摘要
Spartina alterniflora is one of exotic plants along the coastal region in China. It was introduced as an important engineering approach to ecological restoration in the later 1970 s. However, owing to its good adaptability and strong reproductive capacity, the introduced species is explosively spreading along the coastal region quickly and resulting in a significant impact on the health and safety of coastal wetland ecosystems. It is imperative to quantify the spatial extent and the rate of S. alterniflora sprawl in order to assess its ecological damages and economic impacts. Remote sensing techniques have been used to address these challenges but large unsuccessful due to mixed spectral properties. In this study, a hybrid method was proposed for S. alterniflora detection using medium resolution remote sensing images by integrating both spatial and spectral features of S. alterniflora. The hybrid method consists of two phases：（1） delineation of intertidal zone as the potential area of S. alterniflora distribution and（2） extraction of S. alterniflora fraction distribution with a mixture pixel analysis. The proposed method was tested at the Xiangshan Bay on the east coastal region of Zhejiang Province, China, and mapped the spatial extent of S. alterniflora with Landsat datasets in the 2003, 2009 and 2014. The results showed that, the S. alterniflora has grown exponentially over past 10 years. In 2003, the total area of S. alterniflora was about 590 hm2, but quickly reached to 1 745 hm2 in 2009, and 5 715 hm2 in 2014. With a rate of approximately 10-folds growth within a decade, the invasive species almost occupied all muddy beaches to become the most dominant coastal salt vegetation in this region. It is believed that the strong biological reproductive capacity was the primary reason for such quick spread and at the same time human reclamation activities were also believed to have facilitated the environmental conditions for S. alterniflora sprawl.
Spartina alterniflora is one of exotic plants along the coastal region in China. It was introduced as an important engineering approach to ecological restoration in the later 1970 s. However, owing to its good adaptability and strong reproductive capacity, the introduced species is explosively spreading along the coastal region quickly and resulting in a significant impact on the health and safety of coastal wetland ecosystems. It is imperative to quantify the spatial extent and the rate of S. alterniflora sprawl in order to assess its ecological damages and economic impacts. Remote sensing techniques have been used to address these challenges but large unsuccessful due to mixed spectral properties. In this study, a hybrid method was proposed for S. alterniflora detection using medium resolution remote sensing images by integrating both spatial and spectral features of S. alterniflora. The hybrid method consists of two phases：（1） delineation of intertidal zone as the potential area of S. alterniflora distribution and（2） extraction of S. alterniflora fraction distribution with a mixture pixel analysis. The proposed method was tested at the Xiangshan Bay on the east coastal region of Zhejiang Province, China, and mapped the spatial extent of S. alterniflora with Landsat datasets in the 2003, 2009 and 2014. The results showed that, the S. alterniflora has grown exponentially over past 10 years. In 2003, the total area of S. alterniflora was about 590 hm2, but quickly reached to 1 745 hm2 in 2009, and 5 715 hm2 in 2014. With a rate of approximately 10-folds growth within a decade, the invasive species almost occupied all muddy beaches to become the most dominant coastal salt vegetation in this region. It is believed that the strong biological reproductive capacity was the primary reason for such quick spread and at the same time human reclamation activities were also believed to have facilitated the environmental conditions for S. alterniflora sprawl.
基金
The National Natural Science Foundation of China under contract Nos 41201460,61375002 and 61473286
the Special Research Project for the Commonwealth of the Ministry of Water Resources of the People’s Republic of China under contract No.201201092
the National Science and Technology Pillar Program under contract No.2015BAJ02B01
