Dubayah, Ralph: University of Maryland (Project Lead)
Blair, Bryan: NASA GSFC (Co-Investigator)
Hurtt, George: University of Maryland (Participant)
Swatantran, Anuradha (Anu): University of Maryland (Participant)
Project Funding:
2004 - 2007
NRA: 2003 NASA: Interdisciplinary Research in Earth Science
Funded by NASA, Other US Funding: NASA
Abstract:
The overall science goal of this proposal is to link lidar remote sensing of forest structure with field studies and ecosystem modeling across a range of environmental gradients to improve land surface carbon predictions, and to explore the effects of this structure on species richness and distributions. In particular we seek to answer the following two methodological questions: (1) How can changes in forest carbon stocks and associated fluxes be observed over time using a combined lidar remote sensing/modeling approach? (2) How can lidar remote sensing be used to discover and characterize forest spatial and vertical structure relevant to species distribution and richness? The activities of this research fall into three categories: (1) the production of a time series of forest structure from lidar and other remote sensing data; (2) the modeling of carbon stocks and fluxes using an ecosystem model as initialized with lidar data; and (3) application of the derived and modeled products for assessments of biodiversity. Airborne lidar LVIS data sets were acquired in 1998-1999. Areas flown included La Selva Biological Station (Costa Rica), the Hubbard Brook, Harvard Forest, and Coweeta LTER sites, Bartlett, Duke, and Patuxent forests, as well as extensive flying in the Sierra National Forest in California. Comprehensive field data were also collected at many of these areas. The first major effort of our research will be to refly these existing field sites with the addition of Sevilleta and the HJ Andrews LTER sites. This will then provide a time series of lidar observations across a range of environmental gradients separated by at least 5 years. These new data will be processed, the existing lidar data processed, and a variety of structure products derived at 25 m resolution that will provide the foundation for addressing our science goals. The spatial and temporal distribution of aboveground carbon stocks at all sites will be produced first from lidar data and plot-level ground observations. Next, lidar retrievals of canopy height and other structure will be used to initialize Ecosystem Demography (ED) model. ED model outputs of stocks and fluxes will then be determined (at 1 hectare level) and analyzed. The wealth of field data on species distribution and richness at the LTER and other sites will be used with this forest structure data, along with ED model outputs, to explore questions concerning the relationship of structure and production to biotic diversity and habitat characterization. First, lidar data, along with other remote sensing observations, will be used to generate maps of forest structure that are believed to be relevant for specific species and these then related to species presence, absence, distribution, abundance and richness. Next, field data on species richness will be merged with forest structure data, including carbon stocks, to explore potential relationships between diversity and structure. Lastly, the spatial variability of a productivity surrogate, the change in biomass between the two lidar data acquisition dates, along with ED estimates of productivity, will be used to address the interrelationship between productivity and species richness.
Publications:
Dubayah, R. O., Sheldon, S. L., Clark, D. B., Hofton, M. A., Blair, J. B., Hurtt, G. C., Chazdon, R. L. 2010. Estimation of tropical forest height and biomass dynamics using lidar remote sensing at La Selva, Costa Rica. Journal of Geophysical Research: Biogeosciences. 115(G2). DOI: 10.1029/2009JG000933
Fricker, G. A., Saatchi, S. S., Meyer, V., Gillespie, T. W., Sheng, Y. 2012. Application of Semi-Automated Filter to Improve Waveform Lidar Sub-Canopy Elevation Model. Remote Sensing. 4(6), 1494-1518. DOI: 10.3390/rs4061494
Goetz, S. J. 2006. REMOTE SENSING OF RIPARIAN BUFFERS: PAST PROGRESS AND FUTURE PROSPECTS. Journal of the American Water Resources Association. 42(1), 133-143. DOI: 10.1111/j.1752-1688.2006.tb03829.x
GOETZ, S., STEINBERG, D., DUBAYAH, R., BLAIR, B. 2007. Laser remote sensing of canopy habitat heterogeneity as a predictor of bird species richness in an eastern temperate forest, USA. Remote Sensing of Environment. 108(3), 254-263. DOI: 10.1016/j.rse.2006.11.016
Hofton, M. A., Malavassi, E., Blair, J. B. 2006. Quantifying recent pyroclastic and lava flows at Arenal Volcano, Costa Rica, using medium-footprint lidar. Geophysical Research Letters. 33(21). DOI: 10.1029/2006gl027822
Hofton, M. A., Malavassi, E., Blair, J. B. 2006. Quantifying recent pyroclastic and lava flows at Arenal Volcano, Costa Rica, using medium-footprint lidar. Geophysical Research Letters. 33(21). DOI: 10.1029/2006gl027822
2008 NASA Carbon Cycle & Ecosystems Joint Science Workshop Posters
- Laser Remote Sensing of Canopy Habitat Heterogeneity as a Predictor of Bird Diversity and Abundance
-- (Scott Goetz, Daniel Steinberg, Ralph Dubayah, Richard Holmes, Matthew Betts, Patrick Doran)
[abstract]
- Topography, Vegetation Structure, and Ice Studies Using NASAs LVIS Sensor: An Airborne, Wide-Swath, Full-Waveform, Imaging Lidar
-- (Bryan Blair, Michelle Hofton, David Rabine)
[abstract]
- Using GLAS as a tool to detect relative changes in forest structure caused by the 2005 hurricane season.
-- (Katelyn Anne Dolan, George Hurtt, Jeff Chambers, Ralph Dubayah, Jeff Masek)
[abstract]
More details may be found in the following project profile(s):
