Loading…

MAPPING OF PLANETARY SURFACE AGE BASED ON CRATER STATISTICS OBTAINED BY AN AUTOMATIC DETECTION ALGORITHM

The analysis of the impact crater size-frequency distribution (CSFD) is a well-established approach to the determination of the age of planetary surfaces. Classically, estimation of the CSFD is achieved by manual crater counting and size determination in spacecraft images, which, however, becomes ve...

Full description

Saved in:
Bibliographic Details
Published in:International archives of the photogrammetry, remote sensing and spatial information sciences. remote sensing and spatial information sciences., 2016-01, Vol.XLI-B4, p.479-486
Main Authors: Salih, A. L., Mühlbauer, M., Grumpe, A., Pasckert, J. H., Wöhler, C., Hiesinger, H.
Format: Article
Language:English
Subjects:
Citations: Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-a2896-ce2374a9c77f35c7ce4afce30f1e06a4e3da76ddc43b1b42a23b3991220b58273
cites
container_end_page 486
container_issue
container_start_page 479
container_title International archives of the photogrammetry, remote sensing and spatial information sciences.
container_volume XLI-B4
creator Salih, A. L.
Mühlbauer, M.
Grumpe, A.
Pasckert, J. H.
Wöhler, C.
Hiesinger, H.
description The analysis of the impact crater size-frequency distribution (CSFD) is a well-established approach to the determination of the age of planetary surfaces. Classically, estimation of the CSFD is achieved by manual crater counting and size determination in spacecraft images, which, however, becomes very time-consuming for large surface areas and/or high image resolution. With increasing availability of high-resolution (nearly) global image mosaics of planetary surfaces, a variety of automated methods for the detection of craters based on image data and/or topographic data have been developed. In this contribution a template-based crater detection algorithm is used which analyses image data acquired under known illumination conditions. Its results are used to establish the CSFD for the examined area, which is then used to estimate the absolute model age of the surface. The detection threshold of the automatic crater detection algorithm is calibrated based on a region with available manually determined CSFD such that the age inferred from the manual crater counts corresponds to the age inferred from the automatic crater detection results. With this detection threshold, the automatic crater detection algorithm can be applied to a much larger surface region around the calibration area. The proposed age estimation method is demonstrated for a Kaguya Terrain Camera image mosaic of 7.4 m per pixel resolution of the floor region of the lunar crater Tsiolkovsky, which consists of dark and flat mare basalt and has an area of nearly 10,000 km2. The region used for calibration, for which manual crater counts are available, has an area of 100 km2. In order to obtain a spatially resolved age map, CSFDs and surface ages are computed for overlapping quadratic regions of about 4.4 x 4.4 km2 size offset by a step width of 74 m. Our constructed surface age map of the floor of Tsiolkovsky shows age values of typically 3.2-3.3 Ga, while for small regions lower (down to 2.9 Ga) and higher (up to 3.6 Ga) age values can be observed. It is known that CSFD-derived absolute model ages can exhibit variations although the surface has a constant age. However, for four 10-20 km sized regions in the eastern part of the crater floor our map shows age values differing by several hundred Ma from the typical age of the crater floor, where the same regions are also discernible in Clementine UV/VIS color ratio image data probably due to compositional variations, such that the age differences of
doi_str_mv 10.5194/isprs-archives-XLI-B4-479-2016
format article
fullrecord <record><control><sourceid>proquest_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_d5418813af724cb9b500f04acd05ad8d</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><doaj_id>oai_doaj_org_article_d5418813af724cb9b500f04acd05ad8d</doaj_id><sourcerecordid>1986622270</sourcerecordid><originalsourceid>FETCH-LOGICAL-a2896-ce2374a9c77f35c7ce4afce30f1e06a4e3da76ddc43b1b42a23b3991220b58273</originalsourceid><addsrcrecordid>eNpNkVtr3DAQhU1poSHNfxAU-qZWN1_0UpAd70bgtRdbC82TkGW58ZLWWykp9N9XybYhTzPMOXNm4EuSTxh9TjFnX5Zw8gEab--W3y7Ab42EJYMs55AgnL1JLkh0QY4oe_uqf59chXBECGGWZSlKL5K7ndjvZbsF3QbsG9HWSvS3YDj0G1HVQGxrUIqhvgZdC6peqLoHgxJKDkpWA-hKJWQb1fIWiBaIg-p2UazAda3qSsm4JJpt10t1s_uQvJvNfXBX_-plctjUqrqBTbeVlWigIQXPoHWE5sxwm-czTW1uHTOzdRTN2KHMMEcnk2fTZBkd8ciIIXSknGNC0JgWJKeXiTznTqs56pNffhj_R69m0c-D1X_Xxj8s9t7pKWW4KDA1c06YHfmYIjQjZuyEUjMVU8z6eM46-fXXowsP-rg--p_xfY15kWWEkBxF19ezy_o1BO_ml6sY6SdY-hmW_g9LR1i6ZDrC0k-w6F-Dk4Qy</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1986622270</pqid></control><display><type>article</type><title>MAPPING OF PLANETARY SURFACE AGE BASED ON CRATER STATISTICS OBTAINED BY AN AUTOMATIC DETECTION ALGORITHM</title><source>Publicly Available Content Database</source><source>EZB Electronic Journals Library</source><creator>Salih, A. L. ; Mühlbauer, M. ; Grumpe, A. ; Pasckert, J. H. ; Wöhler, C. ; Hiesinger, H.</creator><creatorcontrib>Salih, A. L. ; Mühlbauer, M. ; Grumpe, A. ; Pasckert, J. H. ; Wöhler, C. ; Hiesinger, H.</creatorcontrib><description>The analysis of the impact crater size-frequency distribution (CSFD) is a well-established approach to the determination of the age of planetary surfaces. Classically, estimation of the CSFD is achieved by manual crater counting and size determination in spacecraft images, which, however, becomes very time-consuming for large surface areas and/or high image resolution. With increasing availability of high-resolution (nearly) global image mosaics of planetary surfaces, a variety of automated methods for the detection of craters based on image data and/or topographic data have been developed. In this contribution a template-based crater detection algorithm is used which analyses image data acquired under known illumination conditions. Its results are used to establish the CSFD for the examined area, which is then used to estimate the absolute model age of the surface. The detection threshold of the automatic crater detection algorithm is calibrated based on a region with available manually determined CSFD such that the age inferred from the manual crater counts corresponds to the age inferred from the automatic crater detection results. With this detection threshold, the automatic crater detection algorithm can be applied to a much larger surface region around the calibration area. The proposed age estimation method is demonstrated for a Kaguya Terrain Camera image mosaic of 7.4 m per pixel resolution of the floor region of the lunar crater Tsiolkovsky, which consists of dark and flat mare basalt and has an area of nearly 10,000 km2. The region used for calibration, for which manual crater counts are available, has an area of 100 km2. In order to obtain a spatially resolved age map, CSFDs and surface ages are computed for overlapping quadratic regions of about 4.4 x 4.4 km2 size offset by a step width of 74 m. Our constructed surface age map of the floor of Tsiolkovsky shows age values of typically 3.2-3.3 Ga, while for small regions lower (down to 2.9 Ga) and higher (up to 3.6 Ga) age values can be observed. It is known that CSFD-derived absolute model ages can exhibit variations although the surface has a constant age. However, for four 10-20 km sized regions in the eastern part of the crater floor our map shows age values differing by several hundred Ma from the typical age of the crater floor, where the same regions are also discernible in Clementine UV/VIS color ratio image data probably due to compositional variations, such that the age differences of these four regions may be real.</description><identifier>ISSN: 2194-9034</identifier><identifier>ISSN: 1682-1750</identifier><identifier>EISSN: 2194-9034</identifier><identifier>DOI: 10.5194/isprs-archives-XLI-B4-479-2016</identifier><language>eng</language><publisher>Gottingen: Copernicus GmbH</publisher><subject>Age ; Algorithms ; Area ; Automation ; Basalt ; Calibration ; Chronology ; Colour ; Counting ; Data ; Data acquisition ; Detection ; Frequency distribution ; Image acquisition ; Image detection ; Image resolution ; Impact analysis ; Lunar craters ; Mathematical models ; Mosaics ; Planet detection ; Planetary surfaces ; Regions ; Resolution ; Size determination ; Spacecraft ; Statistical methods ; Ultraviolet radiation</subject><ispartof>International archives of the photogrammetry, remote sensing and spatial information sciences., 2016-01, Vol.XLI-B4, p.479-486</ispartof><rights>Copyright Copernicus GmbH 2016</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a2896-ce2374a9c77f35c7ce4afce30f1e06a4e3da76ddc43b1b42a23b3991220b58273</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/1986622270?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>309,310,314,780,784,789,790,23930,23931,25140,25753,27924,27925,37012,44590</link.rule.ids></links><search><creatorcontrib>Salih, A. L.</creatorcontrib><creatorcontrib>Mühlbauer, M.</creatorcontrib><creatorcontrib>Grumpe, A.</creatorcontrib><creatorcontrib>Pasckert, J. H.</creatorcontrib><creatorcontrib>Wöhler, C.</creatorcontrib><creatorcontrib>Hiesinger, H.</creatorcontrib><title>MAPPING OF PLANETARY SURFACE AGE BASED ON CRATER STATISTICS OBTAINED BY AN AUTOMATIC DETECTION ALGORITHM</title><title>International archives of the photogrammetry, remote sensing and spatial information sciences.</title><description>The analysis of the impact crater size-frequency distribution (CSFD) is a well-established approach to the determination of the age of planetary surfaces. Classically, estimation of the CSFD is achieved by manual crater counting and size determination in spacecraft images, which, however, becomes very time-consuming for large surface areas and/or high image resolution. With increasing availability of high-resolution (nearly) global image mosaics of planetary surfaces, a variety of automated methods for the detection of craters based on image data and/or topographic data have been developed. In this contribution a template-based crater detection algorithm is used which analyses image data acquired under known illumination conditions. Its results are used to establish the CSFD for the examined area, which is then used to estimate the absolute model age of the surface. The detection threshold of the automatic crater detection algorithm is calibrated based on a region with available manually determined CSFD such that the age inferred from the manual crater counts corresponds to the age inferred from the automatic crater detection results. With this detection threshold, the automatic crater detection algorithm can be applied to a much larger surface region around the calibration area. The proposed age estimation method is demonstrated for a Kaguya Terrain Camera image mosaic of 7.4 m per pixel resolution of the floor region of the lunar crater Tsiolkovsky, which consists of dark and flat mare basalt and has an area of nearly 10,000 km2. The region used for calibration, for which manual crater counts are available, has an area of 100 km2. In order to obtain a spatially resolved age map, CSFDs and surface ages are computed for overlapping quadratic regions of about 4.4 x 4.4 km2 size offset by a step width of 74 m. Our constructed surface age map of the floor of Tsiolkovsky shows age values of typically 3.2-3.3 Ga, while for small regions lower (down to 2.9 Ga) and higher (up to 3.6 Ga) age values can be observed. It is known that CSFD-derived absolute model ages can exhibit variations although the surface has a constant age. However, for four 10-20 km sized regions in the eastern part of the crater floor our map shows age values differing by several hundred Ma from the typical age of the crater floor, where the same regions are also discernible in Clementine UV/VIS color ratio image data probably due to compositional variations, such that the age differences of these four regions may be real.</description><subject>Age</subject><subject>Algorithms</subject><subject>Area</subject><subject>Automation</subject><subject>Basalt</subject><subject>Calibration</subject><subject>Chronology</subject><subject>Colour</subject><subject>Counting</subject><subject>Data</subject><subject>Data acquisition</subject><subject>Detection</subject><subject>Frequency distribution</subject><subject>Image acquisition</subject><subject>Image detection</subject><subject>Image resolution</subject><subject>Impact analysis</subject><subject>Lunar craters</subject><subject>Mathematical models</subject><subject>Mosaics</subject><subject>Planet detection</subject><subject>Planetary surfaces</subject><subject>Regions</subject><subject>Resolution</subject><subject>Size determination</subject><subject>Spacecraft</subject><subject>Statistical methods</subject><subject>Ultraviolet radiation</subject><issn>2194-9034</issn><issn>1682-1750</issn><issn>2194-9034</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpNkVtr3DAQhU1poSHNfxAU-qZWN1_0UpAd70bgtRdbC82TkGW58ZLWWykp9N9XybYhTzPMOXNm4EuSTxh9TjFnX5Zw8gEab--W3y7Ab42EJYMs55AgnL1JLkh0QY4oe_uqf59chXBECGGWZSlKL5K7ndjvZbsF3QbsG9HWSvS3YDj0G1HVQGxrUIqhvgZdC6peqLoHgxJKDkpWA-hKJWQb1fIWiBaIg-p2UazAda3qSsm4JJpt10t1s_uQvJvNfXBX_-plctjUqrqBTbeVlWigIQXPoHWE5sxwm-czTW1uHTOzdRTN2KHMMEcnk2fTZBkd8ciIIXSknGNC0JgWJKeXiTznTqs56pNffhj_R69m0c-D1X_Xxj8s9t7pKWW4KDA1c06YHfmYIjQjZuyEUjMVU8z6eM46-fXXowsP-rg--p_xfY15kWWEkBxF19ezy_o1BO_ml6sY6SdY-hmW_g9LR1i6ZDrC0k-w6F-Dk4Qy</recordid><startdate>20160101</startdate><enddate>20160101</enddate><creator>Salih, A. L.</creator><creator>Mühlbauer, M.</creator><creator>Grumpe, A.</creator><creator>Pasckert, J. H.</creator><creator>Wöhler, C.</creator><creator>Hiesinger, H.</creator><general>Copernicus GmbH</general><general>Copernicus Publications</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TN</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>H96</scope><scope>HCIFZ</scope><scope>L.G</scope><scope>L6V</scope><scope>M7S</scope><scope>PCBAR</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>DOA</scope></search><sort><creationdate>20160101</creationdate><title>MAPPING OF PLANETARY SURFACE AGE BASED ON CRATER STATISTICS OBTAINED BY AN AUTOMATIC DETECTION ALGORITHM</title><author>Salih, A. L. ; Mühlbauer, M. ; Grumpe, A. ; Pasckert, J. H. ; Wöhler, C. ; Hiesinger, H.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a2896-ce2374a9c77f35c7ce4afce30f1e06a4e3da76ddc43b1b42a23b3991220b58273</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Age</topic><topic>Algorithms</topic><topic>Area</topic><topic>Automation</topic><topic>Basalt</topic><topic>Calibration</topic><topic>Chronology</topic><topic>Colour</topic><topic>Counting</topic><topic>Data</topic><topic>Data acquisition</topic><topic>Detection</topic><topic>Frequency distribution</topic><topic>Image acquisition</topic><topic>Image detection</topic><topic>Image resolution</topic><topic>Impact analysis</topic><topic>Lunar craters</topic><topic>Mathematical models</topic><topic>Mosaics</topic><topic>Planet detection</topic><topic>Planetary surfaces</topic><topic>Regions</topic><topic>Resolution</topic><topic>Size determination</topic><topic>Spacecraft</topic><topic>Statistical methods</topic><topic>Ultraviolet radiation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Salih, A. L.</creatorcontrib><creatorcontrib>Mühlbauer, M.</creatorcontrib><creatorcontrib>Grumpe, A.</creatorcontrib><creatorcontrib>Pasckert, J. H.</creatorcontrib><creatorcontrib>Wöhler, C.</creatorcontrib><creatorcontrib>Hiesinger, H.</creatorcontrib><collection>CrossRef</collection><collection>Oceanic Abstracts</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Earth, Atmospheric &amp; Aquatic Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy &amp; Non-Living Resources</collection><collection>SciTech Premium Collection</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) Professional</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Earth, Atmospheric &amp; Aquatic Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>Directory of Open Access Journals</collection><jtitle>International archives of the photogrammetry, remote sensing and spatial information sciences.</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Salih, A. L.</au><au>Mühlbauer, M.</au><au>Grumpe, A.</au><au>Pasckert, J. H.</au><au>Wöhler, C.</au><au>Hiesinger, H.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>MAPPING OF PLANETARY SURFACE AGE BASED ON CRATER STATISTICS OBTAINED BY AN AUTOMATIC DETECTION ALGORITHM</atitle><jtitle>International archives of the photogrammetry, remote sensing and spatial information sciences.</jtitle><date>2016-01-01</date><risdate>2016</risdate><volume>XLI-B4</volume><spage>479</spage><epage>486</epage><pages>479-486</pages><issn>2194-9034</issn><issn>1682-1750</issn><eissn>2194-9034</eissn><abstract>The analysis of the impact crater size-frequency distribution (CSFD) is a well-established approach to the determination of the age of planetary surfaces. Classically, estimation of the CSFD is achieved by manual crater counting and size determination in spacecraft images, which, however, becomes very time-consuming for large surface areas and/or high image resolution. With increasing availability of high-resolution (nearly) global image mosaics of planetary surfaces, a variety of automated methods for the detection of craters based on image data and/or topographic data have been developed. In this contribution a template-based crater detection algorithm is used which analyses image data acquired under known illumination conditions. Its results are used to establish the CSFD for the examined area, which is then used to estimate the absolute model age of the surface. The detection threshold of the automatic crater detection algorithm is calibrated based on a region with available manually determined CSFD such that the age inferred from the manual crater counts corresponds to the age inferred from the automatic crater detection results. With this detection threshold, the automatic crater detection algorithm can be applied to a much larger surface region around the calibration area. The proposed age estimation method is demonstrated for a Kaguya Terrain Camera image mosaic of 7.4 m per pixel resolution of the floor region of the lunar crater Tsiolkovsky, which consists of dark and flat mare basalt and has an area of nearly 10,000 km2. The region used for calibration, for which manual crater counts are available, has an area of 100 km2. In order to obtain a spatially resolved age map, CSFDs and surface ages are computed for overlapping quadratic regions of about 4.4 x 4.4 km2 size offset by a step width of 74 m. Our constructed surface age map of the floor of Tsiolkovsky shows age values of typically 3.2-3.3 Ga, while for small regions lower (down to 2.9 Ga) and higher (up to 3.6 Ga) age values can be observed. It is known that CSFD-derived absolute model ages can exhibit variations although the surface has a constant age. However, for four 10-20 km sized regions in the eastern part of the crater floor our map shows age values differing by several hundred Ma from the typical age of the crater floor, where the same regions are also discernible in Clementine UV/VIS color ratio image data probably due to compositional variations, such that the age differences of these four regions may be real.</abstract><cop>Gottingen</cop><pub>Copernicus GmbH</pub><doi>10.5194/isprs-archives-XLI-B4-479-2016</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2194-9034
ispartof International archives of the photogrammetry, remote sensing and spatial information sciences., 2016-01, Vol.XLI-B4, p.479-486
issn 2194-9034
1682-1750
2194-9034
language eng
recordid cdi_doaj_primary_oai_doaj_org_article_d5418813af724cb9b500f04acd05ad8d
source Publicly Available Content Database; EZB Electronic Journals Library
subjects Age
Algorithms
Area
Automation
Basalt
Calibration
Chronology
Colour
Counting
Data
Data acquisition
Detection
Frequency distribution
Image acquisition
Image detection
Image resolution
Impact analysis
Lunar craters
Mathematical models
Mosaics
Planet detection
Planetary surfaces
Regions
Resolution
Size determination
Spacecraft
Statistical methods
Ultraviolet radiation
title MAPPING OF PLANETARY SURFACE AGE BASED ON CRATER STATISTICS OBTAINED BY AN AUTOMATIC DETECTION ALGORITHM
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-05T19%3A29%3A10IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=MAPPING%20OF%20PLANETARY%20SURFACE%20AGE%20BASED%20ON%20CRATER%20STATISTICS%20OBTAINED%20BY%20AN%20AUTOMATIC%20DETECTION%20ALGORITHM&rft.jtitle=International%20archives%20of%20the%20photogrammetry,%20remote%20sensing%20and%20spatial%20information%20sciences.&rft.au=Salih,%20A.%20L.&rft.date=2016-01-01&rft.volume=XLI-B4&rft.spage=479&rft.epage=486&rft.pages=479-486&rft.issn=2194-9034&rft.eissn=2194-9034&rft_id=info:doi/10.5194/isprs-archives-XLI-B4-479-2016&rft_dat=%3Cproquest_doaj_%3E1986622270%3C/proquest_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-a2896-ce2374a9c77f35c7ce4afce30f1e06a4e3da76ddc43b1b42a23b3991220b58273%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1986622270&rft_id=info:pmid/&rfr_iscdi=true