Tracking the phenology and expansion of Spartina alterniflora coastal wetland by time series MODIS and Landsat images

Abstract

Accurate information on phenology of Spartina alterniflora is basic for observing its growing condition in native and invasive places. Remote sensing (RS) can be used to analyse and monitor vegetation at a large spatial and long time scale. In this study, RS is used to explore phenology of coastal wetland vegetation (Reed, Suaeda salsa and Spartina alterniflora) based on time series data of four spectral indices (SI): Normalized Difference Vegetation Index (NDVI); Enhanced Vegetation Index (EVI); Land Surface Water Index (LSWI) and Modified Normalized Difference Moisture Index (mNDWI). These SIs were calculated based on Moderate Resolution Imaging Spectroradiometer (MODIS) and Land Satellite (Landsat) images, respectively. Phenology (including growing season and non-growing season) of Spartina alterniflora based on SIs to track its dynamic expansion since it invaded in southern Yellow Sea (Jiangsu, Yancheng), China through observing Landsat sub-pixels in per MODIS pixel. We also developed a new phenology-based algorithm to identify Spartina alterniflora from 1984 to 2015. The results show that Spartina alterniflora has a longer growth circle (around 286 days in a year) and higher productivity (about 0.6–0.8 NDVI) than the other salt marsh vegetation. The way of observing vegetation phenology on RS, and then developing a new phenology-based algorithm to track coastal wetland including invasive species—like Spartina alterniflora can support the studies of biological expansion, coastal wetland biodiversity conservation, and even global carbon cycling and climate change further.