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Poster Session: Planetary Spatial Data Infrastructure, Processing, Mapping, Tools and Machine Learning: The Rise of the Machines

Tuesday, March 14, 2023, 6:30 PM
Town Center Exhibit Hall

Tate C. D.* Annex A. M. Wolff M. Hayes A. H. Randazzo N. et al.
The Metaverse Is Here — So Let’s Use It to Explore Mars [#2888]
Mozilla Hubs and other metaverse platforms show great promise for collaborative planetary exploration, especially for Mars rovers.
Gross C.* Munteanu R. R. C. Walter S. H. G. Patermann L. Schreiner B. et al.
20 Years of High Resolution Stereo Camera Image Releases of ESA's Mars Express Mission [#1951]
After 20 years of image release activity we want to make HRSC data products easily accessible for scientists and the public using Mapservers.
Zuschneid W.* Michael G. G. Walter S. H. G. Postberg F.
The HRSC Level 3 Mosaic of Mars: Equatorial Regions, Mid-Latitudes — Improvements and Outlook [#2168]
We present the current status of the global HRSC Level 3 image mosaic. Equatorial mosaics are completed and updated, and mid-latitudes mosaics are in progress.
Grotheer E.* Breitfellner M. Godfrey J. Heather D. Martin P. et al.
New MEX-HRSC Radiometrically Calibrated Data in the ESA's Planetary Science Archive GIS-Based Map View [#1706]
New HRSC radiometrically calibrated data, now on version 4.0, is available in ESA´s Planetary Science Archive, including via the GIS-based Map View interface.
Itoh Y.* Packer L. L. Kawamura M. S. Romeo G. Matiella Novak A. et al.
Empirical Geometric Normalization for TER/MTRDR Processing of CRISM Restricted Gimbal Range Targeted Observations [#2433]
A new EGN method using the geometric model of early-mission data is proposed for the production of TER/MTRDR suites of post-May 2012 FRS/ATO/ATU observations.
Phillips M. S.* Murchie S. L. Seelos F. P. Hancock K. M. Stephens D. C. et al.
A Processing Pipeline for CRISM Hyperspectral Mapping Data [#2260]
A fresh dataset / To answer questions old, new / HSP map tiles.
Walter S. H. G.* Munteanu R. R. C. Aye K.-M.
CTX In-Flight Calibration and Data Dissemination [#3011]
We provide the resulting flat-field files that can be used directly in the ISIS environment permanently under this repository:
Hidaka M. H.* Ogawa Y. O.
Development of Spectral Data Analysis Tool for Investigating Water Environment of Mars [#2962]
Development of spectral data analysis tool for investigating water environment of Mars.
Belhadfa E. C.* Fujita M. F.
MAGIC: Martian Analysis for Geological and Intelligent Classification [#1400]
MAGIC is an intuitive, interactive tool to perform rapid classification of geophysical data to support ongoing martian research.
Rojas C.* Bell J. F. Paris K. N. Cisneros E. Bailey A. M. et al.
Mastcam-Z Image Products in Mars 2020 Perseverance and Ingenuity Operations [#2504]
Summary of the use of Mastcam-Z products in science and engineering operations, providing insight into instrument operations, data reduction, and data analysis.
Kumari N.* Glotch T. D. Greenhagen B. T.
Brewing Machine Learning Models for Accurate Analysis of Current and Future Mission Datasets [#2396]
We have designed a machine learning model to predict Christiansen feature from the three compositional bands of the Diviner instrument.
Benedix G. K.* Lagain A. Bland P. A.
Can We Create a New View of the Moon with Machine Learning? [#2070]
TLDR: Machine learning means lots of data — craters and crater densities can reveal geologic insights.
Cui X.-L.* Ding M. Yan S. Deng Q. Zhu M.-H.
Globally Automated Lunar Mare and Melt Detection Using Deep Learning [#1869]
We combines the existing mare basalt map for the Moon and the deep learning technique to automatically detect mare-like geologic units with smooth surfaces.
Gauthier J. M.* Wróblewski F. B.
Augmenting Virtual Lunar Terrain with Procedural and Machine Learning Models in Real-Time [#2916]
We present a graphical model showcasing the real-time augmentation of lunar DEMs in virtual reality.
Ogino K.* Ibuka K. Goto M. Ohtake M. Demura H.
Verification of Super-Resolution Method for Lunar Polar DEM by Generative Adversarial Networks [#1932]
This research focuses on how to make high-resolution DEM from only low-resolution ones by SRGAN. This research uses LOLA GDR for the south pole.
DesRochers B.* Lemelin M.
Combining Photogrammetry and Image Super-Resolution to Increase Lunar and Martian Digital Elevation Models Resolution using Descent Imagery [#2873]
This project aims at creating digital elevation models of landing sites with a resolution of up to 2.5 cm per pixel using machine learning and photogrammetry.
Ibuka K.* Ogino K. Goto M. Ohtake M. Demura H.
Image-to-Dem Translation with Conditional Adversarial Networks of Depth Estimation Based on Monocular Images on the Moon [#1927]
This study is a trial to generate lunar DEMs from LRO NAC images using Pix2Pix, which is a type of GAN to learn a set of DEM and visible images.
Beyer R. A.* Alexandrov O. Balaban E. Colaprete A. Shirley M. et al.
VIPER Geospatial Data for Site Selection and Traverse Planning [#2377]
Products like terrain, slope maps, orthoimages, count maps, error maps, maximally-lit mosaics, and depth to ice stability maps, etc., used to help plan VIPER.
Runyon K. D.* DeWitt B. Williams D. Jenet F.
MoonHacker(TM) Lunar Data Analytics: A Case Study for Exploring Amundsen Crater [#1166]
Lunar Station Corporation illustrates its MoonHacker(TM) lunar geospatial analytics capabilities as applied to a case study at Amundsen crater.
Ostrach L. R.* Weller L. A. Wheeler B. H.
Creation of a Near-Global Lunar Control Network Using Kaguya Terrain Camera Data, Progress Report [#2735]
We report on progress creating a near-global lunar control network using the Kaguya Terrain Camera morning stereoscopic and monoscopic datasets.
Archinal B. A.* IAU WG on Cart. Coord. & Rot. Elements 
Considerations on Updating the Lunar Reference Frame [#2305]
Considerations on the current status of the Lunar Reference Frame, whether and how it could be updated, and a request for input from the lunar community.
Speyerer E. J.* Wagner R. V. Robinson M. S. Mahanti P. Humm D.
Geometric Characterization of the ShadowCam Instrument [#1842]
Through a series of pre-flight and in-flight experiments, we have characterized the geometry of the ShadowCam instrument to enable precise mapping inside PSRs.
Harris C. P.* Thomson B. J. Cahill J. T. S. Fassett C. I. Turner F. S. et al.
Analysis of Corrective Methods for Mini-RF Monostatic Data [#2845]
An analysis of methodologies useful for correcting spatial offset errors present in available lunar Mini-RF monostatic radar data.
Narang S.* Pandey H. Gunasekhar P. Ramakrishna B. N.
Integrated Lunar Coverage Information System: Implemented for Chandrayaan-2 Payloads [#1921]
A Lunar Coverage Information System is implemented using the Chandrayaan-2 ground trace and instrument swath to provide quick coverage info for payload plan.
Heyer T.* Hiesinger H. Iqbal W. Schmedemann N.
The Multi-Temporal Database of Planetary Image Data (MUTED): Developing a Web-Service to Automatically Detect Craters in Orbital Images [#1137]
The Multi-Temporal Database of Planetary Image Data (MUTED) is a comprehensive web-tool to identify and access orbital images of Mars, the Moon, and Mercury.
Annex A. M.* Hare T. M. Laura J. R. Manaud N. Malapert J.-C. et al.
Filling in the Gaps in Maps: Embracing Open GIS Standards in Planetary Science [#1668]
We describe progress toward embracing open GIS standards to enable cloud native Planetary Spatial Data Infrastructure across the ecosystem of open GIS software.
Black S. R.* Buban H. C. Wilber C. H. Bogle S. R.
Cultivating Digital Mapping Resources for the Planetary Science Community: Updates for 2023 [#1675]
Planetary maps / For long hard to find and use / Are now made for all.
Hare T. M.* Huber L. Mafi J. Neakrase L. Hartke M. et al.
PDS Annex and the Planetary Data Ecosystem [#2382]
The PDS4 information model will likely see updates to better support the planetary data ecosystem using ideas born from the PDS annex data repository concept.
Hoover R. H.* Robbins S. J. Kirchoff M. R.
Greenberger R. N.* Pinkston D. Wang A. Azad S. Mueller J. et al.
The Workbench for Imaging Spectroscopy Exploration and Research (WISER) — A Customizable, Extendable Visualization and Analysis Tool for Imaging Spectroscopy Data [#2360]
Free Python-based software for imaging spectroscopy data visualization and analysis that can be extended with user-generated plugins.
Phillips M. S.* Moersch J. E. Basu U. Hamilton C. W.
HyPyRameter: A Python Toolbox to Calculate Hyperspectral Reflectance Parameters [#2245]
HyPyRameter / Easily interpret your / Reflectance data.
Fonteyne R.* Konstantinidis K.
Mapping the Landscape of Space Exploration with a Comprehensive Technology Tree [#1519]
The technology tree links technologies or capabilities together to provide more accurate insights to the diverse stakeholders involved in space exploration.
Ward J. G. Guinness E. A.* Scholes D. M. Stein T. C. Politte D. V. et al.
The NASA PDS Geosciences Node in 2023 and Beyond [#1533]
The PDS Geosciences Node helps the planetary science community archive, find, and use data from missions to the terrestrial planets and their moons.
Scholes D. M.* Wang J. Byrne P. K. Guinness E. A. Zhou F.
Recent Enhancements to the PDS Geosciences Node's Orbital Data Explorer [#1561]
A description of recent updates to a NASA PDS web-based search tool (ODE) for locating and downloading orbital data of Mars, Mercury, the Moon, and Venus.
Suresh K.* Prashar A. K. Amitabh 
Chandrayaan-2 Orbiter Data Explorer and Visualization — A Webbased Application for Accessing Imaging Payload PDS Datasets Accessing Imaging Payload PDS Datasets [#1827]
Chandrayaan-2 Imaging Payload datasets are archived in PDS-4 standard and disseminated. This paper discusses the web application for data explorer.
Stein T. C.* Zhou F.
Updates to the PDS Analyst's Notebook [#2194]
Recent updates to the PDS Analyst’s Notebook for Mars 2020, MSL, InSight, MER, and Phoenix.
Zhou F.* Stein T. C. Byrne P. K.
The PDS MSL Analyst's Notebook Map Tool [#2166]
New features of MSL AN Map tool includes contour and science target, locations linked to data products, and map visual setting can be controlled by the user.
Raga F.* Docasal R. Osinde J. Perez H. Saiz J. et al.
ESA’s PSA: PDS3/4 Geometry Generation Pipeline [#1483]
Full description of the pipeline used to process, standardise, ingest, publish, and display PDS geometry in the ESA’s Planetary Science Archive.