TY - GEN
T1 - Robust Extraction of Digital Terrain Information from Noisy Point Clouds-Prevention of Surface Discharges into Water Infrastructure Networks
AU - Paladugu, Bala Sai Krishna
AU - Grau, David
AU - Ray, Tiyasa
N1 - Publisher Copyright:
© 2020 American Society of Civil Engineers.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020
Y1 - 2020
N2 - Uncontrolled water discharges into waterways pose significant threats to public health and the environment. Debris, chemicals, sediments, and other pollutants from soil embankments and surrounding areas with an inverted slope (leaning towards the waterway) are discharged with surface debris into waterways. In reality, the control and prevention of surface water discharges is an Environmental Protection Agency's National Enforcement Initiative of mandatory compliance and thus a critical water management function. However, identification and mitigation of inverted slopes on large water networks with manual surveying is error-prone, expensive, time-consuming, and, often, unfeasible. As a result, the presence and location of inverted slopes are commonly unknown to water management authorities. The ongoing study presented in this paper introduces a novel and computationally inexpensive noise filter terrain modeling algorithm that efficiently extracts rough terrain soil embankment profiles from noisy point cloud datasets, and determines the slope along the embankment surfaces. High-density LiDAR and photogrammetric data were collected and leveraged to model the slope profile. Results were validated and presented as geo-referenced slope heat maps.
AB - Uncontrolled water discharges into waterways pose significant threats to public health and the environment. Debris, chemicals, sediments, and other pollutants from soil embankments and surrounding areas with an inverted slope (leaning towards the waterway) are discharged with surface debris into waterways. In reality, the control and prevention of surface water discharges is an Environmental Protection Agency's National Enforcement Initiative of mandatory compliance and thus a critical water management function. However, identification and mitigation of inverted slopes on large water networks with manual surveying is error-prone, expensive, time-consuming, and, often, unfeasible. As a result, the presence and location of inverted slopes are commonly unknown to water management authorities. The ongoing study presented in this paper introduces a novel and computationally inexpensive noise filter terrain modeling algorithm that efficiently extracts rough terrain soil embankment profiles from noisy point cloud datasets, and determines the slope along the embankment surfaces. High-density LiDAR and photogrammetric data were collected and leveraged to model the slope profile. Results were validated and presented as geo-referenced slope heat maps.
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M3 - Conference contribution
AN - SCOPUS:85096753827
T3 - Construction Research Congress 2020: Computer Applications - Selected Papers from the Construction Research Congress 2020
SP - 389
EP - 397
BT - Construction Research Congress 2020
A2 - Tang, Pingbo
A2 - Grau, David
A2 - El Asmar, Mounir
PB - American Society of Civil Engineers (ASCE)
T2 - Construction Research Congress 2020: Computer Applications
Y2 - 8 March 2020 through 10 March 2020
ER -