Extraction of City Roads Using Luojia 1-01 Nighttime Light Data
The extraction of a road network is critical for city planning and has been widely studied in previous research using high resolution images, whereas the high cost of high-resolution remote sensing data and the complexity of its analysis also cause huge challenges for the extraction. The successful...
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2021
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oai:doaj.org-article:78f5c82b13d941fdbdf15529490c9a3e2021-11-11T15:10:56ZExtraction of City Roads Using Luojia 1-01 Nighttime Light Data10.3390/app1121101132076-3417https://doaj.org/article/78f5c82b13d941fdbdf15529490c9a3e2021-10-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/21/10113https://doaj.org/toc/2076-3417The extraction of a road network is critical for city planning and has been widely studied in previous research using high resolution images, whereas the high cost of high-resolution remote sensing data and the complexity of its analysis also cause huge challenges for the extraction. The successful launch of a high resolution (130 m) nighttime remote sensing satellite, Luojia 1-01, provides great potential in the study of urban issues. This study attempted to extract city roads using a Luojia 1-01 nighttime lighting image. The urban regions were firstly distinguished through a threshold method. Then, an unsupervised PCNN (pulse coupled neural network) was established to extract the road networks in urban regions. A series of optimizing methods was proposed to enhance the image contrast and eliminate the residential regions along the roads. The final extraction results after optimizing were compared with OSM (OpenStreetMap) data, showing the high precision of the proposed approach with the accuracy rate reaching 83.2%. We also found the precision of city centers to be lower than suburban regions due to the influence of intensive human activities. Our study confirms the potential of Luojia 1-01 data in the extraction of city roads and provides new thought for more complex and microscopic study of city issues.Luyao WangHao ZhangHaiyan XuAnfeng ZhuHong FanYankun WangMDPI AGarticleLuojia 1-01nighttime light imageryroad extractionurban regionsTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10113, p 10113 (2021) |
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DOAJ |
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Luojia 1-01 nighttime light imagery road extraction urban regions Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 |
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Luojia 1-01 nighttime light imagery road extraction urban regions Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Luyao Wang Hao Zhang Haiyan Xu Anfeng Zhu Hong Fan Yankun Wang Extraction of City Roads Using Luojia 1-01 Nighttime Light Data |
| description |
The extraction of a road network is critical for city planning and has been widely studied in previous research using high resolution images, whereas the high cost of high-resolution remote sensing data and the complexity of its analysis also cause huge challenges for the extraction. The successful launch of a high resolution (130 m) nighttime remote sensing satellite, Luojia 1-01, provides great potential in the study of urban issues. This study attempted to extract city roads using a Luojia 1-01 nighttime lighting image. The urban regions were firstly distinguished through a threshold method. Then, an unsupervised PCNN (pulse coupled neural network) was established to extract the road networks in urban regions. A series of optimizing methods was proposed to enhance the image contrast and eliminate the residential regions along the roads. The final extraction results after optimizing were compared with OSM (OpenStreetMap) data, showing the high precision of the proposed approach with the accuracy rate reaching 83.2%. We also found the precision of city centers to be lower than suburban regions due to the influence of intensive human activities. Our study confirms the potential of Luojia 1-01 data in the extraction of city roads and provides new thought for more complex and microscopic study of city issues. |
| format |
article |
| author |
Luyao Wang Hao Zhang Haiyan Xu Anfeng Zhu Hong Fan Yankun Wang |
| author_facet |
Luyao Wang Hao Zhang Haiyan Xu Anfeng Zhu Hong Fan Yankun Wang |
| author_sort |
Luyao Wang |
| title |
Extraction of City Roads Using Luojia 1-01 Nighttime Light Data |
| title_short |
Extraction of City Roads Using Luojia 1-01 Nighttime Light Data |
| title_full |
Extraction of City Roads Using Luojia 1-01 Nighttime Light Data |
| title_fullStr |
Extraction of City Roads Using Luojia 1-01 Nighttime Light Data |
| title_full_unstemmed |
Extraction of City Roads Using Luojia 1-01 Nighttime Light Data |
| title_sort |
extraction of city roads using luojia 1-01 nighttime light data |
| publisher |
MDPI AG |
| publishDate |
2021 |
| url |
https://doaj.org/article/78f5c82b13d941fdbdf15529490c9a3e |
| work_keys_str_mv |
AT luyaowang extractionofcityroadsusingluojia101nighttimelightdata AT haozhang extractionofcityroadsusingluojia101nighttimelightdata AT haiyanxu extractionofcityroadsusingluojia101nighttimelightdata AT anfengzhu extractionofcityroadsusingluojia101nighttimelightdata AT hongfan extractionofcityroadsusingluojia101nighttimelightdata AT yankunwang extractionofcityroadsusingluojia101nighttimelightdata |
| _version_ |
1718437151136284672 |