PE and RS PUBLIC November 2011 : Page-1078

Figure 5. Breaklines for streams and waterbodies overlying intensity data on the left and hydro-ﬂ attened DEM data on the right. Note the TIN artifacts and data irregularities in the left-side image for areas within the breaklines and the smooth surface within the same areas in the right-side image. These forms of tests may be a typical part of the advanced visual checks performed on fi nal data sets. continued from page 1077 • Products, Documents, Reports, and Metadata: There is a complex set of deliverable components in a lidar data project. Checksheets and methods are needed to compile a complete list of deliverable products and to verify them against require-ments and speciﬁ cations. Best practice methods are needed that might include a project data directory structure for data and derived information products, as well as a possible project documents, reports, and metadata repository to assure proper organization and delivery of ﬁ nal products. Benefits: Standardizing the organization and delivery of components of project products will help assure consistent products that may be effectively tested against guidelines and speciﬁ cations. Implementing streamlined capabilities that enable real-time testing of incremental products during the lidar project life cycle will ensure that post production tests of end products will meet product speciﬁ cations and requirements and will help improve the accuracy and quality of lidar data and derived information products. Multi-County Project, Michigan (USGS) A USGS-funded acquisition project collected lidar data for multiple counties in Michigan (Figure 7). This data collection illustrates what is becoming more of the norm for lidar acquisi-tion projects in which data are collected for multiple counties and deliverables conform to speciﬁ cations of the USGS and FEMA for elevation updates, map data enhancements, and ﬂ ood plain mapping updates. Lidar was collected by a ﬁ xed-wing aerial platform. Data management and organization of data and derived products becomes more of a challenge with large projects, in this case comprising over 2,500 tiles of classiﬁ ed LAS data, DEM data, and other derived data products. Accuracy of the lidar point cloud data was determined to be .284 US Survey Feet (8.66 cm) at the 95% conﬁ dence level (FVA) and for the DEM to be .342 US Survey Feet (10.42 cm) at the 95% conﬁ dence level (FVA). Texas DOT Demonstration Project (Industry Collaboration) In a project aimed at highway transportation data acquisition for design and other applications, high-accuracy helicopter and terrestrial mobile lidar datasets were acquired for a segment of I-30 in Texas. Data were acquired to improve understand-ing of water accumulation of the interstate segment studied. Tuck Mapping ﬂ ew helicopter lidar and other project partners collected terrestrial mobile lidar datasets. The lidar collected by Tuck Mapping (Figure 8) was found to have an RMSE Z of 0.039 US Survey Feet (1.19 cm) and a FVA 95% conﬁ dence level accuracy of 0.076 US Survey Feet (2.32 cm). Focus Projects Spatial Information Solutions (SIS) has compiled a collection of recently acquired sample lidar data sets from federal agen-cies as well as industry lidar data producers. In some cases, data were provided along with surveyed checkpoints which were used in the SIS software product, Topo Analyst, to verify accuracy and perform other quantitative and qualitative checks on the data sets. A brief description of the data sets, a view of the data and fundamental accuracy characteristics follow for a set of highlighed focus projects. Channel Islands, California (USGS) The USGS funded a lidar collection for the Channel Islands off the coast of California. The project presented challenges in terms of difﬁ culty of access, lack of ability to establish ground survey base stations, and the rugged terrain and steep cliffs on the sides of the islands. These factors combined to add difﬁ culties to aspects of data acquisition and processing. The lidar data were collected by helicopter and survey checkpoint locations were accessed by helicopter. As shown in ﬁ gure 6, the fundamental vertical accuracy on this project was determined to be 5.8 cm. Figure 6. View of Channel Islands elevation data and absolute accuracy verifi cation testing of LAS data by Fundamental Vertical Accuracy for quantifying accuracy to the 95 percent confi dence level. 1078 November 2011 Photogrammetric engineering & remote SenSing

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