Robust Extraction of Digital Terrain Information from Noisy Point Clouds-Prevention of Surface Discharges into Water Infrastructure Networks

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.