Vegetation Products from ICESat: A database of GLAS (Geosciences Laser Altimeter System) waveforms and a global map of forest canopy height
Michael
A
Lefsky, Colorado State, lefsky@cnr.colostate.edu
(Presenting)
Yong
Pang, Forest Remote Sensing Lab.,, Institute of Forest Resource Information Techniques,, Chinese Academy of Forestry, caf.pang@gmail.com
Data from the GLAS sensor can accurately estimate forest canopy height but application of the data is complicated in four ways: (1) there is no data product that combines all the vegetation relevant information produced by the sensor, (2) height estimates are biased on sloped terrain and require calibration, (3) there are no established methods for ensuring spatial and temporal consistency, and (4) the sensor samples the earth’s surface but does not create the wall-to-wall raster coverages expected by end-users. The first of these complications is specific to ICESat data, but any spaceborne lidar mission designed to map ecosystem structure must address the final three.
In addition to creating a data product that combines all of the sensor’s vegetation relevant information, the ICESat Vegetation Product (IVP) project addressed the final three requirements. We identified an index of forest height (the crown-area-weighted height of dominant and co-dominant crowns- Loreycd) that can be estimated from field inventory, airbone small-footprint lidar and spaceborne large-footprint waveform recording sensors. The ability to estimate this index from multiple sources allows us an unprecedented flexibility to relate it to regional and national field inventories (which can also be used to estimate aboveground biomass) and to calibrate estimates of the index from easily obtained airborne data collections.
Estimates of Loreycd require that background noise and return signal be separated with the use of a threshold. While airborne waveform recording instruments can adopt a mission specific threshold, with a long lifetime mission the effect of changing characteristics of the laser over time must be considered along with changes in sensor sensitivity, atmospheric conditions and solar background strength. Coincident pairs of waveform observations collected within and between observation periods were identified and the difference between the two sets of waveform indices was minimized using optimization. This allowed for comparisons between observations from all possible pairs of observation periods and led to an approach based on estimating threshold values from signal-to-noise ratios.
For the foreseeable future, spaceborne lidar sensors will remain capable of sampling no more than a fraction of the earth’s vegetated regions. The availability of wall-to-wall coverage of ecosystem structure would accelerate the incorporation of these data into mapping and modeling. This will require combining the lidar and a second data source with wall-to-wall coverage such as polarmetric or interferrometric SAR; however no global dataset of these data sources are currently available. For the IVP raster product we use multi-temporal MODIS data processed using image segmentation. Source data and texture indices were used to estimate mean heights derived from those GLAS observations that fell within individual patches. Equations to estimate patch height had correlation coefficients of about 0.7 and residuals with RMSEs of about 4m; these varied by ecoregion. A robust method of verification resulted in independent training and testing datasets that had correlation coefficients and RMSEs within 10% of each other. Draft versions of a global map of Loreycd and the individual GLAS observations are available through the website ceal.cnr.colostate.edu
Presentation Type: Poster
Poster Session: Ecosystems Science
NASA TE Funded Awards Represented:
Lefsky, Michael
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