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Title: Advancements in LiDAR-based registration of FIA field plots

Author: Gatziolis, Demetrios.;

Date: 2012

Source: In: Morin, Randall S.; Liknes, Greg C., comps. Moving from status to trends: Forest Inventory and Analysis (FIA) symposium 2012; 2012 December 4-6; Baltimore, MD. Gen. Tech. Rep. NRS-P-105. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station. [CD-ROM]: 432-437.

Publication Series: Paper (invited, offered, keynote)

   Note: This article is part of a larger document. View the larger document

Description: Meaningful integration of National Forest Inventory field plot information with spectral imagery acquired from satellite or airborne platforms requires precise plot registration. Global positioning system-based plot registration procedures, such as the one employed by the Forest Inventory and Analysis (FIA) Program, yield plot coordinates that, although adequate for some purposes, often contain substantial error. Conversely, the registration of Light Detection and Ranging (LiDAR) data is accurate and precise. Considering the proliferation of high density LiDAR data, there is potential to substantially improve plot registration. Earlier attempts were not successful because they relied solely on the relative location of mapped tree stems and local maxima in vegetation surfaces generated from the LiDAR data. In this study, registration is achieved by examining the correlation between plot canopy surfaces generated by using the FIA field data and modeled tree crowns and the corresponding vegetation surface derived from the LiDAR data. With the LiDAR vegetation surface remaining stationary, the modeled surface is jittered in two dimensions at regular intervals, and the correlation is computed for each moving instance. Assuming that it satisfies a set of consistency criteria, the moving instance for which correlation is maximized yields the plot coordinates. Gains in computational efficiency are realized via parallelization. Results from eastern Oregon show that precise--better than 2 m--registration is achieved for 80 percent of the investigated FIA plots.

Keywords: statistics, estimation, sampling, modeling, remote sensing, forest health, data integrity, environmental monitoring, cover estimation, international forest monitoring

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Citation:


Gatziolis, Demetrios. 2012. Advancements in LiDAR-based registration of FIA field plots. In: Morin, Randall S.; Liknes, Greg C., comps. Moving from status to trends: Forest Inventory and Analysis (FIA) symposium 2012; 2012 December 4-6; Baltimore, MD. Gen. Tech. Rep. NRS-P-105. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station. [CD-ROM]: 432-437.

 


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