A Comparison of Standard Modeling Techniques Using Digital Aerial Imagery with National Elevation Datasets and Airborne LiDAR to Predict Size and Density Forest Metrics in the Sapphire Mountains MT, USA

In recent years airborne Light Detection and Ranging (LiDAR) technology has received a great deal of attention. Using airborne LiDAR, analysts have successfully related height measurements to forest characteristics such as tree size, basal area, and number of trees. Similarly, National Agricultural...

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Bibliographic Details
Published in:ISPRS international journal of geo-information 2019-01, Vol.8 (1), p.24
Main Authors: Ahl, Robert, Hogland, John, Brown, Steve
Format: Article
Language:English
Subjects:
Accuracy
Aerial photography
AIC
Airborne remote sensing
Airborne sensing
comparison
Costs
Datasets
Digital imaging
Elevation
Estimates
Forest management
forest metrics
Forests
Global positioning systems
GPS
Imagery
LIDAR
modeling
Montana
Mountains
NAIP
Sapphire
Topography
Variables
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Summary:In recent years airborne Light Detection and Ranging (LiDAR) technology has received a great deal of attention. Using airborne LiDAR, analysts have successfully related height measurements to forest characteristics such as tree size, basal area, and number of trees. Similarly, National Agricultural Imagery Program (NAIP) digital aerial imagery in combination with elevation datasets such as the National Elevation Dataset (NED) have been used to estimate similar forest characteristics. Few comparisons, however, have been made between using airborne LiDAR, NAIP, and NED to estimate forest characteristics. In this study we compare airborne LiDAR, NAIP, and NAIP assisted NED based models of forest characteristics commonly used within forest management at the spatial scale of field plots and forest stands. Our findings suggest that there is a high degree of similarity in model fit and estimated values when using LiDAR, NAIP, and NAIP assisted NED predictor variables.
ISSN:2220-9964
2220-9964
DOI:10.3390/ijgi8010024