#LPSC2023
#LPSC2023
Program with Links to Abstracts
Schedule Overview
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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.
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.
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.
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.
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.
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.
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: https://dx.doi.org/10.17169/refubium-37236.
We provide the resulting flat-field files that can be used directly in the ISIS environment permanently under this repository: https://dx.doi.org/10.17169/refubium-37236.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Fully Controlling Mars Reconnaissance Orbiter Context Camera Images and Producing Cosmetically Stable Mosaics (2023 Update)
[#2444]
Control big data / Make pretty mosaics of / The martian surface.
Control big data / Make pretty mosaics of / The martian surface.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Full description of the pipeline used to process, standardise, ingest, publish, and display PDS geometry in the ESA’s Planetary Science Archive.
*presenter
