Next Article in Journal
The S-NPP VIIRS Day-Night Band On-Orbit Calibration/Characterization and Current State of SDR Products
Next Article in Special Issue
Establishing a Baseline for Regional Scale Monitoring of Eelgrass (Zostera marina) Habitat on the Lower Alaska Peninsula
Previous Article in Journal
A Kalman Filter-Based Method to Generate Continuous Time Series of Medium-Resolution NDVI Images
Previous Article in Special Issue
A Simple Method for Retrieving Understory NDVI in Sparse Needleleaf Forests in Alaska Using MODIS BRDF Data
Article Menu

Export Article

Open AccessArticle

Mapping Forest Height in Alaska Using GLAS, Landsat Composites, and Airborne LiDAR

ASRC Federal InuTeq, contractor to US Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, 47914 252nd Street, Sioux Falls, SD 57198, USA
USGS EROS, 47914 252nd Street, Sioux Falls, SD 57198, USA
Author to whom correspondence should be addressed.
Remote Sens. 2014, 6(12), 12409-12426;
Received: 27 June 2014 / Revised: 22 November 2014 / Accepted: 3 December 2014 / Published: 10 December 2014
(This article belongs to the Special Issue Remote Sensing of Changing Northern High Latitude Ecosystems)
PDF [4227 KB, uploaded 10 December 2014]


Vegetation structure, including forest canopy height, is an important input variable to fire behavior modeling systems for simulating wildfire behavior. As such, forest canopy height is one of a nationwide suite of products generated by the LANDFIRE program. In the past, LANDFIRE has relied on a combination of field observations and Landsat imagery to develop existing vegetation structure products. The paucity of field data in the remote Alaskan forests has led to a very simple forest canopy height classification for the original LANDFIRE forest height map. To better meet the needs of data users and refine the map legend, LANDFIRE incorporated ICESat Geoscience Laser Altimeter System (GLAS) data into the updating process when developing the LANDFIRE 2010 product. The high latitude of this region enabled dense coverage of discrete GLAS samples, from which forest height was calculated. Different methods for deriving height from the GLAS waveform data were applied, including an attempt to correct for slope. These methods were then evaluated and integrated into the final map according to predefined criteria. The resulting map of forest canopy height includes more height classes than the original map, thereby better depicting the heterogeneity of the landscape, and provides seamless data for fire behavior analysts and other users of LANDFIRE data. View Full-Text
Keywords: GLAS; LiDAR; Alaska; LANDFIRE; forest height GLAS; LiDAR; Alaska; LANDFIRE; forest height

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Peterson, B.; Nelson, K.J. Mapping Forest Height in Alaska Using GLAS, Landsat Composites, and Airborne LiDAR. Remote Sens. 2014, 6, 12409-12426.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top