Mapping changing distributions of dominant species in oil-contaminated salt marshes of Louisiana using imaging spectroscopy

REMOTE SENSING OF ENVIRONMENT

卷:182

Article

Beland, Michael^1,2  Roberts, Dar A.²  Peterson, Seth H.²  Biggs, Trent W.¹  Kokaly, Raymond F.³  Piazza, Sarai⁴  Roth, Keely L.⁵  Khanna, Shruti⁵  Ustin, Susan L.⁵ 

[1] San Diego State Univ, Dept Geog, San Diego, CA 92182 USA

[2] Univ Calif Santa Barbara, Dept Geog, Santa Barbara, CA 93106 USA

[3] US Geol Survey, MS 973,Box 25046, Denver, CO 80225 USA

[4] US Geol Survey, Livestock Show Off, Baton Rouge, LA 70803 USA

[5] Univ Calif Davis, Dept Land Air & Water Resources, Davis, CA 95616 USA

关键词: AVIRIS;    Deepwater Horizon;    Oil spills;    Image classification;    Dominant species mapping;    Salt marsh vegetation;    Canonical discriminant analysis;    Hyperspectral remote sensing;   

DOI  :  10.1016/j.rse.2016.04.024

来源: Elsevier

【 摘 要 】

The April 2010 Deepwater Horizon (DWH) oil spill was the largest coastal spill in U.S. history. Monitoring subsequent change in marsh plant community distributions is critical to assess ecosystem impacts and to establish future coastal management priorities. Strategically deployed airborne imaging spectrometers, like the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), offer the spectral and spatial resolution needed to differentiate plant species. However, obtaining satisfactory and consistent classification accuracies over time is a major challenge, particularly in dynamic intertidal landscapes. Here, we develop and evaluate an image classification system for a time series of AVIRIS data for mapping dominant species in a heavily oiled salt marsh ecosystem. Using field-referenced image endmembers and canonical discriminant analysis (CDA), we classified 21 AVIRIS images acquired during the fall of 2010, 2011 and 2012. Classification results were evaluated using ground surveys that were conducted contemporaneously to AVIRIS collection dates. We analyzed changes in dominant species cover from 2010 to 2012 for oiled and non-oiled shorelines. CDA discriminated dominant species with a high level of accuracy (overall accuracy = 82%, kappa = 0.78) and consistency over three imaging dates (overall(2010) = 82%, overall(2011) = 82%, overall(2012) = 88%). Marshes dominated by Spartina alterniflora were the most spatially abundant in shoreline zones (<= 28 m from shore) for all three dates (2010 = 79%, 2011 = 61%, 2012 = 63%), followed by Juncus roemerianus (2010 = 11%, 2011 = 19%, 2012 = 17%) and Distichlis spicata (2010 = 4%, 2011 = 10%, 2012 = 7%). Marshes that were heavily contaminated with oil exhibited variable responses from 2010 to 2012. Marsh vegetation classes converted to a subtidal, open water class along oiled and non-oiled shorelines that were similarly situated in the landscape. However, marsh loss along oil-contaminated shorelines doubled that of non-oiled shorelines. Only S. alterniflora dominated marshes were extensively degraded, losing 15% (354,604 m(2)) cover in oiled shoreline zones, suggesting that S. alterniflora marshes may be more vulnerable to shoreline erosion following hydrocarbon stress, due to their landscape position. (C) 2016 Elsevier Inc. All rights reserved.

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