Analysis of Early Forest Regrowth in the Eastern US using IceSAT/GLAS-LiDAR and Landsat- spectral data.
Abstract
Forest-cover conversion, disturbance, and recovery have been proposed as key mechanisms for transferring carbon between the land surface and the atmosphere, yet the area and timing of these processes are still poorly quantified. Combining remote sensing products such as LiDAR and Landsat data can help quantify the amount, area and timing of forest disturbance along with estimated rate of recovery. This study examines the use of NASA's Geoscience Laser Altimeter System (GLAS) for assessing post-disturbance forest re-growth rates via "space for time" substitution -GLAS observations from a single year combined with 20+ year Landsat disturbance record. Landsat image time series from three locations in the Eastern US (Maine, Virginia, Mississippi) were analyzed to obtain the timing and magnitude of major disturbance events for the 1984-2003 period. GLAS waveforms from 2003 were extracted for these patches and heights were determined via visual inspection of the waveform. Only "high magnitude" (stand clearing) disturbance events were selected, and only from regions of low topographic relief (< 5 degrees). Height Measurements of forest stands undisturbed over the last 20 years were also obtained along the latitudinal transect. Results show a progression in stand height from youngest to oldest stand. Regrowth rates vary with ecoregion and climate, from 0.6 m/yr (Maine) to 1.0-1.2 m/yr (Virginia - Mississippi). The latter rates compare favorably with known values for southeastern loblolly pine. Although the precision of an individual GLAS-derived height is relatively low, this study demonstrates that by combining multiple space-for-time observations, we can measure landscape-scale growth rates on order of ~1 m/yr. Decreasing the diameter of the lidar footprint in future land missions may help to increase the accuracy of forest structure measurements.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2007
- Bibcode:
- 2007AGUFM.B43C1466D
- Keywords:
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- 0439 Ecosystems;
- structure and dynamics (4815);
- 0480 Remote sensing;
- 1632 Land cover change