{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T10:19:57Z","timestamp":1772533197468,"version":"3.50.1"},"reference-count":40,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2017,6,1]],"date-time":"2017-06-01T00:00:00Z","timestamp":1496275200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>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\u2019s 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 &lt; 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.<\/jats:p>","DOI":"10.3390\/rs9060547","type":"journal-article","created":{"date-parts":[[2017,6,1]],"date-time":"2017-06-01T10:36:36Z","timestamp":1496313396000},"page":"547","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Post-Deepwater Horizon Oil Spill Monitoring of Louisiana Salt Marshes Using Landsat Imagery"],"prefix":"10.3390","volume":"9","author":[{"given":"Yu","family":"Mo","sequence":"first","affiliation":[{"name":"Department of Environmental Science and Technology, University of Maryland, 1426 Animal Sci.\/Ag. Engr. Bldg., College Park, MD 20742, USA"}]},{"given":"Michael","family":"Kearney","sequence":"additional","affiliation":[{"name":"Department of Environmental Science and Technology, University of Maryland, 1426 Animal Sci.\/Ag. Engr. Bldg., College Park, MD 20742, USA"}]},{"given":"J.","family":"Riter","sequence":"additional","affiliation":[{"name":"Department of Environmental Science and Technology, University of Maryland, 1426 Animal Sci.\/Ag. Engr. Bldg., College Park, MD 20742, USA"}]}],"member":"1968","published-online":{"date-parts":[[2017,6,1]]},"reference":[{"key":"ref_1","unstructured":"McNutt, M., Camilli, R., Guthrie, G., Hsieh, P., Labson, V., Lehr, B., Maclay, D., Ratzel, A., and Sogge, M. (2011). 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