infection
发表于 2025-3-21 16:43:59
书目名称Advances in Remote Sensing for Infrastructure Monitoring影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0149566<br><br> <br><br>书目名称Advances in Remote Sensing for Infrastructure Monitoring影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0149566<br><br> <br><br>书目名称Advances in Remote Sensing for Infrastructure Monitoring网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0149566<br><br> <br><br>书目名称Advances in Remote Sensing for Infrastructure Monitoring网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0149566<br><br> <br><br>书目名称Advances in Remote Sensing for Infrastructure Monitoring被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0149566<br><br> <br><br>书目名称Advances in Remote Sensing for Infrastructure Monitoring被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0149566<br><br> <br><br>书目名称Advances in Remote Sensing for Infrastructure Monitoring年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0149566<br><br> <br><br>书目名称Advances in Remote Sensing for Infrastructure Monitoring年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0149566<br><br> <br><br>书目名称Advances in Remote Sensing for Infrastructure Monitoring读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0149566<br><br> <br><br>书目名称Advances in Remote Sensing for Infrastructure Monitoring读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0149566<br><br> <br><br>
annexation
发表于 2025-3-21 23:59:36
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褪色
发表于 2025-3-22 03:05:44
Sentinel-1 InSAR Data for the Continuous Monitoring of Ground Deformation and Infrastructures at Regbust Earth observation system. The results obtained are presented and discussed through the case studies of Pistoia and Guasticce (Livorno), where land subsidence threatens linear and areal strategic infrastructures. The examples highlight the capability of radar satellite missions to provide regula
Certainty
发表于 2025-3-22 06:17:09
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暂时休息
发表于 2025-3-22 10:08:53
Landslide Activity Assessment of a Subtropical Area by Integrating InSAR, Landslide Inventory, Airbomoving landslides with a surface displacement of about 2 cm/year and debris flows on the bed of a gully. The InSAR displacement map helps to recognize the possible deep-seated landslides not previously known using a DTM. The field validation of the InSAR results from the proposed approach confirmed
NICE
发表于 2025-3-22 14:16:15
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Anthrp
发表于 2025-3-22 17:13:04
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incarcerate
发表于 2025-3-22 22:40:19
Earth Observation Based Understanding of Canadian Urban Forme urban form and its impacts by using spatial information from image data at pixel level. The scope of this research is in a broad range in nature and includes information extraction from remote sensing image data, integration of land use time-series maps from diverse historic sources and finally sp
puzzle
发表于 2025-3-23 02:16:24
Extraction of Building Footprints from LiDAR: An Assessment of Classification and Point Density Requ open-source tools) point data clouds in the building extraction process. Results indicate that vendor-classified point cloud data with a minimum density of 4 pts/m. is sufficient to accurately extract building footprints with >75% confidence. For re-classified LiDAR a density of at least 8 pts/m. w
抱怨
发表于 2025-3-23 07:36:36
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