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(Street) Lights Will Guide You: Georeferencing Nighttime Astronaut Photography of Earth
Astronaut photography from the International Space Station provides the highest spatial resolution nighttime Earth observations imagery publicly available, offering up to a 150x increase in resolution over other freely accessible satellite data sources. Yet, this imagery is underutilized in science...
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creator | Stoken, Alex Ilhardt, Peter Lambert, Mark Fisher, Kenton |
description | Astronaut photography from the International Space Station provides the highest spatial resolution nighttime Earth observations imagery publicly available, offering up to a 150x increase in resolution over other freely accessible satellite data sources. Yet, this imagery is underutilized in science applications because it lacks the geolocation meta-data required for downstream analysis. We present Night-Match, a fast and accurate method for localizing and geo-rectifying nighttime astronaut photography. By combining street network data with daytime satellite imagery, we produce a reliable reference target for similarity detection via pairwise image matching. We curate and release the Astronaut Imagery Matching Subset - Night (AIMS-Night), a collection of 363 images and ground truth localizations, and benchmark our method against this set to establish a robust localization pipeline. Our method correctly localizes 81.8% of AIMS-Night, and can be quickly deployed on the over 2 million nighttime astronaut photographs to produce a high quality analysis-ready data product. |
doi_str_mv | 10.1109/CVPRW63382.2024.00054 |
format | conference_proceeding |
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Our method correctly localizes 81.8% of AIMS-Night, and can be quickly deployed on the over 2 million nighttime astronaut photographs to produce a high quality analysis-ready data product.</description><subject>Astronaut Photography</subject><subject>Earth</subject><subject>Geology</subject><subject>Image Matching</subject><subject>Location awareness</subject><subject>Nighttime Imagery</subject><subject>Photography</subject><subject>Remote Sensing</subject><subject>Roads</subject><subject>Soft sensors</subject><subject>Urban areas</subject><issn>2160-7516</issn><isbn>9798350365474</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2024</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNqFjkFrwjAYQONgMNn6Dxx8R3ew-9I0abvbEHWHMWQTiycJ-rWN1EaS9OC_V8H7Tu_w3uEx9sox5hyL9-l6-VsqIfIkTjBJY0SU6YBFRVbkQqJQMs3SBzZMuMJJJrl6YpH3h2vGMZeyEENWjv-CIwpv8G3qJngoTdvCojd7go3tP2BB1lFFjrqd6Wr4uVXBHAk-fXC2032AZWODrZ0-NWewFcy0C80Le6x06ym685mN5rPV9GtiiGh7cuao3XnLUWX59U78oy8mhkSg</recordid><startdate>20240617</startdate><enddate>20240617</enddate><creator>Stoken, Alex</creator><creator>Ilhardt, Peter</creator><creator>Lambert, Mark</creator><creator>Fisher, Kenton</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>20240617</creationdate><title>(Street) Lights Will Guide You: Georeferencing Nighttime Astronaut Photography of Earth</title><author>Stoken, Alex ; Ilhardt, Peter ; Lambert, Mark ; Fisher, Kenton</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-ieee_primary_106782163</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Astronaut Photography</topic><topic>Earth</topic><topic>Geology</topic><topic>Image Matching</topic><topic>Location awareness</topic><topic>Nighttime Imagery</topic><topic>Photography</topic><topic>Remote Sensing</topic><topic>Roads</topic><topic>Soft sensors</topic><topic>Urban areas</topic><toplevel>online_resources</toplevel><creatorcontrib>Stoken, Alex</creatorcontrib><creatorcontrib>Ilhardt, Peter</creatorcontrib><creatorcontrib>Lambert, Mark</creatorcontrib><creatorcontrib>Fisher, Kenton</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Stoken, Alex</au><au>Ilhardt, Peter</au><au>Lambert, Mark</au><au>Fisher, Kenton</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>(Street) Lights Will Guide You: Georeferencing Nighttime Astronaut Photography of Earth</atitle><btitle>2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)</btitle><stitle>CVPRW</stitle><date>2024-06-17</date><risdate>2024</risdate><spage>492</spage><epage>501</epage><pages>492-501</pages><eissn>2160-7516</eissn><eisbn>9798350365474</eisbn><coden>IEEPAD</coden><abstract>Astronaut photography from the International Space Station provides the highest spatial resolution nighttime Earth observations imagery publicly available, offering up to a 150x increase in resolution over other freely accessible satellite data sources. Yet, this imagery is underutilized in science applications because it lacks the geolocation meta-data required for downstream analysis. We present Night-Match, a fast and accurate method for localizing and geo-rectifying nighttime astronaut photography. By combining street network data with daytime satellite imagery, we produce a reliable reference target for similarity detection via pairwise image matching. We curate and release the Astronaut Imagery Matching Subset - Night (AIMS-Night), a collection of 363 images and ground truth localizations, and benchmark our method against this set to establish a robust localization pipeline. Our method correctly localizes 81.8% of AIMS-Night, and can be quickly deployed on the over 2 million nighttime astronaut photographs to produce a high quality analysis-ready data product.</abstract><pub>IEEE</pub><doi>10.1109/CVPRW63382.2024.00054</doi></addata></record> |
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source | IEEE Xplore All Conference Series |
subjects | Astronaut Photography Earth Geology Image Matching Location awareness Nighttime Imagery Photography Remote Sensing Roads Soft sensors Urban areas |
title | (Street) Lights Will Guide You: Georeferencing Nighttime Astronaut Photography of Earth |
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