NASA Logo

NTRS

NTRS - NASA Technical Reports Server

Back to Results
Merging IceSAT GLAS and Terra MODIS Data in Order to Derive Forest Type Specific Tree Heights in the Central Siberian Boreal ForestMapping of boreal forest's type, biomass, and other structural parameters are critical for understanding of the boreal forest's significance in the carbon cycle, its response to and impact on global climate change. We believe the nature of the forest structure information available from MISR and GLAS can be used to help identify forest type, age class, and estimate above ground biomass levels beyond that now possible with MODIS alone. The ground measurements will be used to develop relationships between remote sensing observables and forest characteristics and provide new information for understanding forest changes with respect to environmental change. Lidar is a laser altimeter that determines the distance from the instrument to the physical surface by measuring the time elapsed between the pulse emission and the reflected return. Other studies have shown that the returned signal may identify multiple returns originating from trees, building and other objects and permits the calculation of their height. Studies using field data have shown that lidar data can provide estimates of structural parameters such as biomass, stand volume and leaf area index and allows remarkable differentiation between primary and secondary forest. NASA's IceSAT Geoscience Laser Altimeter System (GLAS) was launched in January 2003 and collected data during February and September of that year. This study used data acquired over our study sites in central Siberia to examine the GLAS signal as a source of forest height and other structural characteristics. The purpose of our Siberia project is to improve forest cover maps and produce above-ground biomass maps of the boreal forest in Northern Eurasia from MODIS by incorporating structural information inherent in the Terra MISR and ICESAT Geoscience Laser Altimeter System (GLAS) instruments. A number of forest cover classifications exist for the boreal forest. We believe the limiting factor in these products is the lack of structural information, particularly in the vertical dimension. The emphasis of this project is to improve upon satellite maps of boreal forest structure parameters (i.e. height and biomass) using temporal, multi-angle, and vertical profile information of GLAS data. The existing and near future lidar data is useful for demonstrating these techniques and pursuing current estimates. Future lidar missions may be several years in the future, so we will work other new data sets that may aide in biomass estimates such as ALOS PALSAR We will continue this work to produce an accurate map of current above ground forest phytomass/carbon storage possible for the study area. We plan to develop, test, and integrate remote sensing methods for extracting forest canopy structure measures. We are compiling our field measurements and will compare them with the remote sensing methods where possible. We also be able to produce a realistic error bound on the remotely sensed carbon estimates.
Document ID
20080045493
Acquisition Source
Goddard Space Flight Center
Document Type
Conference Paper
Authors
Ranson, K. Jon
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Sun, Guoqing
(Maryland Univ. College Park, MD, United States)
Kimes, Daniel
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Kovacs, Katalin
(Science Systems and Applications, Inc. Lanham, MD, United States)
Kharuk, Viatscheslav
Date Acquired
August 24, 2013
Publication Date
July 31, 2006
Subject Category
Earth Resources And Remote Sensing
Meeting Information
Meeting: International Geoscience and Remote Sensing Symposium and 27th Canadian Symposium on Remote Sensing
Location: Colorado
Country: United States
Start Date: July 31, 2006
End Date: August 4, 2006
Sponsors: Institute of Electrical and Electronics Engineers
Distribution Limits
Public
Copyright
Other

Available Downloads

There are no available downloads for this record.
No Preview Available