Assessing spatiotemporal characteristics of native and invasive species with multi‐temporal remote sensing images in the Yellow River Delta, China

As the main invasive plant species in the Yellow River Delta, Spartina alterniflora ( S. alterniflora ) has been a great threat to local ecosystems, but there are few studies on the growth scale, habitat structural changes, and expansion pattern of S. alterniflora . In this study, the native and invasive species in the Yellow River Delta were examined for their spatiotemporal characteristics and succession patterns. First, multi‐temporal SENTINEL‐2 and LANDSAT‐8 images from 2018 were selected. A random forest algorithm was used to verify the image spectral band's significance and separability to determine the native and invasive species. Then, the spatiotemporal variation of habitat structure of the species was discussed in depth from the perspective of landscape ecology. Finally, the expansion direction and expansion mode of S. alterniflora were further analyzed. The main results obtained were as follows: (a) SENTINEL‐2 images with red‐edge bands had obvious advantages in vegetation community extraction as compared to LANDSAT‐8 images (SENTINEL‐2, OA = 82.86%, kappa coefficient = 0.79; LANDSAT‐8, OA = 78.77%, kappa coefficient = 0.74). (b) The expansion pattern of the S. alterniflora community became spatially continuous, more regularized, and aggregated over time. (c) The expansion in the north shore mainly faced toward the sea, and the south bank mainly faced toward the land, and this phenomenon was closely related to the sedimentation of the Yellow River Delta. Marginal and external expansion both occurred, but marginal expansion predominated. The results have important theoretical and scientific value for the environmental protection and sustainable development of the entire Yellow River Delta

Biology · Delta · Geography · Habitat · Physical geography · Remote sensing · River delta · Spartina alterniflora · Wetland · Coastal wetland ecosystem dynamics · Environmental Science · Land Use and Ecosystem Services · Remote Sensing in Agriculture · Ecology

• Random Forests

  Open Access•Leo Breiman•Machine Learning•2001

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