دسته بندی:
بینایی ماشین - Machine vision
سال انتشار:
2022
عنوان انگلیسی مقاله:
Assessing surface drainage conditions at the street and neighborhood scale: A computer vision and flow direction method applied to lidar data
ترجمه فارسی عنوان مقاله:
ارزیابی شرایط زهکشی سطحی در مقیاس خیابان و محله: یک روش دید کامپیوتری و جهت جریان اعمال شده به داده های لیدار
منبع:
ScienceDirect- Elsevier- Computers, Environment and Urban Systems, 93 (2022) 101755: doi:10:1016/j:compenvurbsys:2021:101755
نویسنده:
Cheng-Chun Lee
چکیده انگلیسی:
Surface drainage at the neighborhood and street scales plays an important role in conveying stormwater and
mitigating urban flooding. Surface drainage at the local scale is often ignored due to the lack of up-to-date fine-
scale topographical information. This paper addresses this issue by providing a novel method for evaluating
surface drainage at the neighborhood and street scales based on mobile lidar (light detection and ranging)
measurements. The developed method derives topographical properties and runoff accumulation by applying a
semantic segmentation (SS) model (a computer vision technique) and a flow direction model (a hydrology
technique) to lidar data. Fifty lidar images representing 50 street blocks were used to train, validate, and test the
SS model. Based on the test dataset, the SS model has 80.3% IoU and 88.5% accuracy. The results suggest that the
proposed method can effectively evaluate surface drainage conditions at both the neighborhood and street scales
and identify problematic low points that could be susceptible to water ponding. Municipalities and property
owners can use this information to take targeted corrective maintenance actions.
keywords: تقسیم بندی معنایی | جهت جریان | لیدار موبایل | زهکشی سطحی | زیرساخت های زهکشی | Semantic segmentation | Flow direction | Mobile lidar | Surface drainage | Drainage infrastructure
قیمت: رایگان
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