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Extracting Building Features from LiDAR and Optical Data

Mark Alonzo

As the availability of remotely acquired data continues to grow, high quality imagery is more accessible and less expensive than it was in previous decades. As a result, the need to incorporate remotely sensed imagery into GIS-based analyses continues to increase as well.  Further, LiDAR data can be combined with spectral imagery sources to efficiently provide map and information support for relief and recovery in the aftermath of a disaster, such as an earthquake.  One method of image analysis that can be used to take advantage of remotely sensed data and update GIS databases includes object-based image analysis.

When studying the operational landscape or needing updated information for situational awareness, one important factor that is needed is the quantity and location of building footprints. I n this study, the E3De LiDAR processing tool was used to extract building footprints from a dense LiDAR point cloud collection.  ENVI was used to fuse image data with the processed LiDAR data for enhanced building extraction efforts and attribution. The results from this image analysis process can be provided in raster or vector format, depending on the needs of the user. The results often provide critical, time-sensitive information that can be used, for example, to update a geodatabase, understand how many buildings are of a certain size, or create a map for dissemination to analysts on the ground.

Learn more about E3De, ENVI, and LiDAR feature extracting by attending my presentation at Esri's Federal GIS Conference on Friday, Feburary 24, 2023 in Room 209B at 10:15am.

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