Extended Abstract (568K)P1.1
Gulf Coast forest damage detection and carbon flux estimation using ICESat GLAS and Landsat TM
Jason Brent Jones, NASA DEVELOP Program, Stennis Space Center, MS; and L. M. Childs, M. W. Brozen, M. C. Batina, A. Maki, A. O. Brooks, J. W. Frey, and C. Chappell
Tropical storms and hurricanes annually cause defoliation and deforestation along the Gulf Coast. Following severe storms, there is an urgent need to assess the impact on timber growth so resources can be targeted to assist in recovery efforts. It is also important to identify these damaged areas due to their increased risk of fire, heightened susceptibility to invasive species, and fluctuations in carbon storage capacity. Current methods of detection involve assessment through ground-based field surveys, aerial surveys, computer modeling, space-borne remote sensing, and Forest Inventory and Analysis field plots. This project focuses on a need for methods that are at once more synoptic than field surveys and more closely linked to the phenomenology of tree loss and damage than passive remote sensing methods.
The primary concentration of the project is on the utilization of Ice, Cloud, and land Elevation Satellite (ICESat) data products to detect changes in forest canopy height as an indicator of post-hurricane forest disturbances, and the use of Landsat TM imagery to create forest fuel type land classifications and estimations of carbon loss due to storms. ICESat is a LIDAR mission for measuring ice sheet mass balance, cloud and aerosol heights, as well as land topography and vegetation characteristics. ICESat's Geoscience Laser Altimeter System (GLAS) instrument was used to measure topography over land, focusing on coastal forest canopy heights.
By analyzing ICESat and Landsat data over areas in Pearl River County, Hancock County, St. Tammany Parish, and Washington Parish affected by Hurricane Katrina, this study demonstrates that ICESat may serve as an indicator of a storm's direct effects on coastal forests as well as its long term consequences, while Landsat TM can be useful in estimating carbon flux over time.
Poster Session 1, Student Conference Posters
Sunday, 11 January 2009, 5:30 PM-7:00 PM
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