Table 1.

A brief summary on image data sources and methods used in previous studies for classifying and mapping Spartina saltmarsh.

Methods		Multi-spectral images		Hyperspectral images	Multi-source images
		VHSR	HSR
Visual interpretation		Liu et al. (2017)	Zhang et al. (2004); Wan et al. (2014)
Images and spatial statistics of images	MLC	Liu et al. (2016);	Li et al. (2006);		Chust et al. (2008);
		Ai et al. (2017)	Huang and Zhang(2007b); Lu and Zhang (2013); Zhang et al. (2017)		Hladik et al. (2013)
	NN	Morris et al. (2005)
	SVM	Ai et al. (2017)	Wang et al. (2015); Liu et al. (2018); Mao et al. (2019)
	RB/DT/RF	Wan et al. (2014); Lin et al. (2015); Wang et al. (2015)	Zuo et al. (2012); Sun et al. (2016)		Hladik et al. (2013); van Beijma et al. (2014)
	SMA		Zhu et al. (2016)	Rosso et al. (2005)
Pixels and temporal statistics of pixels			This study

Note: VHSR: Very high spatial resolution satellite image (e.g., GF-1); HSR: high spatial resolution satellite image (e.g., Landsat); MLC: Maximum likelihood classification; NN: Artificial Neural Network; SVM: Support vector machine; RB: Rule-based; DT: Decision tree; RF: Random forest; SMA: Spectral mixture analysis.