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LiDAR Feature Extraction and Geospatial Analysis

Mark Alonzo
In just a few days I’ll be at the 2012 Esri International User Conference and I’m looking forward to seeing what new LiDAR applications and methods everyone is buzzing about.  Recently, I’ve seen the growing use of LiDAR data across a huge variety of industries and applications.  But years ago, LiDAR data was used primarily for atmospheric research and large-scale measurements of ocean and forest properties.  Now that LiDAR flying missions are more affordable and providers more abundant, the geospatial user community is able to take advantage of the high density data to perform advanced analyses such as feature extractions and fine scale measurements. One of the features of LiDAR analysis that I find most interesting is feature extraction, the process of finding and extracting specific objects of interest from LiDAR point clouds.  After extracting features in a point cloud, those features can be exported as products or layers for additional geospatial analysis, and shared with colleagues for verification studies, or inclusion in your GIS for mapping applications. At the UC, I’ll be demonstrating how to extract trees from within a forest plot.  To do this, I’ll use E3De to extract trees within a defined area of my point cloud data and then I’ll classify the trees by height.  The production parameters allow me to define the minimum and maximum height and radius for automated tree extraction, allowing me to filter out low vegetation, undergrowth, or anomalies in the data.  You can stop by our booth to learn more about this technique and share with me how you’re using LiDAR data to enhance your geospatial analysis.   What are you looking forward to seeing at the 2012 Esri UC?

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