Establishing a Baseline for Regional Scale Monitoring of Eelgrass (Zostera marina) Habitat on the Lower Alaska Peninsula

Remote Sensing

Kyle R. Hogrefe¹  David H. Ward¹  Tyrone F Donnelly¹  Niels Dau³  Santonu Goswami²  Daniel J. Hayes²  Guido Grosse²  Benjamin Jones² 

[1] Alaska Science Center, US Geological Survey, 4210 University Drive, Anchorage, AK 99508, USA; E-Mails:Alaska Science Center, US Geological Survey, 4210 University Drive, Anchorage, AK 99508, USA;;Migratory Bird Management, US Fish and Wildlife Service, 1011 E. Tudor Road, Anchorage, AK 99503, USA; E-Mail:

关键词: remote sensing;    satellite imagery;    Landsat;    classification;    habitat mapping;    isodata;    maximum likelihood;    Zostera marina;    eelgrass;    monitoring program;   

DOI  :  10.3390/rs61212447

来源: mdpi

【 摘 要 】

Seagrass meadows, one of the world’s most widespread and productive ecosystems, provide a wide range of services with real economic value. Worldwide declines in the distribution and abundance of seagrasses and increased threats to coastal ecosystems from climate change have prompted a need to acquire baseline data for monitoring and protecting these important habitats. We assessed the distribution and abundance of eelgrass (Zostera marina) along nearly 1200 km of shoreline on the lower Alaska Peninsula, a region of expansive eelgrass meadows whose status and trends are poorly understood. We demonstrate the effectiveness of a multi-scale approach by using Landsat satellite imagery to map the total areal extent of eelgrass while integrating field survey data to improve map accuracy and describe the physical and biological condition of the meadows. Innovative use of proven methods and processing tools was used to address challenges inherent to remote sensing in high latitude, coastal environments. Eelgrass was estimated to cover ~31,000 ha, 91% of submerged aquatic vegetation on the lower Alaska Peninsula, nearly doubling the known spatial extent of eelgrass in the region. Mapping accuracy was 80%–90% for eelgrass distribution at locations containing adequate field survey data for error analysis.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.