this work have been drawn from the recently published article Framework for the Development of Planetary Spatial Data Infrastructures: A Europa Case Study. We are intentionally omitting the theoretical foundations from which the proposed Europa SDI is derived and suggest the aforementioned article to the interested reader

Towards a Planetary Spatial Data Infrastructure

Planetary science is the study of planets, moons, irregular bodies such as asteroids and the processes that create and modify them. Like terrestrial sciences, planetary science research is heavily dependent on collecting, processing and archiving large quantities of spatial data to support a range of activities. To address the complexity of storing, discovering, accessing, and utilizing spatial data, the terrestrial research community has developed conceptual Spatial Data Infrastructure (SDI) models and cyberinfrastructures. The needs that these systems seek to address for terrestrial spatial data users are similar to the needs of the planetary science community: spatial data should just work for the non-spatial expert. Here we discuss a path towards a Planetary Spatial Data Infrastructure (PSDI) solution that fulfills this primary need. We first explore the linkage between SDI models and cyberinfrastructures, then describe the gaps in current PSDI concepts, and discuss the overlap between terrestrial SDIs and a new, conceptual PSDI that best serves the needs of the planetary science community

A roadmap for planetary spatial data infrastructure

A major component of many planetary missions is to return planetary spatial data, which are any data with a spatial component. Such data include orbital, remotely sensed data; rover-collected, navigation imagery; and collected samples with a spatial component. These data are used to make higher-order products used by planetary scientists and engineers for analysis and exploration, including image mosaics, basemaps, Digital Elevation Models (DEMs), thermal maps, and other products. Often these spatial data are not processed in ways that are standard or interpretable to users outside the mission science teams, nor are the higher-order products available to the general scientific user, especially over the long term. Earth science data users have addressed this issue and made easily accessible clearinghouses of ready-to-use spatial data, for example for Landsat Enhanced Thematic Mapper images. NASA and the planetary community have recognized the need for a strategy for making planetary spatial data accessible and useable to the planetary community and have assembled the Mapping and Planetary Spatial Infrastructure Team (MAPSIT), similar to other Assessment Groups (AGs). This community group (with the author list as the steering committee) is tasked with preparing a Roadmap for Planetary Spatial Data Infrastructure (PSDI). Here we detail the rationale, outline, and plans for this roadmap