Evaluating the Potential of SDGSAT-1 Glimmer Imagery for Urban Road Detection
Sustainable Development Science Satellite 1 (SDGSAT-1), an innovative satellite engineered by the Chinese Academy of Sciences, focuses on achieving sustainable development goals (SDGs) by using high-resolution low-light imaging for urban planning and environmental monitoring. Although its potential...
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IEEE
2025-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
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| Online Access: | https://ieeexplore.ieee.org/document/10758202/ |
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| author | Yu Wang Hailan Huang Bin Wu |
| author_facet | Yu Wang Hailan Huang Bin Wu |
| author_sort | Yu Wang |
| collection | DOAJ |
| description | Sustainable Development Science Satellite 1 (SDGSAT-1), an innovative satellite engineered by the Chinese Academy of Sciences, focuses on achieving sustainable development goals (SDGs) by using high-resolution low-light imaging for urban planning and environmental monitoring. Although its potential to provide substantial information relevant to various SDG indicators has been demonstrated across multiple domains, a comprehensive analysis of the potential of SDGSAT-1 glimmer imagery for urban road detection has not yet conducted. To address this gap, we aimed to evaluate the applicability of SDGSAT-1 glimmer imagery in road detection across five cities with well-developed road networks in China, namely Chengdu, Guangzhou, Hangzhou, Shanghai, and Wuhan. Watershed segmentation and optimal thresholding algorithms were applied to extract the road network data of these five cities. We observed that the large connecting roads, including highways (<italic>Motorway</italic>), urban expressways (<italic>Trunk</italic>), urban main roads (<italic>Primary</italic>), urban secondary roads (<italic>Secondary</italic>), and urban tertiary roads (<italic>Tertiary</italic>), were visible in the SDGSAT-1 glimmer data. Watershed segmentation and optimal thresholding algorithms demonstrated a remarkable precision of approximately 80% for road extraction across all cities. Approximately, 64% of urban roads were detectable within the SDGSAT-1 glimmer imager data. Our study suggests that the SDGSAT-1 glimmer data have great potential for extracting urban roads. |
| format | Article |
| id | doaj-art-76f581c2ed3948ca9a875112cb76696c |
| institution | OA Journals |
| issn | 1939-1404 2151-1535 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
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| series | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| spelling | doaj-art-76f581c2ed3948ca9a875112cb76696c2025-08-20T02:38:51ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing1939-14042151-15352025-01-011878579410.1109/JSTARS.2024.350221810758202Evaluating the Potential of SDGSAT-1 Glimmer Imagery for Urban Road DetectionYu Wang0https://orcid.org/0009-0008-3801-4869Hailan Huang1https://orcid.org/0009-0004-0134-1904Bin Wu2https://orcid.org/0000-0002-1511-2457School of Geospatial Engineering and Science, Sun Yat-sen University, Zhuhai, ChinaSchool of Geospatial Engineering and Science, Sun Yat-sen University, Zhuhai, ChinaSchool of Geospatial Engineering and Science, Sun Yat-sen University, Zhuhai, ChinaSustainable Development Science Satellite 1 (SDGSAT-1), an innovative satellite engineered by the Chinese Academy of Sciences, focuses on achieving sustainable development goals (SDGs) by using high-resolution low-light imaging for urban planning and environmental monitoring. Although its potential to provide substantial information relevant to various SDG indicators has been demonstrated across multiple domains, a comprehensive analysis of the potential of SDGSAT-1 glimmer imagery for urban road detection has not yet conducted. To address this gap, we aimed to evaluate the applicability of SDGSAT-1 glimmer imagery in road detection across five cities with well-developed road networks in China, namely Chengdu, Guangzhou, Hangzhou, Shanghai, and Wuhan. Watershed segmentation and optimal thresholding algorithms were applied to extract the road network data of these five cities. We observed that the large connecting roads, including highways (<italic>Motorway</italic>), urban expressways (<italic>Trunk</italic>), urban main roads (<italic>Primary</italic>), urban secondary roads (<italic>Secondary</italic>), and urban tertiary roads (<italic>Tertiary</italic>), were visible in the SDGSAT-1 glimmer data. Watershed segmentation and optimal thresholding algorithms demonstrated a remarkable precision of approximately 80% for road extraction across all cities. Approximately, 64% of urban roads were detectable within the SDGSAT-1 glimmer imager data. Our study suggests that the SDGSAT-1 glimmer data have great potential for extracting urban roads.https://ieeexplore.ieee.org/document/10758202/Glimmer datanighttime light (NTL)sustainable development science satellite 1 (SDGSAT-1)urban roadswatershed segmentation |
| spellingShingle | Yu Wang Hailan Huang Bin Wu Evaluating the Potential of SDGSAT-1 Glimmer Imagery for Urban Road Detection IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Glimmer data nighttime light (NTL) sustainable development science satellite 1 (SDGSAT-1) urban roads watershed segmentation |
| title | Evaluating the Potential of SDGSAT-1 Glimmer Imagery for Urban Road Detection |
| title_full | Evaluating the Potential of SDGSAT-1 Glimmer Imagery for Urban Road Detection |
| title_fullStr | Evaluating the Potential of SDGSAT-1 Glimmer Imagery for Urban Road Detection |
| title_full_unstemmed | Evaluating the Potential of SDGSAT-1 Glimmer Imagery for Urban Road Detection |
| title_short | Evaluating the Potential of SDGSAT-1 Glimmer Imagery for Urban Road Detection |
| title_sort | evaluating the potential of sdgsat 1 glimmer imagery for urban road detection |
| topic | Glimmer data nighttime light (NTL) sustainable development science satellite 1 (SDGSAT-1) urban roads watershed segmentation |
| url | https://ieeexplore.ieee.org/document/10758202/ |
| work_keys_str_mv | AT yuwang evaluatingthepotentialofsdgsat1glimmerimageryforurbanroaddetection AT hailanhuang evaluatingthepotentialofsdgsat1glimmerimageryforurbanroaddetection AT binwu evaluatingthepotentialofsdgsat1glimmerimageryforurbanroaddetection |