Publication Details

Refining FIA plot locations using LiDAR point clouds

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Schrader-Patton, Charlie; Liknes, Greg C.; Gatziolis, Demetrios; Wing, Brian M.; Nelson, Mark D.; Miles, Patrick D.; Bixby, Josh; Wendt, Daniel G.; Kepler, Dennis; Schaaf, Abbey

Year Published

2015

Publication

In: Stanton, Sharon M.; Christensen, Glenn A., comps. 2015. Pushing boundaries: new directions in inventory techniques and applications: Forest Inventory and Analysis (FIA) symposium 2015. 2015 December 8?10; Portland, Oregon. Gen. Tech. Rep. PNW-GTR-931. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station: 247-252.

Abstract

Forest Inventory and Analysis (FIA) plot location coordinate precision is often insufficient for use with high resolution remotely sensed data, thereby limiting the use of these plots for geospatial applications and reducing the validity of models that assume the locations are precise. A practical and efficient method is needed to improve coordinate precision. To address this need, the USDA Forest Service’s Remote Sensing Steering Committee has funded an applied research project to evaluate alternative methods that capitalize on lidar data availability to improve plot location precision. We are exploring two methods to improve plot location precision—a manual interpretation technique and a 3D surface model matching routine using FIA tree data and lidar collected in northeastern Minnesota.

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Citation

Schrader-Patton, Charlie; Liknes, Greg C.; Gatziolis, Demetrios; Wing, Brian M.; Nelson, Mark D.; Miles, Patrick D.; Bixby, Josh; Wendt, Daniel G.; Kepler, Dennis; Schaaf, Abbey. 2015. Refining FIA plot locations using LiDAR point clouds. In: Stanton, Sharon M.; Christensen, Glenn A., comps. 2015. Pushing boundaries: new directions in inventory techniques and applications: Forest Inventory and Analysis (FIA) symposium 2015. 2015 December 8–10; Portland, Oregon. Gen. Tech. Rep. PNW-GTR-931. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station: 247-252.

Last updated on: February 17, 2016