College of Agriculture & Natural Resources

Permanent URI for this communityhttp://hdl.handle.net/1903/1598

The collections in this community comprise faculty research works, as well as graduate theses and dissertations.

Browse

Filters

20172

Settings

Author: search.filters.author.Mo, Yu

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Post-Deepwater Horizon Oil Spill Monitoring of Louisiana Salt Marshes Using Landsat Imagery
    (MDPI, 2017-06-01) Mo, Yu; Kearney, Michael S.; Riter, J. C. Alexis
    The Deepwater Horizon oil spill, the second largest marine oil spill in history, contaminated over a thousand kilometers of coastline in the Louisiana salt marshes and seriously threatened this valuable ecosystem. Measuring the impacts of the oil spill over the large and complex coast calls for the application of remote sensing techniques. This study develops a method for post-Deepwater Horizon oil spill monitoring of the damaged marsh vegetation using Landsat imagery. This study utilizes 10 years of Landsat data, from 2005 to 2014, to examine the longevity of the oil spill’s impacts on the marsh vegetation. AVIRIS data collected between 2010 and 2012 are used to validate the Landsat results. Landsat imagery documents the significant effect of oiling on the Normalized Difference Vegetation Index (NDVI) of the marsh vegetation in 2010 and 2011 (p < 0.01 in both cases). These results are corroborated by the AVIRIS data, which recorded the most severe impact in May 2011 followed by progressive recovery in October 2011 and October 2012. The Landsat imagery, combined with relevant environmental information and appropriate statistical tools, provides a robust and low-cost method for long-term post-oil spill monitoring of the marshes, revealing that the major aboveground impacts (at 30 m scale) of the Deepwater Horizon oil spill on Louisiana salt marshes lasted for two years. The method presented is applicable for other hazardous events whenever pre-event referencing and long-term post-event monitoring are desired, thereby offering an effective and economical tool for disaster management.
  • Thumbnail Image
    Item
    Phenology of coastal marshes in Louisiana from 1984-2014: Long- and short-term variations associated with climate change and disastrous events
    (2017) Mo, Yu; Kearney, Michael S.; Environmental Science and Technology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    The sustainability of coastal ecosystems is of increasing importance given the reliance of the growing coastal population and the threat from rising sea-level. Coastal marshes in Louisiana, similar to other ecosystems located in the major river-dominated deltas in the world, are influenced by various natural and anthropogenic factors. However, the existing studies mostly focus on specific sites and events, and comprehensive studies of the marshes’ responses to different stressors are limited. This study presents a new way to study and compare the broad patterns of ecosystem changes associated with different stressors by examining long-term remote sensing phenology of the marshes. The phenological records of coastal marshes in Louisiana were studied using the Landsat satellite data from 1984 to 2014. The correlation between the Landsat-derived Normalized Difference Vegetation Index (NDVI) and the marsh aboveground biomass was established. A nonlinear mixed model was developed to estimate the key phenological parameters, i.e., peak NDVI, peak NDVI day, and growth duration, of the freshwater, intermediate, brackish, and saline marshes in the Louisiana coast. The impacts of drought and hurricanes were studied by examining multiple events over the study period. The impacts of the Deepwater Horizon oil spill and climate change were investigated using continuous long-term records. The results highlight the vulnerability of different marsh types: the freshwater marshes are quite resilient to different stressors; the intermediate and brackish marshes are more prone to damage from hurricanes and climate change; and the saline marshes are more susceptible to drought and the Deepwater Horizon oil spill. The results also underscore the influences of global climate patterns (i.e., La Niña and climate change) and human interventions (i.e., nutrient loading and oil spill) on the marshes. The findings provide valuable insights for preserving the coastal marshes in Louisiana and other coastal ecosystems suffering similar stresses, and the method presented can be applied to study the key stressors of the other coastal ecosystems, thereby contributing to the sustainable management of coastal ecosystems under the changing climate.