Methane Emission From Global Lakes: New Spatiotemporal Data and Observation-Driven Modeling of Methane Dynamics Indicates Lower Emissions.

Lakes have been highlighted as one of the largest natural sources of the greenhouse gas methane (CH) to the atmosphere. However, global estimates of lake CH fluxes over the last 20 years exhibit widely different results ranging from 6 to 185 Tg CH yr, which is to a large extent driven by differences in lake areas and thaw season lengths used. This has generated uncertainty regarding both lake fluxes and the global CH budget.

Evaluation of modelled net primary production using MODIS and landsat satellite data fusion.

Background: To improve estimates of net primary production for terrestrial ecosystems of the continental United States, we evaluated a new image fusion technique to incorporate high resolution Landsat land cover data into a modified version of the CASA ecosystem model. The proportion of each Landsat land cover type within each 0.004 degree resolution CASA pixel was used to influence the ecosystem model result by a pure-pixel interpolation method.

Alaska ecosystem carbon fluxes estimated from MODIS satellite data inputs from 2000 to 2010.

Background: Trends in Alaska ecosystem carbon fluxes were predicted from inputs of monthly MODerate resolution Imaging Spectroradiometer (MODIS) vegetation index time-series combined with the NASA-CASA (Carnegie Ames Stanford Approach) carbon cycle simulation model over the past decade. CASA simulates monthly net ecosystem production (NEP) as the difference in carbon fluxes between net primary production (NPP) and soil microbial respiration (Rh).

Results: Model results showed that NEP on a unit area basis was estimated to be highest (> +10 g C m-2 yr-1) on average over the period 2000 to 2010 within the Major Land Resource Areas (MRLAs) of the Interior Brooks Range Mountains, the Arctic Foothills, and the Western Brooks Range Mountains.

Forest production predicted from satellite image analysis for the Southeast Asia region.

Background: The objective of this study was to demonstrate a new, cost-effective method to define the sustainable amounts of harvested wood products in Southeast Asian countries case studies, while avoiding degradation (net loss) of total wood carbon stocks. Satellite remote sensing from the MODIS sensor was used in the CASA (Carnegie Ames Stanford Approach) carbon cycle model to map forest production for the Southeast Asia region from 2000 to 2010. These CASA model results have been designed to be spatially detailed enough to support carbon cycle assessments in different wooded land cover classes, e.

Carbon fluxes in ecosystems of Yellowstone National Park predicted from remote sensing data and simulation modeling.

Background: A simulation model based on remote sensing data for spatial vegetation properties has been used to estimate ecosystem carbon fluxes across Yellowstone National Park (YNP). The CASA (Carnegie Ames Stanford Approach) model was applied at a regional scale to estimate seasonal and annual carbon fluxes as net primary production (NPP) and soil respiration components. Predicted net ecosystem production (NEP) flux of CO2 is estimated from the model for carbon sinks and sources over multi-year periods that varied in climate and (wildfire) disturbance histories.

Remote sensing-based time-series analysis of cheatgrass (Bromus tectorum L.) phenology.

The western United States is under invasion from cheatgrass (Bromus tectorum L.), an annual grass that alters the pattern of phenology in the ecosystems it infests. This study was conducted to investigate methods for monitoring this invasion.

Net primary productivity of forest stands in New Hampshire estimated from Landsat and MODIS satellite data.

Background: A simulation model that relies on satellite observations of vegetation cover from the Landsat 7 sensor and from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to estimate net primary productivity (NPP) of forest stands at the Bartlett Experiment Forest (BEF) in the White Mountains of New Hampshire.

Results: Net primary production (NPP) predicted from the NASA-CASA model using 30-meter resolution Landsat inputs showed variations related to both vegetation cover type and elevational effects on mean air temperatures. Overall, the highest predicted NPP from the NASA-CASA model was for deciduous forest cover at low to mid-elevation locations over the landscape.