Auto Neural Architecture Generator for UAV-Based Geospatial Surveillance for Aerial Crisis Mapping in Dark
Natural disasters such as flood, tsunami, earthquake and cyclones usually influence the microspaces and in urban areas, thereby causing the problem to rescuers to make way to the victims. Rescue operations in these situations are also hampered due to darkness caused by power cut and unavailability o...
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| Veröffentlicht in: | Journal of the Indian Society of Remote Sensing 2021-03, Vol.49 (3), p.507-514 |
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| container_title | Journal of the Indian Society of Remote Sensing |
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| creator | Rai, Ankush Kannan, R. Jagadeesh |
| description | Natural disasters such as flood, tsunami, earthquake and cyclones usually influence the microspaces and in urban areas, thereby causing the problem to rescuers to make way to the victims. Rescue operations in these situations are also hampered due to darkness caused by power cut and unavailability of other light sources to rescue people in peril or to even carry out evacuation operations. Therefore, we need solution to map all the essential large-scale feature spaces in dark to avail safety and saving numerous lives in disaster environments. This study presents a soft framework for crisis mapping in dark to map aerial view of geo-specific terrain in disaster struck areas so that effective map of debris and localization of victims can be achieved to enable strategic planning of rescue operations. |
| doi_str_mv | 10.1007/s12524-020-01236-y |
| format | Article |
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This study presents a soft framework for crisis mapping in dark to map aerial view of geo-specific terrain in disaster struck areas so that effective map of debris and localization of victims can be achieved to enable strategic planning of rescue operations.</description><subject>Cyclones</subject><subject>Darkness</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Earthquakes</subject><subject>Flood mapping</subject><subject>Light sources</subject><subject>Natural disasters</subject><subject>Remote Sensing/Photogrammetry</subject><subject>Rescue operations</subject><subject>Research Article</subject><subject>Seismic activity</subject><subject>Unmanned aerial vehicles</subject><subject>Urban areas</subject><issn>0255-660X</issn><issn>0974-3006</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp9kDFPwzAQhS0EEqXwB5giMRvOduw4YyhQkAoMUMRmua5dXEIS7ASp_x6XIrExnO709L073UPolMA5ASguIqGc5hgoYCCUCbzZQyMoixwzALGfZso5FgJeD9FRjOsk5pzQEVpXQ99mD3YIus6qYN58b00_BJtNbWOD7tuQuVTz6gVf6miXSW9jp3uf-KchfFlf17ox9oeqbNjqk-Cjj9m97jrfrDLfZFc6vB-jA6fraE9--xjNb66fJ7d49ji9m1QzbGgBPS6ps05wB4uc0YLJQizBgaQSmCx5-tAQyXPDGWjmnBRmURhhnHR6q4uSjdHZbm8X2s_Bxl6t2yE06aSinAAtC0khUXRHmdDGGKxTXfAfOmwUAbXNVO0yVemi-slUbZKJ7Uwxwc3Khr_V_7i-AQGEeW8</recordid><startdate>20210301</startdate><enddate>20210301</enddate><creator>Rai, Ankush</creator><creator>Kannan, R. 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| ispartof | Journal of the Indian Society of Remote Sensing, 2021-03, Vol.49 (3), p.507-514 |
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| language | eng |
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| source | SpringerLink Journals - AutoHoldings |
| subjects | Cyclones Darkness Earth and Environmental Science Earth Sciences Earthquakes Flood mapping Light sources Natural disasters Remote Sensing/Photogrammetry Rescue operations Research Article Seismic activity Unmanned aerial vehicles Urban areas |
| title | Auto Neural Architecture Generator for UAV-Based Geospatial Surveillance for Aerial Crisis Mapping in Dark |
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