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Grant Agreement

776276

Acronym

PLANMAP

Project full title

Planetary mapping

Deliverable

D 7.5

Deliverable Name

Data management plan update

Nature of deliverable

ORDP

Dissemination level

PU

Scheduled delivery date`

31h March 2020 à 15th May 2020

Status

Final

Prepared by:

Angelo Pio Rossi, Luca Penasa, Riccardo Pozzobon

Verified by:

Erica Luzzi

Approved by:

Matteo Massironi

 

 

Disclaimer

This document is property of the PLANMAP Consortium. This document may not be copied,  reproduced,  or  modified  in  the  whole  or  in  the  part  for  any purpose  without  written  permission  from  the  PLANMAP  Coordinator  with  acceptance  of  the Project Consortium.


 

Table of contents

Table of Contents




Executive Summary

The updated PLANMAP Data Management Plan (DMP) is provided. Map-wide metadata structure and fields for PLANMAP mapping products are described and exemplified. The long-term data repository venues for PLANMAP products are listed and specified. Delivery file formats are updated, as reflected by deliverables. Described aspects in this DMP include: beneficiaries producing data, adherence to FAIR principles, data types, formats and standards, metadata, documentation, intellectual property and data storage, archiving and curation during and after the project.


List of acronyms

Acronym

Description

ASCIII

American Standard Code for Information Interchange

ASI

Agenzia Spaziale Italiana

CC-BY

Creative Commons Attribution (license)

CRISM

Compact Reconnaissance Imaging Spectrometer for Mars

CRS

Coordinate Reference System

CTX

Context Camera

DoA

Description of Action

DOI

Digital Object Identifier

EPN-TAP

EuroPlanet Table Access Protocol (TAP)

ESA

European Space Agency

ESAC

European Space Astronomy Centre (ESA establishment)

FELICS

Fast Efficient & Lossless Image Compression System

FTP

File Transfer Protocol

HRSC

High Resolution Stereo Camera

ISIS

Integrated Software for Imagers and Spectrometers

GDAL

Geospatial Data Abstraction Library

GNU

GNU's Not Unix (recursive acronym)

GPL

GNU General Public License

GSF

Guest Storage Facility (for ESA ESAC)

H2020

Horizon 2020 (Framework Programme)

HiRISE

High Resolution Imaging Science Experiment

OMEGA

Observatoire pur la Minéralogie, l'Eau, les Glaces et l'Activité

LROC

Lunar Reconnaissance Orbiter Camera

M3

Moon Mineralogy Mapper

MESSENGER

MErcury, Surface, Space ENvironment, GEochemistry and Ranging

MDIS

Mercury Dual Imaging System

MLA

Mercury Laser Altimeter

MOC

Mars Orbiter Camera

NAC

Narrow Angle Camera

OGC

Open Geospatial Consortium

PDS

Planetary Data System (archive, organisation, standard)

PSA

Planetary Science Archive (ESA planetary archive)

PUG

Product User Guide (for ESA GSF)

RDR

Reduced Data Record

SME

Small, Medium Enterprise

SNR

Signal to Noise Ratio

SPICE

Spacecraft ... Planet ... Instrument ... C-matrix (orientation) ... Events

SWIR

Short-Wave InfraRed (spectral range)

TAP

Table Access Protocol (VO)

USGS

United States Geological Survey

VESPA

Virtual European Solar and Planetary Access

VICAR

Video Image Communication And Retrieval

VNIR

Visible and Near Infrared (spectral range)

VO

Virtual Observatory

WAC

Wide Angle Camera


 

Introduction

PLANMAP will both use and produce data. Different data categories can be distinguished in the framework of PLANMAP:

Base mapping data:

  • A) Individual higher-level data products derived from raw experiment data (which are archived on PDS or PSA), e.g. map-projected individual images or custom calibrated cubes (e.g. CTX, OMEGA, CRISM)
  • B) Custom processed or mosaicked data from multiple data products (i.e. derived hyperspectral summary products, multi-image mosaics) available in public archives or repositories (e.g. PSA, PDS, USGS)
  • C) Individual higher-level data products already produced by experiment teams and available from PDS/PSA archives (e.g. HRSC)
  • D)Custom processed or mosaicked data with from multiple data products (i.e. derived hyperspectral summary products, multi-image mosaics) produced by the consortium

Integrated mapping products:

  • Intermediate temporary mapping products (for scientific discussion and sharing within the consortium)
    • Raster imagery/data
    • Vector mapping data
  • Finished geological maps (See D2.1 (Mapping Standards), Rothery et al, 2018, D2.2-public (Morphostratigraphic maps, Rothery et al., 2019)
    • Standard USGS-like geological maps
    • Integrated geo-spectral and geo-stratigraphic maps
    • Geo-structural maps
    • Geo-modelling maps
    • Landing site and traverse maps
    • In-situ integrated maps
    • Digital outcrop models
    • Subsurface models
    • 3D models for Virtual Reality environments (from one or more of the above categories)

The fate of datasets and data products belonging to these categories is different. Individual data products (A B, C) are preserved for the long-term in appropriate archives. Their eventual reduction and reprocessing is reproducible, with well-known open source tools, and supported for the long term by robust institutions and agencies (e.g. USGS/NASA). Intermediate mapping products are instrumental to producing final, released and/or published PLANMAP digital mapping products (see section on Data Storage and Management during the project) and their long term-storage is not planned, but documentation, in the form of wiki or individual documents is going to be preserved during the course of the project, and significant summaries and excerpts will be included as deliverable text and annexes, and can also be used as ancillary material attached to scientific publications.

The current long-term archiving and availability of PLANMAP data is as follows (please refer to relevant subsections below):


Scope of the document

The present document updates the type of data, their characteristics and their use, archiving and preservation plans throughout the PLANMAP project. Intellectual property rights are also clarified, as well as specific per-partner data use and responsibilities. The document outlines the basic data management directions that are going to be updated throughout the project and issued at discrete steps.


Beneficiaries using data

All beneficiaries will use data, in either individual or - in most cases - combined forms. Data access to archived (NASA/ESA) mission data is free for anyone. Some data will have temporary team-only access (during an embargo of up to several months), such as mapping data used by PLANMAP researchers (see section on Data Storage and Management during the project)

Beneficiaries producing data

All beneficiaries will produce either derived data (higher-level data products) or new data derived by both human and computer/algorithm-assisted mapping.

In particular, beneficiaries are set to produce these data categories (see Annex A, B):

  • UNIPD: 
    • mosaics and higher-level products derived from planetary archives
    • vector mapping products (geologic/geomorphologic maps)
    • 3D models
    • (subject to increase/expansion)
  • OU
    • mosaics and higher-level products derived from planetary archives
    • vector mapping products (geologic/geomorphologic maps)
    • (subject to increase/expansion)
  • WWU
    • mosaics and higher-level products derived from planetary archives
    • vector mapping products (geologic/geomorphologic maps)
    • (subject to increase/expansion)
  • INAF
    • mosaics and higher-level products derived from planetary archives
    • (subject to increase/expansion)
  • CNRS
    • 3D and virtual reality models
    • digital outcrop maps
    • vector mapping products (geologic/geomorphologic maps and models)
    • (subject to increase/expansion)
  • JacobsUni
    • mosaics and higher-level products derived from planetary archives
    • vector mapping products (geologic/geomorphologic maps)
    • (subject to increase/expansion)


Adherence to FAIR principles

Data produced by PLANMAP will impact future robotic and space exploration, mainly through mature, finished, published mapping products. Underlying data and special mapping products will be of scientific use also before and beyond that. Accessibility to the data will be provided in three different forms:

Findable data:  

  • Longer-term discoverability will be guaranteed via connected Institutional repositories (ESA, UNIPD, INAF), VESPA sharing and inclusion in planetary data archives that are accessible and commonly used by the community. 
  • Shorter-term discoverability will be supported by the PLANMAP web-map and data access 



Accessible data:

  • Geological mapping products will have multiple level of accessibility, with variable scale and complexity, from individual units to finished products and thematic maps

Interoperable data:

  • OGC standards for CRS and formats will be adopted 
  • Data discovery interoperability will be granted via the use of state-of-the-art VESPA EPN-TAP (Virtual European Solar and Planetary Access  EuroPlanet Table Access Protocol) for data search and query.

Re-usable data: 

  • Raw data will be used and processed/reduced, with embedded re-usability upstream with respect to PLANMAP
  • Custom base-map data (e.g. mosaics) and partial mapping products and processed/derived datasets underlying geological mapping products (standard, non-standard, integrated, etc.) will be usable by others, also in the future, regardless of the final geological mapping products.
  • Integrated and/or final mapping products will be re-usable directly or indirectly, with access to combined information content or individual layers (See D2.1 (Mapping Standards), D2.2-public) with relevant topologies (units, contacts, etc.).

Data types, formats and standards

PLANMAP uses existing datasets and data products and creates new products deriving from combination or derivation of existing, processed data products, as well as from completely new mapping (e.g. units), see D2.1 (Mapping Standards) (Rothery et al., 2018).


Data

Raw data

Planetary archives, PDS3, PDS4 imagery and cubes.

Base mapping data

OGC-compliant data already available from external entities (e.g. USGS) or base mapping data produced by PLANMAP partners, some in PDS standards/formats.

Integrated mapping products

Integrated mapping products with individual layers are being produced in OGC-compliant formats, both raster and vector, as well as with suitable 3D formats (See Annex A). All individual layers/components of maps are in geospatial format and with CRS suitable for the specific mapping project: in-situ, local (mostly non-standard, see D2.1 (Mapping Standards)), regional or global (both standard and non-standard).


Metadata

The aim of including metadata is to allow reproducibility by providing information about the processing steps performed. Map-wide metadata including both geometric and bibliographic information are provided for each map (e.g. as accessible on https://data.planmap.eu/).

Raw data

Metadata from processed raw data are the same as those from archived data. SPICE kernel version and software used (e.g. USGS ISIS) should be recorded.

Isis Cube labels (i.e. recording cumulative processing steps and used ancillary data, metadata, CRS and alike). The information is going to be recorded in processing labels and as temporary output in ASCII format.

Base mapping data

Projection, cubes and images used, type of control network used, and relevant additional information available from original derived data producers (e.g. USGS, ESA, academic institutions or local PLANMAP base mapping data producers or groups) will be recorded.

Integrated mapping products

Metadata for integrated mapping products will be both map-related and sub-map-related (i.e. geological unit).

Map-related metadata include, as a minimum:

  • Used datasets and products
  • Mapping individuals
  • CRS
  • Summary of used tools and documented workflow

Unit-related data/metadata include, as a minimum, recorded and updated during the mapping processes, see also D2.1-public.

  • Individual products and layers used to determine unit extent and contacts
  • Eventual interpolation/extrapolation of data underlying mapped unit outline
  • Qualitative assessment on uncertainties involved in the unit determination

Authors of the maps, programs, processing and basic info to allow reproducibility of the underlying workflow is included and added to the documentation. Also, geocoding of units (i.e. associating toponyms to locations and mapped surface units) will be produced in order to ease search of at least individual maps as well as individual units and their occurrence within maps (Rossi et al, 2018).




Map types

PLANMAP map-types, as per DoA and subsequent updates (e.g. See D7.6, D6.1) include:

  • S = Stratigraphic
  • C = Compositional
  • M = Morphologic
  • G = Geo-structural
  • I = Integrated
  • D = Additional DOM-specific mapping products for individual or multiple lander/rover-imaged outcrops can be included


Map-level metadata

Complementing metadata related to individual units, each map of PLANMAP include several map-wide fields, exemplified below:


Field

Field description (and example entries)

Map name (PM_ID)

PM-MER-MS-H02_3cc

Target body

Mercury

Title of map

Geologic Map of the Victoria Quadrangle (H02), Mercury

Bounding box - Min Lat

-22.5°

Bounding box - Max Lat

65°

Bounding box - Min Lon (0-360)

270°

Bounding box - Max Lon (0-360)

360°

Author(s)

Valentina Galluzzi; Laura Guzzetta; Luigi Ferranti; Gaetano di Achille; David A. Rothery; Pasquale Palumbo

Type

Released

Output scale

1:3M

Original Coordinate Reference System

Lambert conformal conic

Center longitude: 315°

Standard parallel 1: 30°

Standard parallel 2: 58°

Datum: 2440 km (non-IAU, MESSENGER team datum)

Data used

MESSENGER MDIS BDR v0 uncontrolled basemap (166 m/pixel)

MESSENGER MDIS 2013 complete uncontrolled basemap (250 m/pixel)

MESSENGER MDIS uncontrolled mosaics v6, v7, v8 (250 m/pixel)

MESSENGER MDIS partial mosaic (USGS) (200 mpp)

MESSENGER MDIS 2011 albedo partial mosaic (USGS) (200 m/pixel)

Mariner 10 + MESSENGER flyby uncontrolled basemap (USGS) (500 m/pixel)

MESSENGER MLA DTM (665 m)

MESSENGER MDIS M2 flyby stereo-DTM (DLR) (1000 m)

Standards adhered to

Mapping scale: Tobler (1987); Output scale: USGS; Symbology: USGS FGDC and other new symbols

DOI

10.1080/17445647.2016.1193777

Aims

Morpho-stratigraphic analysis of Mercury's units and BepiColombo target selection.

Short description

Mercury’s quadrangle H02 ‘Victoria’ is located in the planet’s northern hemisphere and lies between latitudes 22.5° N and 65° N, and between longitudes 270° E and 360° E. This quadrangle covers 6.5% of the planet’s surface with a total area of almost 5 million km2. Our 1:3,000,000-scale geologic map of the quadrangle was produced by photo-interpretation of remotely sensed orbital images captured by the MESSENGER spacecraft. Geologic contacts were drawn between 1:300,000 and 1:600,000 mapping scale and constitute the boundaries
of intercrater, intermediate and smooth plains units; in addition, three morpho-stratigraphic classes of craters larger than 20 km were mapped. The geologic map reveals that this area is dominated by Intercrater Plains encompassing some almost-coeval, probably younger,
Intermediate Plains patches and interrupted to the north-west, north-east and east by the Calorian Northern Smooth Plains. This map represents the first complete geologic survey of the Victoria quadrangle at this scale, and an improvement of the existing 1:5,000,000 Mariner 10-based map, which covers only 36% of the quadrangle.

Related products

Geologic Map of the Hokusai Quadrangle (H05), Mercury

Geologic Map of the Shakespeare Quadrangle (H03), Mercury (pre-Planmap)

Geologic Map of the Kuiper Quadrangle (H06), Mercury (pre-Planmap)

Units Definition (polygon styling)

Smooth Plains, sp, 255-190-190

Northern Smooth Plains, spn, 245-162-122

Intermediate Plains, imp, 245-122-122

Intercrater Plains, icp, 137-90-68

Crater material-well preserved, c3, 255-255-115

Crater material-degraded, c2, 92-137-68

Crater material-heavily degraded, c1, 115-0-0

Crater floor material-smooth, cfs, 255-255-175

Crater floor material-hummocky, cfh, 205-170-102

Stratigraphic info

This map has an associated database of craters larger than 5 km used for basic crater frequency analysis for N(5), N(10), and N(20).

Other comments

Since the mapping scale (~1:400k) was much higher than the output scale (1:3M) the polylines of the map were not smoothed.

This map is currently being updated to fit the new controlled MESSENGER's end-of-mission basemaps.

A post-release boundary merging was done with the H03 and H05 quadrangles.

This map uses a legend also for feature labels.

Heritage used

former Mariner 10 map by McGill and King (1983)

Link to other repositories

(crater database link)

(shapefiles database link)

Acknowledgements beyond Planmap

This research was supported by the Italian Space Agency (ASI) within the SIMBIOSYS project [ASI-INAF agreement number I/022/10/0]. Rothery was funded by the UK Space Agency (UKSA) and STFC.

Table 1: Exemplary map-wide metadata for PLANMAP products, implemented for a PLANMAP in-kind contribution (Geologic map by Galluzzi et al., 2016) see https://data.planmap.eu/pub/mercury/PM-MER-MS-H02_3cc/

A subset of metadata are (see section on ESA PSA delivery) is also included on the datasets released to ESA.

Documentation

Documentation of PLANMAP will be available on the project wiki space (https://wiki.planmap.eu/display/planmap), which will be kept functional after project-end based on best-effort and availability of resources. The internal wiki space is used for both internal project coordination and technical, scientific documentation. The latter, in evolved form, will be also shared via the project public wiki space (https://wiki.planmap.eu/display/public).

The types of documentation in the PLANMAP wiki include:

  • Summary of relevant activities per WP
  • Procedures and workflows 
  • Mapping use case description
  • Best practices and recommendations
  • Tutorials on data handling and mapping
  • Other documents

Software

The software used to access and analyze PLANMAP data will be based on Open Standards, in particular OGC standards. Both Open Source and proprietary software (such as QGIS, ArcGis, and such like) will therefore be suitable for accessing PLANMAP data. A particular case is constituted by the software that is employed for 3d geological modeling, for which open source alternatives rarely exist. For the choice of the software package two criteria will be considered: a) the feasibility for the task that will be undertaken b) the academic licensing scheme that is adopted. Under the same feasibility conditions, software packages granting low-cost/affordable licensing schemes for academic purposes will be favoured.

The consortium will use a wide range of publicly available Open Source and commercial tools to work and perform mapping tasks. Additionally, algorithmic and programmatic methods that add value to interactive human-computer mapping will also use, as far as possible, Open Source tools, packages and libraries.

Software, tools and scripts or snippets developed throughout the project will be shared both internally and externally via the PLANMAP GitHub organization and relevant repositories (https://github.com/planmap-eu). Some repositories might be private, with access restricted to beneficiaries, during the early phases of the project. Ultimately, all will be made public and will be made available indefinitely after the end of PLANAMP. 

Data exploitation, accessibility and intellectual property

Intellectual property rights on individual science outputs will be held by the scientific collaborators and publishing venue/journal (e.g. individual papers).  Data and maps published on the PLANMAP data archive (ESA Guest Storage facility, INAF, UNIPD or other institutional data repositories) and their long-term evolution are cited either via their dataset DOI or via relevant linked publications.

Data and metadata

Produced base mapping data are provided as CC-BY (attribution).

Published maps (of any kind) are going to be provided, free to use, with CC-BY (attribution).

Acknowledgment of the PLANMAP EC H2020 Space project is requested from those using PLANMAP-derived data. A relevant acknowledgement message will be included in the documentation provided to ESA, as well as within the global metadata of VESPA-shared datasets.

Documentation

Documentation licensing will follow Creative Commons CC-BY-4.0 (https://creativecommons.org/licenses/by/4.0/). Documentation will be also available, complementing or copying information on the public wiki space, on GitHub and possibly other public repositories. 

At the end of the project the entire body of documentation will be consolidated and available both on the PLANMAP public (https://wiki.planmap.eu/display/public)  wiki and GitHub (https://github.com/planmap-eu).


Software 

Software developed by PLANMAP partners is going to be open source, with the possible exception of specific software involving SMEs (e.g. subcontracted within virtual-reality tasks). GPLv3 is recommended, or any other license covered by the Open Source initiative (https://opensource.org/licenses/category).

Specific licensing for WP involving SMEs and potential exploitation beyond the project of pre-existing or specific technological aspects WP5 will be established and documented.

Software, tools and scripts produced by PLANMAP will be available as soon as they are considered usable, on the public GitHub organisation (https://github.com/planmap-eu). Private repositories will be used during the course of the project but will cease to exist at its end and all will be made public.

Data/Software citation

Archived data used that comes from mission archives will follow the custom of quoting experiment description papers and eventual relevant follow-up papers (e.g. Malin et al., 2007; McEwen et al., 2007; Neukum et al., 2004; Jaumann et al., 2007).

Datasets from NASA/ESA archives (PDS, PSA) follow the citation requirements of those archives. In the case of NASA public domain data, the experiment-description papers (e.g. Malin et al., 2007) would be cited in scientific publications.  ESA data follow similar citation styles (suggested citations are included in the PSA entry pages).

Datasets produced by the PLANMAP consortium will be possibly quoted via:

  • Relevant peer-reviewed publications or published maps indicated in the dataset metadata (similar to PSA/VESPA)
  • Dataset-specific DOI, i.e via OpenAIRE/Zenodo/GitHub for relevant datasets
  • Eventual additional DOI-generating data services that might become available during the project lifetime

Data storage and management during project

During day-to-day operations and technical/scientific activities of the consortium, data will be stored on each partner's premises as well as, when relevant, on shared network resources (such as cloud, FTP and web mapping data access services). In principle, data will be made publicly available as soon as possible during the project, respecting publication embargoes.

Data curation, archiving, preservation and security

Data curation 

Base data and maps (See Annex A) undergo archiving review by the archive maintainers (PDS, PSA). If any issue is encountered (e.g. missing or problematic labels, metadata and/or eventual problems with data themselves) the PLANMAP consortium will share that information with respective archive data publishers (PDS, PSA).

Mapping is an iterative, interactive process that will go through a few levels of interactive, informal and formal scientific review within the PLANMAP partners and consortium. Before a final map is produced (and its related scientific publication is submitted), preliminary versions will be shared on the PLANMAP web page, wiki and web-mapping data access page (https://maps.planmap.eu/ and its file-based access site on https://data.planmap.eu/). 

In case underlying base mapping data require or are subject to improvements that will affect the mapping, newer versions will be used and posted, and metadata updated.




Data preservation

Input data (based data and maps) are preserved by the respective archives and not under PLANMAP responsibility.

Custom higher-level data imagery, cubes, virtual environments and 3D models produced by PLANMAP partners during the course of the project will be preserved on PLANMAP storage services. After the project data will be shared (See Data Sharing subsection), optimally with some redundancy and in different geographic locations, for longer-term availability.

Data security

The PLANMAP data processed, produced and analysed are not sensitive. No specific security measures are planned. Data recovery, in case of storage failures will be optimised by the use of central backup and local copies across PLANMAP partner institutions.

Data sharing

Data sharing will be performed via 4 possible channels:

  • Individual partners. E.g., on own web site or repositories using industry standards for geodata (e.g. web-GIS)
  • PLANMAP consortium, via web-gis and data-access web page, linked form the PLANMAP web page
  • ESA PSA, upon delivery of data and mapping products
  • VESPA, via distributed VO-compliant systems for integrated mapping products and, in the future, potentially sub-map, mapping unit-level access (e.g. individual mapping units).

EPN-TAP VESPA-based sharing on premise

VESPA-shared data contain data-product-level metadata pointing to actual data sources. The release of data (see DoA) is planned in steps, to conclude by the end of the project. 


Exemplar metadata for mapping products to be released via VESPA:

A set of mandatory, documented metadata for VESPA services exists (https://voparis-confluence.obspm.fr/display/VES/Implementing+a+VESPA+service), plus optional ones. Those are mostly related to data-products (in PDS sense) with some dataset-wide. Individual unit granularity is not yet covered by VESPA technical capabilities.

New developments of VESPA (currently not implemented but envisaged for future VESPA developments within the lifetime of PLANMAP) should allow for metadata-based discovery and search that could extend the geographic data search and experiment metadata search with feature/unit data/metadata search.

ESA PSA data deliveries 

Individual used data products already existing in planetary archives (PDS, PSA) will not be released to PSA (already in PDS in either raw or processed form).

Exemplary metadata for mapping products to be released via PSA:

Release to PSA of non-PDS data, geological mapping data, with relevant documentation is going to be provided (See D7.6). Periodically, shortly after each formal delivery, possibly more often if needed, data from the Planmap data portal (https://data.planmap.eu) are being provided to ESA with additional map-wide metadata and description as required by ESA (ESA, 2019), including:

  • target body
  • geographic extent (bounding box) of mapping product
  • CRS
  • additional fields as described in the Map-wide metadata table in the above sections.

Data exchange formats for archived data will include:

  • For raster data = preferentially Geotiff
  • For vector data = preferentially OGC/Geopackage
  • Additional files or the same version of release raster files also provided in different formats might include e.g. ISIS3 cube (.cub) format, Envi (.img + .hdr) or alike.

A copy of the data in either geotiff (raster) and Geopackage (vector) will be provided in any case, where relevant.

Each Planmap map (with a unique PM_ID) is considered as a dataset for ESA GSF, with specific authors and DOI. Each map includes typically more products (e.g. pdf layout view, one or more raster imagery, one or more vector datasets packed inside a Geopackage).

The structure of the PUG for each planmap map / planmap ESA GSF dataset is following such structure:

  1. Introduction

       1.1 Dataset (PM_ID) introduction

       1.2 Abbreviations and acronyms

       1.3 References and applicable documents

  1. Dataset generation

       2.1 Data source

       2.2 Processing steps

       2.3 Data product

  1. Archive format and content

       3.1 Naming convention

       3.2 Data types and formats

       3.3 Directory structure

       3.4 Dataset content

  1. Software
  2. Caveats and issues

Such PUG is going to be based on Planmap public deliverables and relevant literature therein.

Annex-A: Planmap datasets

PLANMAP will use existing datasets both as previously and externally processed, mosaicked and merged data ("Base Maps") and selected subsets of datasets, including multiple data products used individually and/or in combination. Individual datasets used or envisaged are listed in the Annex. The list and information contained is subject to updates and improvement throughout the course of the project and the mapping activities.

Base data


Planetary Body

Product

Resolution

Additional info/datasets

URL

Mars

Mars HRSC MOLA Blended DEM Global

200 m/pixel


https://astrogeology.usgs.gov/search/map/Mars/Topography/HRSC_MOLA_Blend/Mars_HRSC_MOLA_BlendDEM_Global_200mp_v2

Mars

MOLA

463 m/pixel

MEGDR/PEDR

https://astrogeology.usgs.gov/search/map/Mars/GlobalSurveyor/MOLA/Mars_MGS_MOLA_DEM_mosaic_global_463m

Mars

THEMIS daytime mosaic

100 m/pixel

IR day

https://astrogeology.usgs.gov/search/map/Mars/Odyssey/THEMIS-IR-Mosaic-ASU/Mars_MO_THEMIS-IR-Day_mosaic_global_100m_v12

Mars

THEMIS night-time mosaic

100 m/pixel

IR night

https://astrogeology.usgs.gov/search/map/Mars/Odyssey/THEMIS-IR-Mosaic-ASU/Mars_MO_THEMIS-IR-Night_mosaic_60N60S_100m_v14

Mars

Viking MDIM2.1 Grayscale Global Mosaic

232 m/pixel


https://astrogeology.usgs.gov/search/map/Mars/Viking/MDIM21/Mars_Viking_MDIM21_Mosaic_global_232m

Moon

LRO LROC-WAC Global Morphology Mosaic

100m/pixel


https://astrogeology.usgs.gov/search/map/Moon/LRO/LROC_WAC/Lunar_LRO_LROC-WAC_Mosaic_global_100m_June2013

Moon

LROC WAC DTM GLD100

118 m/pixel


https://astrogeology.usgs.gov/search/map/Moon/LRO/LROC_WAC/Lunar_LROC_WAC_GLD100_79s79n_118m_v1_1

Moon

LRO NAC Frames and Higher-Level Data Products


Mosaics/DTMs

http://wms.lroc.asu.edu/lroc/rdr_product_select

Moon

LRO LOLA Elevation Model (LDEM GDR)

118m


https://astrogeology.usgs.gov/search/details/Moon/LRO/LOLA/Lunar_LRO_LOLA_Global_LDEM_118m_Mar2014/cub

Moon

Clementine UVVIS Warped Colour Ratio Mosaic

200 m/pixel


https://astrogeology.usgs.gov/search/map/Moon/Clementine/UVVIS/Lunar_Clementine_UVVIS_Warp_ClrRatio_Global_200m

Moon

Clementine UVVIS FeO Colour Binned

1 km/pixel


https://astrogeology.usgs.gov/search/map/Moon/Clementine/UVVIS/Lunar_Clementine_UVVIS_FeO_ClrBinned_70S70N_1km

Moon

LRO LOLA and Kaguya Terrain Camera DEM Merge

59 m/pixel

From 60N to 60S

https://astrogeology.usgs.gov/search/map/Moon/LRO/LOLA/Lunar_LRO_LrocKaguya_DEMmerge_60N60S_512ppd

Mercury

BDR (map-projected Basemap RDR)

166 m/pixel

monochrome morphology mosaic

https://astrogeology.usgs.gov/search/map/Mercury/Messenger/Global/Mercury_MESSENGER_MDIS_Basemap_BDR_Mosaic_Global_166m

http://pdsimage.wr.usgs.gov/Missions/MESSENGER/MSGRMDS_4001

Mercury

HIE (map-projected High-Incidence angle basemap illuminated from East RDR)

166 m/pixel

monochrome morphology mosaic with Sun from East

http://pdsimage.wr.usgs.gov/Missions/MESSENGER/MSGRMDS_7001

Mercury

HIW (map-projected High-Incidence angle basemap illuminated from West RDR)

166 m/pixel

monochrome morphology mosaic with Sun from West

http://pdsimage.wr.usgs.gov/Missions/MESSENGER/MSGRMDS_7101

Mercury

LOI (map-projected Low-Incidence basemap RDR)

166 m/pixel

monochrome low-incidence angle mosaic

https://astrogeology.usgs.gov/search/map/Mercury/Messenger/Global/Mercury_MESSENGER_MDIS_Basemap_LOI_Mosaic_Global_166m

http://pdsimage.wr.usgs.gov/Missions/MESSENGER/MSGRMDS_7201

Mercury

USGS M10+MESSENGER

500 m/pixel

Mariner 10 + MESSENGER flybys combined mosaic

https://astrogeology.usgs.gov/search/map/Mercury/Messenger/Global/Mercury_M1_M2_M3_M10_mosaic_global_2010


CTX (Malin et al., 2007)

Dataset reference and name and acronym

Context Camera (CTX)

Organisation

Malin Space Science Systems, Inc.

Instrument description

CTX is a linescan camera with a 5000-element linear CCD (Kodak KLI-5001G) with 7x7 micron pixels. The CTX telescope is a 350 mm f/3.25 catadioptric with two front and two rear correcting elements. Its field of view is about 5.7 degrees, covering a 30-km swath from 300 km altitude at a resolution of 6 meters/pixel. Its mechanical structure is a composite configuration in which the metering structure is graphite/cyanate-ester (GR/CE), the primary mirror is Zerodur, and the elements are mounted in Invar and titanium cells.

Dataset Description

The Mars Reconnaissance Orbiter (MRO) Context Camera (CTX) is designed to obtain grayscale (black & white) images of Mars at 6 meters per pixel scale over a swath 30 kilometres wide. CTX provides context images for the MRO HiRISE and CRISM.

Standards

PDS3

Spatial extent

Swath width: 30 km

Swath length: variable between 50 km and 300 km

nearly 80% of Mars covered at 2018

Spectral Range

none

Temporal extent

2006-still active

Archive contact (e.g. PDS)

http://pds-geosciences.wustl.edu/contact/default.htm

Data format (raw)

.IMG

Data format (processed)

JP2, PNG, GeoTiff, OGR web services

Archiving URL (archive)

https://pdsimg.jpl.nasa.gov/data/mro/mars_reconnaissance_orbiter/ctx/

Preservation

performed by NASA PDS

Acknowledgements


Table X: Dataset description for the MRO CTX dataset



HRSC

Dataset reference and name

High Resolution Stereo Camera

Organisation

DLR Institute of Planetary Research, Freie Universität Berlin

Instrument Description


Dataset Description

MEX-M-HRSC-3-RDR-V3.0


The High-Resolution Stereo Camera (HRSC) Digital Terrain Map Reduced Data Record (DTMRDR) data products are 8-bit orthoimages for the Nadir channel and the 4 colour channels and 16-bit DTMs (1 m numeric height resolution).  The orthoimages are based on the DTMs and are thus available exclusively for areas covered by the DTMs.

The DTM and the adjusted orientation data are finally applied for orthoimage production.  The only additional pre-processing step for orthoimages consists of a histogram-based linear contrast stretch which does not affect the linear metrics of the radiometric image calibration.

Dataset Description

MEX-M-HRSC-5-REFDR-DTM-V1.0

DTM generation is based on multi-image matching using pyramid-based least-squares correlation after pre-processing by adaptive (variable bandwidth) Gaussian low pass filtering of the stereo images to reduce the effects of image compression.  3D Point determination by least-squares forward intersection is followed by DTM grid interpolation (distance weighted averaging within a local interpolation radius).  The overall process involves automatic procedures in combination with standardized quality checks.  DTM generation uses adjusted orbit and pointing data.

Based on the high-resolution DTM result, the quality of co-registration with the Mars Orbiter Laser Altimeter (MOLA) DTM is evaluated, and final improvements to the exterior orientation data are derived.

Dataset Description

MEX-M-HRSC-5-REFDR-MAPPROJECTED-V3.0

The High-Resolution Stereo Camera (HRSC) Version 3 Map-Projected Reduced Data Record (REFDR3) data products are standard IMAGE objects derived from the RDRV3 data products.  Version 3 products were produced after an improved radiometric calibration.  REFDR3 products are also produced in JPEG 2000 format in addition to the typical IMG format. Footprints are also calculated for each image along with map projection.

Standards

PDS3

Spatial Resolution

DTM: 100 m

RDR V3.0: 12.5 m/pixel

Spatial Extent

Swath width: 52 km

Swath length: 300 km (minimum)

Spectral Range

Panchromatic: 675±90 nm Nadir, 2 stereo, 2 photometric

Near-IR: 970±45 nm

Red: 750±20 nm

Green: 530±45 nm

Blue: 440±45 nm

Temporal Extent

2003-present

Upstream contact (e.g. PDS)

ESA PSA - https://www.cosmos.esa.int/web/psa/contact-us

Data Format (raw)

.IMG (VICAR)

Data Format (processed)

JP2, PNG, GeoTiff, OGR web services

Access URL (archive)

http://psa.esac.esa.int/pub/mirror/MARS-EXPRESS/HRSC/

Preservation

Performed by ESA PSA

Acknowledgements

ESA planetary Science Archive, HRSC Principal Investigator(s): G. Neukum (Freie Universität, Berlin, Germany),

Table X: Dataset description for the MEX HRSC dataset


Hirise (McEwen et al., 2007)

Dataset reference and name

High Resolution Imaging Science Experiment

Organisation

University of Arizona

Instrument Description

The High Resolution Imaging Science Experiment (HiRISE) camera offers unprecedented image quality, giving us a view of the Red Planet in a way never before seen. It’s the most powerful camera ever to leave Earth’s orbit imaging Mars at a resolution of ~0.25 m/pixel. Colour information can be derived from RED (covering the whole swath) Blue-Green and NIR channels. HiRISE is designed to take stereo couples that can be used to reconstruct with photogrammetry the topography of Mars at 1m of horizontal resolution and tens of centimetres of vertical accuracy.

HiRISE offers three data sets, the Experiment Data Record (EDR) data set, the Reduce Data Record (RDR), and the Digital Terrain Model (DTM) data set (in addition, ODE presents the Anaglyphs as a fourth data type - see below). EDRs are raw images from the spacecraft. RDRs are combined and processed images based on several EDRs. DTMs are sets of digital elevation models along with the ortho images used to create them.

Dataset Description

MRO-M-HIRISE-3-RDR-V1.0

HiRISE reduced data records without embedded map projection

The High-Resolution Imaging Science Experiment (HiRISE) Reduced Data Record (RDR) products are combined and processed radiometrically-corrected, geometrically-mapped images based on several EDRs at nominal resolution of 30 cm/pixel from 300 km altitude.  Due to a mid-2008 change in RDR format to include embedded map projection information within the JPEG 2000 files, the majority of RDR products are Version 1.1.

Dataset Description

MRO-M-HIRISE-3-RDR-V1.1

HiRISE Reduced Data Records with embedded map projection


MRO-M-HIRISE-2-EDR-V1.0

The High-Resolution Imaging Science Experiment (HiRISE) Experiment Data Record (EDR) products are the permanent record of the HiRISE raw image data collection.  An EDR contains unprocessed image data (except as noted below), ancillary engineering data, and information about the instrument commanding used to acquire the image.  An EDR image has the inherent properties of raw and unprocessed data.  Data gaps may exist in an EDR primarily due to telemetry communication problems between Mars and Earth.  The image pixel values are raw counts not yet radiometrically corrected. No geometric processing has been applied to the data to correct for optical distortion or view geometry.


The format is nearly identical to the original from of the data stream as produced by the instrument.  Some processing was applied to the data for (1) FELICS decompressing an image (if the data were optionally compressed on the spacecraft), (2) identifying and filling gaps with “no-data” values, (3) mirroring the pixel order of an image line for data read out in reverse order, and (4) adding a PDS label to the beginning of the file.

Dataset Description

DTM

HiRISE images are usually 0.25 - 0.5 m/pixel, so the post spacing is 1-2 m with vertical precision in the tens of centimetres. 

  • The DTM in standard PDS image object (.IMG) format with an embedded label 
  • Orthoimages at the same resolution as the DTM, in JPEG2000 format with detached label 
  • Orthoimages at the resolution of the original image, in JPEG2000 format with detached label

Standards

PDS3

Spatial Resolution

0.25 m/pixel

Spatial Extent

local, targeted

Swath width(Blue-Green-NIR): 1.2 km

Swath width(RED): 6 km

Swath length: 12 km

Spectral Range

Blue-Green (BG): 400 to 600 nm
Red: 550 to 850 nm
Near infra-red (NIR): 800 to 1000 nm

Temporal Extent

2006-present

Upstream contact (e.g. PDS)

NASA PDS- https://pds.nasa.gov

Data Format (raw)

.IMG

Data Format (processed)

.JP2

Access URL (archive)

https://hirise-pds.lpl.arizona.edu/PDS/

Preservation

Performed by NASA PDS

Acknowledgements

NASA/JPL/University of Arizona, A. McEwen (UoA)

Table X: Dataset description for the MRO HiRISE dataset



CaSSIS (Thomas et al., 2017)

Dataset reference and name and acronym

CaSSIS - Colour and Stereo Surface Imaging System

Organisation

University of Bern

Instrument description

CaSSIS will characterise sites that have been identified as potential sources of trace gases and investigate dynamic surface processes – for example, sublimation, erosional processes and volcanism – which may contribute to the atmospheric gas inventory. The instrument will also be used to certify potential landing sites by characterising local slopes, rocks and other possible hazards by acquiring stereoscopic images. The rotation mechanism will be able to turn the entire telescope system by 180° while its support structure remains fixed. This rotation system will also enable the camera to acquire stereo images with only one telescope and focal plane assembly. A stereo image pair will be acquired by first rotating the telescope to point 10° ahead of the spacecraft track to acquire the first image, then rotating it 180° to point 10° behind for the second stereo image. Optimal correlation of the stereo signals will be ensured as there will be identical illumination conditions every time a stereo image pair is acquired. The imager will cover an eight-kilometre-wide swathe of the planet's surface in four different wavelength ranges.

Dataset Description

4 colour (PAN, IR, RED, BLUE) with stereo acquisition along track.

Stereo angle from 400 km altitude 22.39°

DTM: n/a, available in late 2018

Standards

PDS4 to be implemented

Spatial Resolution

4.62 m/pixel

Spatial extent

Swath width: 7-9 km

Swath length: variable 40-50 km

Spectral Range

Pan: 675 nm / 250 nm

Blue-Green: 485 nm / 165 nm

Red: 840 nm / 100 nm

IR: 985 nm / 220 nm

Temporal extent

Nominal mission: 2018-still active

Archive contact (e.g. PDS)

n/a

Data format (raw)

.dat, .xml

Data format (processed)

.cub, JP2, PNG, GeoTIFF, OGR web services

Archiving URL (archive)

n/a

Preservation

University of Bern, to be continued by PSA/PDS

Acknowledgements

Prof. Nicolas Thomas, University of Bern, Dr. Gabriele Cremonese, INAF OaPD


OMEGA

Dataset reference and name

Observatoire pour la Minéralogie, l'Eau, les Glaces et l'Activité (OMEGA)

Organisation

Institut d’Astrophysique Spatiale, Orsay, France

Instrument Description

OMEGA is a mapping spectrometer, with co-aligned channels working in the 0.38-1.05 μm visible and near-IR range (VNIR channel) and in the 0.93-5.1 μm short wavelength IR range (SWIR channel) in 352 contiguous spectral elements (spectels). The signal-to-noise ratio(SNR) is >100 over the whole spectral range for observations obtained in nadir mode and considering low solar zenith angles. Due to the MEx spacecraft elliptic orbit, the scan widths in each orbit are changed (16, 32, 64, 128 pixels) accordingly to the variation of the observing distance. The spatial resolution of OMEGA is in the range 0.3-4-5 km/pixel . The SWIR detector (covering the 1-2.5 µm diagnostic wavelength range) is not functioning any more since 2010.

Dataset Description

The data products constitute three-dimensional ‘image-cubes’, with two spatial and one spectral dimensions. OMEGA provides global coverage at medium-resolution (2-5 km) for altitudes from 1500 km to 4000 km, and high-resolution (< 350 m) spectral images of selected areas, amounting to a few percent of the surface, when observed from near-periapsis (< 300 km altitude).

Standards

PDS3

Spatial Extent and Resolution

Images can vary between 16, 32, 64, 128 pixels of swath depending on the distance. On the ground images are circa from 5-7 km X 3000 km (with 360m/px) up to 300-600 km X 3000 km (with 5km/px).

Spectral Range and Resolution

0.35-5.1um divided into three range: VNIR with a spectral sampling ranging from 7 nm between 0.38 and 1.05 um; SWIR-C with 14 nm between 0.93 and 2.73 um; and SWIR-L with 20 nm between 2.55–5.1 um.

Temporal Extent

Nominal Mission (19 Feb 2003 - 19 Jan 2006; cruise through orbit 2595)
Extended Mission 1 (22 Jan 2006 - 23 Oct 2007; orbits 2607-4890)
Extended Mission 2 (4 Nov 2007 - 3 Jan 2010; orbits 4931-7697)
Extended Mission 3 (4 Jan 2010 - 19 Oct 2012; orbits 7701-11193)
Extended Mission 4 (20 Oct 2012 - 11 Jan 2015)
Extended Mission 5 (14 Jan 2015 - 9 Jan 2017)
Extended Mission 6 (10 Jan 2017 - 3 Jun 2017)

Upstream contact (e.g. PDS)

ESA PSA - https://www.cosmos.esa.int/web/psa/contact-us

High level products

The OMEGA Mars Global Maps data products are primarily available in PDS format in the DATA directory of this data set. Raster maps are formatted using the PDS IMAGE object, and vector maps are formatted using the PDS SPREADSHEET object.

NIR Albedo Map

Ferric Oxide Map

Dust Map

Hydrated Mineral Map

Olivine Maps (3 maps)

Pyroxene Map

Data Format (raw)

The OMEGA files extensions are .QUB for the data (level 1B in the "cube" PDS format) and .NAV for the geometry.

Files are named from the corresponding OMEGA observation: ORBNNNN_S where NNNN is the orbit number (format I4.4) and S is the rank of the OMEGA observation on that orbit (starting with 0).

Data Format (processed)

for data: .sav, .txt

for images: .png, .tiff/.geotiff

Access URL (archive)

http://psa.esac.esa.int/pub/mirror/MARS-EXPRESS/OMEGA/

Preservation

Performed by ESA PSA

Acknowledgements

ESA planetary Science Archive, OMEGA PI Dr. Jean-Pierre Bibring, Institut d'Astrophysique Spatiale, Orsay, France


  SHARAD

Dataset reference and name

Shallow Subsurface Radar

Organisation

ASI, NASA

Instrument Description

The first hundred meters of the subsurface are investigated with a vertical resolution of about 20 metres, horizontal at about one hundred metres in trajectory, while perpendicularly the resolution is in the order of a kilometre depending on subsurface characteristics and local surfaces. The radar instrument points to the nadir with functioning and impulses on two modalities of radar and altimeter. In order to isolate, the reflectors of the subsurface use the synthetic aperture technique. The instrument consists of an antenna and an electronic system working at a wavelength range centred at MHz +/- 5 MHz This configuration enables the analysis of dielectric properties in the subsurface, thereby maintaining low clutter at the surface. The frequencies selected can penetrate the ionosphere. The total cycle of transmission and reception of each impulse is a few milliseconds

Dataset Description

Raw Data Products - EDR (SHARAD Operations, Italy)

mro-m-sharad-3-edr-v1


The Shallow Radar (SHARAD) Experiment Data Record (EDR) for SHARAD is a data product produced by the Italian SHARAD team that consists of the instrument telemetry correlated with the auxiliary information needed to locate observations in space and time and to process data further.  Apart from editing of data to remove duplicates and transmission errors, no processing is applied to the scientific data of the instrument.


Each Data Product contains data from one or more data blocks collected continuously using the same operation mode, instrument status and on-board processing scheme; that is, using a single Operation Sequence Table (OST) line.  The content of each SHARAD data product is highly variable in terms of number of data blocks, and depends on how operations for the instrument were planned during a given data collection period.  The natural organization for data blocks within a Data Product is a table, in which each line contains data from a single data block, and each column contains the value of a single parameter or time sample across different data blocks.


Each Data Product consists of three files:


1) A binary file containing the scientific telemetry of the instrument.  This is a sequence of echoes, each of which is preceded by a header containing information on the collection and on-board processing of the data.  This file is called the Science Telemetry file.

2) A binary table containing geometric quantities generated on-ground from spacecraft navigation data, parameters extracted from instrument and spacecraft housekeeping telemetry, and flags describing the completeness and usability of the associated scientific telemetry.  This file is called the Auxiliary Data file and contains one record for every data block in the Science Telemetry file.

3) A detached ASCII label file describing the content of the data product.  The label is written according to standards defined by the Planetary Data System (PDS), and lists parameters describing both the observation in which data were acquired and the structure of the files in which data are stored.



Dataset Description

Derived Data Products - RDR (SHARAD Operations, Italy)

mro-m-sharad-4-rdr-v1


The Shallow Radar (SHARAD) Reduced Data Record (RDR) for SHARAD is a data product produced by the Italian SHARAD team that consists of received echoes that have been Doppler filtered, range compressed, and converted to complex voltages, correlated with the auxiliary information needed to locate observations in space and time and to process data further.  Data users must be aware that processed echoes may contain artifacts due to off-nadir surface reflections, the so-called clutter, reaching the radar after nadir surface echoes, and thus appearing as subsurface reflections.


Each Data Product is the result of the processing of all echoes acquired continuously in time using the same operation mode, instrument status and on-board processing scheme.  There is one RDR data product for every Experiment Data Record (EDR) data product acquired in subsurface sounding mode, which in fact constitutes the input for the RDR product generation.  Each processed radar observation in an RDR data product is the result of range and azimuth processing of a variable number of raw echoes.  The natural organization for processed echoes within a Data Product is a table, in which each line contains data from a single processed echo, and each column contains the value of a single parameter or time sample across different processed echoes.


Each Data Product consists of two files:

1) A binary file containing the scientific data of the instrument:  a sequence of processed echoes, each of which is preceded by a header containing information on the instrument setting and on-board processing of the data, and followed by parameters characterizing the ground processing of the echoes, by geometric quantities generated on-ground from spacecraft navigation data, and by parameters extracted from instrument housekeeping telemetry.

2) A detached ASCII PDS label file describing the content of the data product.

Dataset Description

Derived Data Products (Radargrams) (SHARAD Science Team, U.S.)

mro-m-sharad-5-radargram-v1


The Shallow Radar (SHARAD) Reduced Data Record of Radar backscatter power (USRDR) is a data product produced by the U.S. SHARAD team.  The image product, the radargram, is a backscatter power presented with along-track distance in the horizontal dimension and round-trip time delay along the vertical axis.


The U.S. radargram processing uses a uniform amplitude model for the frequency components of the SHARAD linear frequency-modulated chirp signal.  This leads to asymmetric offset of the characteristic transform sidelobes, with greater sidelobe amplitude on the downrange (greater delay) side of any echo.  This approach preserves a two-fold oversampling (i.e., 3600 complex samples from 3600 real samples) of the signal after range compression, which allows for flexibility in later interpolation.  Ionospheric distortion is compensated using a model for the frequency dependence of the phase errors.  The resulting correction term is approximately linear with total electron content (TEC), and thus with the change in delay time for signals from the surface and subsurface.  The image-restoring and range corrections are applied where the solar zenith angle (SZA) is less than 100°.  A Hann window function is applied to the frequency-domain data prior to the inverse Fourier transform to reduce sidelobe levels in the range-compressed echo.


Two basic parameters define the processing of SHARAD data.  The first is the coherence time or aperture length, TC (in seconds).  The frequency resolution (in Hz) of the resulting Doppler spectrum is 1/TC, independent of the time spacing between the pulses that make up the synthetic aperture.  The degree of pre-summing, which reduces the pulse repetition frequency (PRF) from the initial value of 700.28 pulses per second, affects only the Doppler frequency bandwidth (in Hz) of the Doppler spectrum, which is given by 1/PRF.  The second parameter specifies the Doppler frequency bandwidth (in Hz), B, of echoes about the centre of the Doppler spectrum to be included in the radar backscatter mapping.  If this frequency width is less than 1/TC, the output map will have only one sample for each output pixel location.  This is a one-look radar image.  If the frequency width is larger than 1/TC, more than one Doppler resolution cell will be averaged, yielding a multi-look image.


Each 32-bit floating-point format radargram file is accompanied by a TIFF image that logarithmically scales the backscattered power over an 8-bit range corresponding to -3 dB to +32 dB with respect to the noise background (i.e., each DN step is about 0.137 dB).  The noise-scaling factor was determined from the average behaviour over the period between orbits 7500 and 32999.  Tracks collected before about orbit 7200 have a slightly higher (about 1.4 dB) background noise, so their TIFF radargram products will appear slightly brighter due to the use of the lower scaling factor.  A reduced-quality JPEG version of each TIFF is provided for browsing the archive.

The Shallow Radar (SHARAD) Geographic, geometric, and ionospheric properties (USGEOM) data file accompanies each U.S. Reduced Data Record of Radar backscatter power (USRDR).  The ASCII-format table file contains location information for each radargram column, the spacecraft and surface radius values required to change the reference planetary shape, and the phase correction value related to the correction of ionospheric distortion and delay.  The coordinate system of planetocentric, with longitude positive toward the east.  Radius values tabulated in the GEOM files are interpolated using a polynomial fit between the along-track elapsed time and data from Mars Orbiter Laser Altimeter (MOLA).  The topographic information for the polynomial fit is drawn from the MOLA 128-ppd (pixels per degree) areoid gridded database for non-polar tracks, and from the 512-ppd gridded dataset for tracks that cross the polar terrain.

Standards

PDS3

Spatial Resolution

Vertical resolution 20 m

Spatial Extent

linear, along track.

Spectral Range

none

Temporal Extent

2006-present

Upstream contact (e.g. PDS)

NASA PDS- https://pds.nasa.gov

Data Format (raw)

.dat, .lbl

Data Format (processed)

.img, .lbl, .tab

Access URL (archive)

http://pds-geosciences.wustl.edu/mro/

Preservation

Performed by NASA, PDS

Acknowledgements

ASI, NASA, Principal Investigator Dr. Roberto Seu of the INFOCOM Department of the Università “La Sapienza” of Rome.



CRISM

Dataset reference and name

 Compact Reconnaissance Imaging Spectrometer for Mars (CRISM)

Organisation

NASA - The Johns Hopkins University/Applied Physics Lab

Instrument Description

CRISM is a hyperspectral imager covering wavelengths from 0.36 to 3.92 microns. The SNR is .... The MRO will operate from a sun-synchronous, near- circular (255x320 km altitude), near-polar orbit with a mean local solar time of 3 PM. ...

https://pds.nasa.gov/ds-view/pds/viewInstrumentProfile.jsp?INSTRUMENT_ID=CRISM&INSTRUMENT_HOST_ID=MRO

Dataset Description

The data products consist in image cubes. In targeted mode (Gimbaled, Hyperspectral Modes), CRISM acquires hyperspectral images from circa 0.4 to 4.0 mm in 544 channels (VNIR 107+ IR 438) at a spatial resolution up to 18 meters per pixel; whereas in global mode (pushbroom modes) images have different spectral sampling in the VNIR (from 19 to 107 channel) and IR (from 0 to 438 channel) with spatial resolution between 100-200 m .

This datasets are defined as:

1) Gimbaled: Full Resolution (FRT); Half resolution short (HRS); Half resolution long (HRL); Full resolution short (FRS); Along-track oversampled (ATO); Along-track undersampled (ATU)

2) Pushbroom: Multispectral Window (MSW); Multispectral VNIR (MSV); Multispectral Survey (MSP); Hyperspectral Mapping (HSP); Hypersepctral VNIR (HSV); Tracking Optical Depth (TOD); Flat Field Calibration (FFC)

Standards

PDS3

Spatial Extent and Resolution

Full Resolution (FRT): Spatial pixels unbinned for target – 18 m/pixel @ 300 km,  

Half resolution short (HRS): Spatial pixels 2x binned for target – 36 m/pixel @ 300 km, same swath length as above

Half resolution long (HRL): Spatial pixels 2x binned for target – 36 m/pixel @ 300 km, twice swath length as above

Full resolution short (FRS): Spatial pixels unbinned for target – 18 m/pixel @ 300 km; half swath length as above

Along-track oversampled (ATO): Spatial pixels unbinned for target – 18 m/pixel cross-track, up to ~3 m/pixel downtrack, requires special processing for increased resolution; half swath length as above

Along-track undersampled (ATU): Spatial pixels unbinned for target – 18 m/pixel cross-track, 36 m/pixel downtrack; half swath length as above

Spectral Range and Resolution

0.36 to 3.92 microns at 6.55 nanometers/channel

Temporal Extent

2007-present

EDR / CDR Volume Coverage
MROCR_0001 Sept. 27, 2006 - Dec. 31, 2007
MROCR_0002 Jan. 1, 2008 - Aug. 8, 2008
MROCR_0003 Aug. 9, 2008 - Aug. 8, 2010
MROCR_0004 Aug. 9, 2010 - Aug. 8, 2011
MROCR_0005 Aug. 11, 2011 - Aug. 3, 2012
MROCR_0006 Sept. 14, 2012 - Aug. 8, 2013
MROCR_0007 Aug. 9, 2013 - Aug. 8, 2014
MROCR_0008 Aug. 9, 2014 - Nov. 8, 2015
MROCR_0009 Nov. 9, 2015 - Nov. 8, 2016
MROCR_0010 Nov. 9, 2016 - Nov. 8, 2017
MROCR_0011 Nov. 9, 2017 - Feb. 8, 2018

Upstream contact (e.g. PDS)

NASA PDS- https://pds.nasa.gov

http://crism.jhuapl.edu

High level products

......................

Data Format (raw) and derived

Crism file extensions are:

Experiment Data Record (EDR) Raw data from the telemetry stream rearranged but unmodified except for lossless decompression.

Calibration Data Record (CDR) Derived values needed to convert a scene-viewing EDR into units of radiance.

Whereas derived CRISM files are:

Derived Data Record (DDR) A companion file for each EDR or TRDR pointed at Mars's surface that contains physical parameters such as latitude, longitude, and incidence, emission, and phase angle. Used for map projection, photometric correction, and to locate correction information in an ADR.

Limb Data Record (LDR) A companion file for each EDR or TRDR pointed at Mars's limb that contains physical parameters such as latitude, longitude, and incidence, emission, and phase angle. Used to locate measurement tangent relative to the surface and model the radiance.

Targeted Reduced Data Record (TRDR) Image data from an EDR converted to units of radiance or I/F using CDRs. A TRDR also contains a set of derived spectral parameters (summary products) that provide an overview of the data set.

Ancillary Data Record (ADR) Reference information used to correct scene measurements for photometric, thermal emission, or atmospheric effects.

Multispectral Reduced Data Record (MRDR) One of many tiles that make up a global mosaic, an MRDR contains map-projected data in units of radiance (extracted from TRDRs), plus I/F, summary products, and the DDR data used to generate them.

Targeted Empirical Record (TER) A spatially reconciled, full spectral range I/F targeted observation central scan image cube in the IR (L-detector) sensor space that has been corrected for geometric, photometric, atmospheric, and instrumental effects.

Map-Projected Targeted Reduced Data Record (MTRDR) Similar in concept to an MRDR, MTRDRs are map-projected versions of TER data products.

Data Format (processed)

for data: .sav, .txt

for images: .png, .tiff/.geotiff

Access URL (archive)

http://pds-geosciences.wustl.edu/mro/

Preservation

Performed by NASA, PDS

Acknowledgements

CRISM Principal Investigator: Scott Murchie, The Johns Hopkins University/Applied Physics Lab

MARSIS

Dataset reference and name and acronym

Mars Advanced Radar for Subsurface and Ionosphere Sounding

Organisation

Università La Sapienza, Roma

Instrument description

The primary objective is to map the distribution of water and ice in the upper portions of the Martian crust. The instrument analyzes reflections of radio waves in the upper 2-3 km of Martian crust to reveal the subsurface structure. MARSIS also studies the ionosphere by characterizing the interaction of the solar wind with the ionosphere and upper atmosphere of Mars.

Dataset Description

Nominal Mission

MEX-M-MARSIS-2-EDR-V2.0


Nominal Mission

MEX-M-MARSIS-2-EDR-EXT1-V2.0


For more information about the dataset

http://pds-geosciences.wustl.edu/mex/mex-m-marsis-2-edr-v2/mexme_1001/catalog/dataset.cat

Standards

PDS3

Spatial extent

2-3 km in depth

Spectral Range

none

Temporal extent

2003-present

Labeling


Archive contact (e.g. PDS)

http://pds-geosciences.wustl.edu/mex/

Data format (raw)

.dat, .lbl

Data format (processed)


Archiving URL (archive)

http://pds-geosciences.wustl.edu/mex/

Preservation

NASA-PDS

Acknowledgements

MARSIS Principal Investigator: Roberto Orosei, MARSIS Principal Investigator from Istituto di Astrofisica e Planetologia Spaziali, Bologna, Italy.

Formerly Prof. Giovanni Picardi, Universita di Roma 'La Sapienza', Rome, Italy.



Moon

See here for labels and format etc.: 

http://ode.rsl.wustl.edu/moon/pagehelp/quickstartguide/index.html?lroc_mdrwvs.htm

LROC NAC (Chin et al., 2007; Robinson et al., 2010)

Dataset reference and name and acronym

LROC NAC

Organisation

NASA PDS

Instrument description

The Lunar Reconnaissance Orbiter Camera (LROC) has been designed to address two of the measurement requirements:

• Landing site certification

• Polar illumination

LROC acquires images to assess meter and smaller scale features to facilitate safety analysis for potential lunar landing sites near polar resources and elsewhere on the Moon. Synoptic 100 m/pixel imaging of the poles during every orbit for a year will unambiguously identify regions of permanent shadow and permanent or near-permanent illumination.

Dataset Description

The Lunar Reconnaissance Orbiter Camera (LROC) Experiment Data Record Narrow Angle Camera (EDRNAC) data product is a NAC panchromatic image corresponding to a single observation (either full resolution or summed), with Digital Number (DN) counts in 8-bit format, companded from 12-bit in the instrument.  The image data consists of one series of contiguous lines up to 52,224 lines with 5,000 samples in full resolution mode, or 104,448 lines with 5,000 samples in 2x cross-track summation mode.


The image file is composed first of the even pixels from each line (with a 20 byte CTX heritage header every 1 MB) and padded to a 1 MB boundary, followed by the odd pixels in the same style.  The EDR file generation process extracts the odd and even pixels, interleaving them to reconstruct original scan lines.  If compression was enabled at image acquisition, the data stream is first de-compressed before the interleaving is performed.  Information from the meta-file, housekeeping, and the SOC database are combined to generate the PDS label with the binary data to compose the EDR file.


Specifications for the right and left NACs are in the table below.  The NAC-L is off-pointed ~2.85° from the NAC-R so that the footprints of the two images overlap ~130 pixels.

Standards

PDS3

Spatial extent

0.5 m/pixel scale panchromatic images over a 5 km swath and a wide-angle camera component (WAC) to provide images at a scale of 75 m/pixel in five visible bandpasses and 400 m/pixel (source LROC RDR SIS)

Spectral Range


Temporal extent


Archive contact (e.g. PDS)

http://pds-geosciences.wustl.edu/contact/default.htm

Data format (raw)

.IMG

Data format (processed)

JP2, PNG, GeoTIFF, OGR web services

Archiving URL (archive)

http://pds-geosciences.wustl.edu/lro/

Preservation

performed by NASA PDS

Acknowledgements

tba



M3  (Pieters et al., 2009)

Dataset reference and name and acronym

Moon Mineralogy Mapper

Organisation

NASA/ISRO

Instrument description

M3 is a broad spectral range imaging spectrometer, measuring from 430 to 3000 nm with 10 nm spectral sampling (### channels), with one detector, through a 24 degree field of view with 0.7 milliradian spatial sampling. It was designed to measure compositionally diagnostic spectral absorption features from a wide variety of known and possible lunar materials. The instrument's SNR was greater than 400 for the specified equatorial reference radiance and greater than 100 for the polar reference radiance. Chandrayaan1 had a nominal 100 km inertially fixed polar orbit, but from the 19th of May 2009, for mission safety, the orbit of Chandrayaan1 was raised from 100 km to 200 km.

Dataset Description

Dataset was defined with two instrument measurement modes, defined as “Target Mode” and "Global Mode". Target Mode is characterized by a full resolution with 260 spectral detector elements for every along‐track sample with a nominal spatial sampling of 70 m. Global Mode was defined to collect rapid full lunar coverage at reduced spatial (140 m/pixel) and spectral sampling (86 spectral channels). 825 nominally illuminated Global Mode and 79 Target Mode images were acquired. 336 contiguous Global Mode images strips provide nearly full coverage of the lunar surface. The acquired M3 measurements provide 95%complete Global Mode coverage of the Moon.

Standards

PDS3

Spatial extent and Resolution

40 km swath and 70 m spatial sampling from the nominal 100 km orbit

Spectral Range and Resolution

430 to 3000 nm with 10 nm of spectral sampling

Temporal extent

OP1A   Nov  18 2018  -­‐  Jan  24 2019   119   100  km  extended commissioning  
OP1B     Jan  25  -­‐  Feb  14   247   100  km   operational,  high  solar  zenith  angles  
OP2A   Apr  15  -­‐  Apr  27   197   100  km   operational,  high  solar  zenith  angles  
OP2B   May  13    -­‐  May  16   20   100  km S/C  emergency,  orbit  raised  
OP2C   May  20  -­‐  Aug  16   375   200  km   operational,  variable  conditions

Archive contact (e.g. PDS)

http://pds-geosciences.wustl.edu/contact/default.htm

Data format (raw)

.IMG

Data format (processed)

for data: .sav, .txt

for images: JP2, PNG, GeoTIFF, OGR web services

Archiving URL (archive)


Preservation

performed by NASA PDS

Acknowledgements

tba



SELENE (Kaguya) Terrain Camera 

Dataset reference and name and acronym


Organisation


Instrument description


Dataset Description


Standards

PDS3

Spatial extent


Spectral Range


Temporal extent


Archive contact (e.g. PDS)


Data format (raw)


Data format (processed)


Archiving URL (archive)


Preservation

performed by JAXA

Acknowledgements

tba


Mercury

MDIS-NAC/WAC (Hawkins, S.E. III et al., 2007, Space Sci. Rev.)

Dataset reference and name and acronym

MDIS - MESSENGER Mercury Dual Imaging System

Organisation

NASA/Johns Hopkins University Applied Physics Laboratory

Instrument description

MDIS consists of a monochrome narrow-angle camera (NAC) and a multispectral wide-angle camera (WAC). The NAC has a single medium-band filter centered at 747.7 nm to match to the corresponding WAC filter for monochrome imaging. The WAC has a 12-position filter wheel (FW) provides color imaging over the spectral range of the CCD detector. Eleven spectral filters spanning the range 395-1,040 nm are defined to cover wavelengths diagnostic of different potential surface materials. The WAC's 10.5° x 10.5° FOV is sufficient that overlap occurs between nadir-pointed image strips taken on adjacent orbits, even at northern mid-latitudes where low altitudes occur. The NAC's 1.5° FOV is sufficiently narrow that 375 m/pixel sampling is attained at 15,000 km altitude. MESSENGER was placed in a highly eccentric orbit with a periapsis altitude of 200 km, a periapsis latitude of ~60° and an apoapsis altitude of 15,200 km. The orbit has a 12-hour period, is inclined 80° to the planet's equatorial plane, and is not Sun synchronous.

Dataset Description

MDIS dataset consists of single wavelength images at variable scales and with variable filters combination. They provided global coverage on B/W, three colors, five colors or eight colors of Mercury surfaces. Targeted region can be characterized by very high spatial resolution from few tens of meters for NAC filter up to few hundred of meters for 8 color image.

Standards

PDS3

Spatial Extent and Resolution

NAC: ~5 m/px at 200-km altitude, 380 m/px at 15,200-km altitude

WAC: ~ 36 m/px at 200-km altitude, 2720 m/px at 15,200-km altitude

Spectral Range and resolution

NAC: single medium-band filter (721–770 nm) centered at 747.7 nm, WAC: 395–1040 nm in 12 filters

Filter number

Filter letter

System wavelength

measured at -26°C (nm)

System bandwidth

measured at -26°C (nm)

6

F

430

18.0

3

C

480.4

8.9

4

D

559.2

4.6

5

E

628.8

4.4

1

A

698.8

4.4

2

B

700

600

7

G

749.0

4.5

12

L

828.6

4.1

10

J

898.1

4.3

8

H

948.0

4.9

9

I

996.8

12.0

11

K

1010

20.0

NAC

M

747.7

52.3


Temporal extent

Mercury flyby 1 → 14 January 2008

Mercury flyby 2 → 6 October 2008

Mercury flyby 3 → 29 September 2009

Orbital phase → March 2011 - April 2015

Archive contact (e.g. PDS)

PDS

High Level Products

Mercury Messenger Global Mosaic 2010

This mosaic represents the best geodetic map of Mercury's surface as of 2010.
https://astrogeology.usgs.gov/search/map/Mercury/Messenger/Global/Mercury_M1_M2_M3_M10_mosaic_global_2010

Mercury MESSENGER MDIS Basemap Enhanced Color Global Mosaic 665m (64ppd)

This view uses a global mosaic with 430, 750, and 1000 nm bands and places the second principal component, the first principal component, and the 430/1000 ratio in the red, green, and blue channels respectively.

https://astrogeology.usgs.gov/search/map/Mercury/Messenger/Global/Mercury_MESSENGER_MDIS_Basemap_EnhancedColor_Mosaic_Global_665m

Mercury MESSENGER MDIS Global Basemap BDR 166m (256ppd)

The Map Projected Basemap RDR (BDR) data set consists of a global monochrome map of reflectance at a resolution of 256 pixels per degree (~166 m/px). 

https://astrogeology.usgs.gov/search/map/Mercury/Messenger/Global/Mercury_MESSENGER_MDIS_Basemap_BDR_Mosaic_Global_166m

Mercury MESSENGER MDIS Basemap MD3 Color Global Mosaic 665m (64ppd)

The mosaic shows Mercury's colors as viewed by placing images from MESSENGER's 1000 nm, 750 nm, and 430 nm narrow-band filters in the red, green, and blue channel respectively.

https://astrogeology.usgs.gov/search/map/Mercury/Messenger/Global/Mercury_MESSENGER_MDIS_Basemap_MD3Color_Mosaic_Global_665m

Mercury MESSENGER MDIS Basemap LOI Global Mosaic 166m (256ppd)

The Map Projected Low-Incidence Angle Basemap RDR (LOI) data set consists of a global monochrome map of reflectance at a resolution of 256 pixels per degree (~166 m/px).

https://astrogeology.usgs.gov/search/map/Mercury/Messenger/Global/Mercury_MESSENGER_MDIS_Basemap_LOI_Mosaic_Global_166m

Mercury MESSENGER MDIS Color Global Mosaic 665m v3

The color mosaic is comprised of photometrically corrected I/F (radiance factor) for 3 narrow-band color filters of the Mercury Dual Imaging System (MDIS) Wide Angle Camera (WAC), placing the 1000-nm, 750-nm, and 430-nm filters in the red, green, and blue channels, respectively.

https://astrogeology.usgs.gov/search/map/Mercury/Messenger/Global/Mercury_MESSENGER_MDIS_ClrMosaic_global_665m_v3

Mercury MESSENGER Global DEM 665m (64ppd) v2 Oct. 2016

The map is a colorized shaded-relief of the original digital elevation model (DEM)

https://astrogeology.usgs.gov/search/map/Mercury/Topography/MESSENGER/Mercury_Messenger_USGS_DEM_Global_665m

Mercury MESSENGER Global Colorized Shade 2km

Global DEM of Mercury from a least-squares bundle adjustment (jigsaw in ISIS3 [Becker 2016]) of common features, measured as tie point coordinates in overlapping NAC and WAC-G filter images. 

https://astrogeology.usgs.gov/search/map/Mercury/Topography/MESSENGER/Mercury_Messenger_USGS_ClrShade_Global_2km

MESSENGER Global Mosaic

8-color (MDR) 64 ppd (all backplanes)

5-color (MP5) 128 ppd (all backplanes)

3-color (MP3) 128 ppd (all backplanes)

Moderate incidence angle (BDR) 256 ppd (image plane only), 43 ppd (all backplanes)

Low incidence angle (LOI) 256 ppd (image plane only), 43 ppd (all backplanes)

East illumination (HIE) 256 ppd (image plane only), 43 ppd (all backplanes)

West illumination (HIW) 256 ppd (image plane only), 43 ppd (all backplanes)

http://messenger.jhuapl.edu/Explore/Images.html#global-mosaics

Data format (raw)

MDIS file extensions are:

Experiment Data Record (EDR)

Calibrated Data Record (CDR)

Derived Data Record (DDR)

Map Projected Multispectral RDR (MDR)

and the raw format is:

.IMG

Data format (processed)

For images: .jpg, .PNG, For data: .GeoTiff, .cub, .dat

Archiving URL (archive)

https://pds-imaging.jpl.nasa.gov/volumes/mess.html

http://ode.rsl.wustl.edu/mercury/index.aspx

https://pds-imaging.jpl.nasa.gov/search/index.html?ATLAS_MISSION_NAME:messenger

Preservation

Performed by NASA PDS

Acknowledgements

tba


Mapping products - Standard

Standard mapping products refer to existing USGS documentation (See D2.1 + USGS guidelines, and references therein), see also van Gasselt and Nass (2011).

Feature representation in GIS environment

To promote consistent representation across GIS software packages, the styling of GIS vector data will be provided in an open format. SLD standard, which stands for Styled Layer Descriptor, is an XML scheme whose specifications are published by the Open Geospatial Consortium, and thus it constitutes the best practice in terms of open standards.

http://www.onegeology.org/wmsCookbook/7_4_5.html provides useful information about the creation of SLD files for geological maps. SLD files can then be easily used in most server side applications for serving maps over the internet.

Mapping products - non-Standard

Compositional basemaps

Compositional basemaps (see D4.2-public) are specific data depending on the target body. Those used for RGB display of different spectral index products are exemplified in Table 2 and are used as basemaps for the production of geological maps integrated with spectral and compositional information.


Index Name

Parameter

Channel

Formulation

Rationale on Mercury

R750

Reflectance at 750 nm (Fig. 1)

MDIS-WAC

R750 nm

Reflectance variations. High values →  bright fresh material, pyroclastic deposits, northern smooth plains. Low values →  dark terrain. Intermediate  values →  intercrater and intermediate plains.

RGB “False Color Mosaic”

R: R996 nm,

G: R750nm,

B: R430 nm

(Fig. 2)

MDIS-WAC

R: R996 nm, G: R750nm, B: R430 nm

Color variations. Red → reflectance at longer wavelength. Green → reflectance at intermediate  wavelength. Blue → reflectance at shorter wavelength.

PC1

PCA first channel (Fig. 3)

MDIS-WAC

PC1

reflectance variation. High values →  brigth fresh material, pyroclastic deposits, northern smooth plains. Low values →  dark terrain. Intermediate  values →  intercrater and intermediate plains.

PC2

PCA second channel (Fig. 4)

MDIS-WAC

PC2

Spectral variabilities not due to reflectance. High values: → pyroclastic deposits, northern smooth plains. Low values → dark material, smooth plains (western area), Intercrater plains and intermediate plains (western area).

RGB “Enhanced Color Mosaic”

R: PC2,

G: PC1,

B: 430/996nm  

(Fig. 5)

MDIS-WAC

R: PC2, G: PC1, B: 430/996nm

Identification of the main terrain units. Orange region → pyroclastic deposits, northern smooth plains, volcanic material. Light blue: crater rays, ejecta, fresh material. Dark blue → dark and very dark material.

RGB “Clementine-like Color Mosaic“

R: R748 nm/R430 nm, G: R748 nm/R828 nm, B: R430 nm/R748 nm (Fig. 6)

MDIS-WAC

R: R748 nm/R430 nm, G: R748 nm/R828 nm, B: R430 nm/R748 nm

Maturity, mafic or glassic components, secondary elements locally concentrated. Yellow →  high-reflectance material and blue areas indicate low-reflectance material and crater rays. Green →  higher intermediate slope. Red → steeper visible slopes relative to bluer areas. Orange/red → steepest visible slopes.

S430_996

Spectral slope between 430 and 996 nm (Fig. 7)

MDIS-WAC

(R996−R430)/((996−430)R433)

Maturity, compositional variation, grain size. Low values → fresh terrains, dark terrain. High values → older terrains,   volcanic  materials, space weathering.

S430_558

Spectral slope between 430 and 558 nm (Fig. 8)

MDIS-WAC

(R558−R430)/((558−430)R430)

Opaque mineralogical phases. Low values → possible presence or opaque phases. High values → pyroclastic deposits and northern smooth plains.

S748_996

Spectral slope between 748 and 996 nm (Fig. 9)

MDIS-WAC

(R996−R748)/((996−748)R748)

1 µm band absorption. Low values → possible absorption at 1µm

RGB “Spectral Slopes”

R: S430_996,

G: S748_996,

B: S430_996  

(Fig. 10)

MDIS-WAC

R: S430_996, G: S748_996, B: S430_996

Spectral slope variations.

Table 2. Summary of delivered spectral indices for the Hokusai Quadrangle.


3D geomodels

Three dimensional geological models provides a numerical representation of geological elements within a volume of interest. This is normally accomplished by following a BRep (Boundary Representation) strategy. Sub-volumes of the model are defined by boundary surfaces, while surfaces are in turn bounded by lines and lines by end points. Geological planar elements that are modeled (i.e. faults, fractures and units contacts) are used to define the boundaries of sub-volumes within the region in which the modeling is made. Volumetric elements, as e.g. the hanging wall block of a fault or a sedimentary body comprises in between two surfaces can thus be completely defined by specifying the specific role of one or more surfaces.

The numerical representation of three dimensional surfaces can be straightforwardly achieved by storing a list of vertices, faces and edges (see e.g. https://en.wikipedia.org/wiki/Polygon_mesh#Representations). When it comes to geological models the relationship occurring between different surfaces must indeed be specified in an explicit way by grouping one or more surfaces in a geologically meaningful object (e.g. a horizon, a fault, an unconformity). This kind of representation requires dedicated software and formats. Although there have been recent efforts (see Pellerin, 2017, which also constitutes a good introduction to the numerical representation of geological models) to create an unified library for the definition of 3d geological elements, there is still no widely-accepted representation standard, which must be evaluated case by case, depending on the specific needs. The following table illustrates the expected outputs of 3D geological modeling software and its usage depending on the context. Each row (namely native/exchange/pure3d) represents a decreasing level of complexity and completeness of a 3D geological model as it is reduced to different numerical representations.

Product completeness level

Definition

Main expected usage

Pro

Cons

native

gocad/3dmove/leapfrog (or any other 3D geomodeling software packages) in native formats (projects)

INTERNAL

Perfect during model development and short term preservation.

Bad for archiving, programmatic access and injection in other WPs, because it is strongly tied to the specific software

exchange

Formats maintaining specific geological information about the surfaces and volumetric meshes. E.g. RINGMesh-supported formats or any other geological-aware data exchange format that might be suitable for a specific software-to-software exchange task

INTERNAL/CROSS SOFTWARE SHARING/POSSIBLY LONG-TERM PRESERVATION

The format can be accessed by the software packages of interest and maintain most of the geological information.

The formats might still not be the perfect solution for long-term preservation. Commercial packages can drop the retro-compatibility with some formats.

pure3d

Pure mesh representation (e.g. triangular meshes) without any predefined way of storing the geological meaning of the surfaces/volumes.

LONG TERM ARCHIVING/PUBLIC and WPs SHARING/OUTREACH

DELIVERABLES

Perfect for long term preservation. Mainly ascii based formats and well-establishes IO libraries for accessing the files

These formats leave out information that is instead present in native and exchange level representations. Some of the information might be provided through metadata.


These different data representations are connected with a sort of data reduction pipeline going from high-to-low completeness. All the levels will be stored once generated although no level is mandatory. E.g. "native" level data can be transformed to "pure3d" level data for composing a deliverable without obtaining "exchange" level data. In the other hand "pure3d" level data might be directly generated for simple task where complex geomodeling software packages are not needed (via ad-hoc modeling strategies).


Complementary data and metadata

Geological constraints. Geological modeling software packages make use of constraints to build the geological model. These might be provided by either referring to the specific product (either PLANMAP's or external) that was used as source of constraints or by providing them as a separated dataset within the metadata of the 3D model. In most of the cases the first strategy will suffice although it is highly desirable to release also 3D constraints as a numerical dataset by disclosing to the public "native" level data format or by providing specific supplementary materials. This strategy is meant to increase reproducibility and peer-validation of results.

Metadata, that are especially important for deliverables, must concisely document the geological meaning of each (or groups of) 3D meshes that are provided, their creators and the dataset that were used for their production. In addition to this information three dimensional models will be provided with all the data that might be needed to correctly identify and localize the modeled region (ROI on map, projection system that has been used etc...).

Virtual reality products

There is currently no real standard in Virtual Reality (VR) in our field of research. VR is a domain that is evolving very quickly, after a major technological breakthrough which occurred in April 2016 when mature virtual reality headsets have been released to the public. The HTC Vive followed by the Oculus rift headsets (and the PSVR on Playstation) have been accessible at reasonable prices since the end of 2016. Low cost solutions have also appeared in parallel, based on smartphones (the google Cardboard, for example). Despite providing reduced comfort and possibilities of interaction with the virtual world, these low cost solutions significantly increased the final number of potential users, but also of possible formats. At the time of writing, several new technological devices are about to be released, some further improving the experience and introducing, for example, mid-range wireless solutions.

As a consequence, standards for the developers are also very quickly evolving in this new field of research. In the framework of PLANMAP, we will produce 3D models (either from surface or satellite images) on landing sites that will be handled in formats such as .obj (with the corresponding .jpg textures and .mtl files). All the integration and interaction tools will be developed with softwares such as Unity, which allow exports of executable files directly compatible with several VR systems. For simple models, new public exchange platforms are currently growing very fast, and could serve to provide a quick worldwide and long-term free access in virtual reality to some of the most relevant 3D models. Sketchfab (https://sketchfab.com/) is one of these relevant emerging platforms. The “destination” workshop in SteamVR could also be mentioned. The final choice of a repository for VR products will be made on a timely manner depending on which solution is gaining strength in the community in the coming months.   

Existing solutions using WebGIS are for the moment not directly compatible with VR, but the main actors in the field (such as ArcGIS from ESRI) are currently doing active research to implement this VR facility in future releases. It should therefore be interesting to follow these developments in parallel during the course of the Planmap project.   

Annex-B: File formats used and envisaged

File formats used for day-to-day activities and sharing, archiving might not be the same. PLANMAP envisages formats for both use and sharing, and archiving will be produced and these are indicated below. When relevant, appropriate PDS (PDS4) labels will be added to describe the data products, depending on actual arrangements with ESA on data delivery. Data shared via VESPA will not bear any PDS label and will contain metadata as needed for operating VESPA services and accessing and using data with commonly used geospatial software (e.g. GDAL/OGR-compatible).

Base formats depending on data type

Dataset type

Format

Common extensions

Products

Notes

Raster

GeoTiff with appropriate type and signedness (compressed or not)

.gtiff, .tif, .tiff

Imagery, possibly multi-band imagery and Digital Terrain Models


jpeg2000 (lossy or lossless)

.jp2 .jk2

Imagery for basemaps/mosaic for which higher compression rates is desirable


Portable network graphics

.png

Imagery for web publication and GIS, imagery intended only for visualization (i.e. grayscale/colour mosaics)


ASCII Gridded formats supported by gdal (arc/Info, GRASS, etc)

any [e.g. .txt, .grid, etc ]

alternative to geotiff for Digital Terrain Models

geotiff is still preferable (e.g. no round-off errors)

World (georeferencing) files

.twf, .pwf, .jwf (or similar)

Gereferencing information for raster dataset which is coupled with each raster file


Vectors

Geopackage (OGC)

Shapefile

.gpkg

.shp (.dbf, .shx , .sbn, .prj)

All mapping products in vector format



Geographical markups: JSON (GeoJSON)/XML (GML)

.json, .xml

Georeferenced products shareable on the web, WFS-served dataset



Relational DB (PostgreSql + PostGIS / SpatiaLite)

----

Dataset meant to be served by Web Feature Services [WFSs]

Internal use only


Styled Layer Descriptors

.xml

XML files describing the styles to be used when displaying vector layers


3D

Stanford Triangle Format, Wavefront OBJ, Stereolithography  and comparable

.ply, .obj, .stl

Three dimensional meshes. Geological meaning must be provided by metadata.

Neutral file formats must be preferred.

Might be equipped with texture files (i.e. for terrain with orthophoto)


VTK File Formats

.vtu, .vtp, .vtk

Commodity format for data exchange. Useful for products that require the preservation of scalar fields associated to triangles or vertices of the meshes and scientific analysis via VTK.



Geological Aware Formats

application-specific

3D geological models from 3D geomodeling software packages

Neutral file formats must be preferred

Hierarchical archives

Planteary Data System (v3,v4)

.pds, .img

Archived dataset with variable content


Other formats

Specific file formats might be used for either accessing mission-specific dataset or for use with specific software. These includes:

Flexible Image Transport System (FITS), Hierarchical Data Format (v4, v5), PDS label files (PDSv3 only), etc...


Annex-C: Data curation and preservation plans per partner

UNIPD 

Data produced will be stored and backed up locally when possible as well as shared with JacobsUni for archiving and web-gis integration. Documentation on data production and pipelines used will be shared via git-hub and wiki. Metadata will be interactively improved during review and shared with JacobsUni for eventual updates. Preservation on premise after the end of the project will be attempted based on financial, human and computing resources. UNIPD has an institutional repository that is going to be used within PLANMAP activities to share data and mapping products: https://researchdata.cab.unipd.it/.

OU

Data produced will be stored and backed up daily as part of the OU automatic backup system, as well as shared with JacobsUni for archiving and web-gis integration. Documentation on data production and pipelines used will be shared via git-hub and wiki. Metadata will be interactively improved during review and shared with JacobsUni for eventual updates. Preservation on premise after the end of the project will be attempted based on financial, human and computing resources. Open University has an Open Access data sharing facility (Open research Data Online) that data can be uploaded to and accessed by the public: https://ou.figshare.com/.

An example of Planetary GIS data shared in this way can be found here: https://figshare.com/articles/Mercury_Catenae_Global_Survey_-_Shapefile/5466535

WWU

Data produced are stored and backed up locally on institute servers, which are backed up on a weekly basis on a university system. Each ArcGIS project and accompanying data sets, figures, and publications are archived on personal external drives, institute/university servers, and institute external drives. Preservation on premises after the end of the project will be attempted based on financial, human and computing resources. Management and documentation of the data is simplified for each project via use of a standard file organizational structure, including folders for documentation relating to each individual project (e.g., projection files, image processing scripts), different kinds of data, and different kinds of data products (e.g., CSFD measurement files/plots, figures, maps). General documentation is available locally and will be added to the wiki. Maps, data, and results will be released as per PLANMAP guidelines, and will accompany peer-reviewed publications either within the main manuscript or as supplemental online material.

INAF

Data produced are stored and backed up locally on a server maintained by the institute. INAF developed its own data repository, with the capability of granting DOIs for each record ingested, for longer-term data preservation.

CNRS

Data produced are stored and backed up locally on a server maintained by the university. Data are backed up each 2-weeks using this system. Each mapping project and accompanying data sets, figures, and publications are also archived on personal external drives, institute/university servers, and institute external drives. Preservation on premises after the end of the project will be attempted based on financial, human and computing resources. General documentation is available locally and will be added to the wiki. Produced results will be released as per PLANMAP guidelines, and will accompany peer-reviewed publications either within the main manuscript or as supplemental online material.

JacobsUni

Data produced by JacobsUni will be stored during the project on premise as well as shared to all other partners via cloud and web mapping services, as well as backed up as much as possible given available computing resources. Documentation of data will be performed during the project using wiki and github. Metadata and documentation will be improved and - when detected - eventual mistakes corrected during the course of the project and reflected on saved data. Preservation on premise after the end of the project will be attempted based on financial, human and computing resources. Release of data via VESPA (distributed system), with possible duplication, for robustness, is planned. Release to ESA guest storage facility of data. Preservation of any other data or code/algorithm not performed via either VESPA or PSA, will be covered via release (see data citation section)  on GitHub/Zenodo.




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