Using LP360 Feature Analyst to QA/QC Building Extraction Results

LP360 now has a full set of feature analysis and editing tools for working with the geometries of features – points, lines and polygons – in your project[1].  As often happens with LP360 features, the initial driver for adding this capability was a very specific problem; editing the toes of stockpiles being used in volume…

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Generating Low Confidence Polygons

In the new ASPRS Positional Accuracy Standards for Digital Geospatial Data, low confidence areas within LIDAR data are defined to be where the bare earth model might not meet the overall data accuracy requirements. Generally speaking with LIDAR data this can occur where there is heavy vegetation that causes poor penetration of the pulses. If…

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Breaklines should Undergo QA/QC

As with any data, breaklines should undergo a QA/QC process. For breaklines this should entail a check for potential topology errors as well as incorrect elevation values. Since breaklines are used to define and control surface behavior in terms of smoothness and continuity they may have a significant effect when incorporated in a surface model.

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Macro Quality Control (QC) before Micro QC

In order to minimize the amount of effort required for performing quality control on data it is best to run macro-level quality control checks to quickly assess whether to invest the labor in micro-level quality assessments. Hillshade images can be used as part of a quick quality control analysis by providing an overview perspective on…

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Control Point Comparison QA-QC Analysis

An important evaluation to make when performing a QAQC analysis of a LIDAR data set is a control point comparison. When discussing control points and LIDAR data, there are typically two types of points that need to be considered independently. Control Points: The monuments or markers used to control the LIDAR collection or validation point…

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Pierce County WA LIDAR Acquisition and Quality Control Procedures using LP360

Pierce County, Washington has used LIDAR data since 2004 as a mission critical component of the County’s Geographic Information System (GIS). The data, collected from 2000 to 2004, has been used for a variety of purposes, including economic development, environmental planning, construction and transportation projects, and emergency management. However, this data was collected with older…

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