English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The overwhelming spread of <italic>Spartina alterniflora (S. alterniflora)</italic> (smooth cordgrass) over recent decades has put many native plant communities and coastal environments at risk. Therefore, long-term monitoring of <italic>S. alterniflora</italic> dynamics is necessary to better understand and manage the invasion of the species. However, it is difficult to map <italic>Spartina</italic> saltmarshes in China on an annual or multiyear epoch basis. To address this issue, we developed a classification approach integrating Google Earth Engine (GEE) and object-based hierarchical random forest (RF) classification, and we applied this approach to quantify the expansion and dieback of <italic>S. alterniflora</italic> at Dafeng Milu National Nature Reserve, Jiangsu, China during 1993&#x2013;2020. Results showed that the area of <italic>S. alterniflora</italic> expanded from 24.48 ha in 1993 to 1564.96 ha in 2010. However, after ecological hydrological engineering and an increase in <italic>Elaphures davidianus</italic> (P&#x00E8;re David&#x0027;s deer) numbers in 2011, the <italic>S. alterniflora</italic> area decreased significantly to 944.28 ha in 2020. During 2011&#x2013;2020, the <italic>S. alterniflora</italic> area decreased substantially at a rate of 67 ha per year and by 86&#x0025; in one area studied in Dafeng Milu National Nature Reserve. In 2020, the 944.28 ha of <italic>S. alterniflora</italic> in the reserve was mainly distributed in mudflats by the sea. Overall, these results show that it is feasible to identify <italic>S. alterniflora</italic> using the GEE platform and object-based hierarchical RF classification; moreover, this approach could improve understanding and management of this invasion species.

ieee journal of selected topics in applied earth observations and remote sensing

Quantifying the Long-Term Expansion and Dieback of <italic>Spartina Alterniflora</italic> Using Google Earth Engine and Object-Based Hierarchical Random Forest Classification

Quantifying the Long-Term Expansion and Dieback of Spartina Alterniflora Using Google Earth Engine and Object-Based Hierarchical Random Forest Classification