基于图谱耦合的高寒湿地土地类型识别与分类

基于图谱耦合的高寒湿地土地类型识别与分类

聂诗音, 刘严松, 李会玲, 薛凯伦, 沈杜衡, 何博宇

Identification and classification of land types of alpine wetlands based on spectral coupling

NIE Shiyin, LIU Yansong, LI Huiling, XUE Kailun, SHEN Duheng, HE Boyu

表1 分类特征变量表

Tab.1 Classification feature variable table

特征类型		特征名称	计算方法或描述
光谱特征	光谱波段	波段	蓝、绿、红、近红外、短波红外
	光谱指数	NDVI	NDVI = (NIR-Red) / (NIR+Red)
		RVI	RVI=NIR / Red
		DVI	DVI=NIR-Red
		MCARI	MCARI =[(NIR-Red)-0.2×(NIR-Green)]×(NIR / Red)
		NDWI	NDWI=(Green-NIR) / (Green+NIR)
		MNDWI	MNDWI = (Green-Mir) / (Green-Mir)
		SWI	SWI = Blue+Red-NIR
纹理特征		均值(Mean)	$M e a n = \sum_{i = 0}^{k} \sum_{j = 0}^{k} p (i, j) \times i$
		方差(Variance)	$V a r i a n c e = \sum_{i = 0}^{k} \sum_{j = 0}^{k} p (i, j) \times {(i - M e a n)}^{2}$
		协同性(Homogeneity)	$H o m o g e n e i t y = \sum_{i = 0}^{k} \sum_{j = 0}^{k} p (i, j) \times \frac{1}{1 + {(i - j)}^{2}}$
		对比度(Contrast)	$C o n t r a s t = \sum_{i = 0}^{k} \sum_{j = 0}^{k} p (i, j) \times {(i - j)}^{2}$
		相异性(Dissimilarity)	$D i s s i m i l a r i t y = \sum_{i = 0}^{k} \sum_{j = 0}^{k} p (i, j) \times \|i - j\|$
		信息熵(Entropy)	$E n t r o p y = \sum_{i = 0}^{k} \sum_{j = 0}^{k} p (i, j) \times l o g p (i, j)$
		二阶矩(Second Moment)	$S e c o n d ? M o m e n t = \sum_{i = 0}^{k} \sum_{j = 0}^{k} p (i, j)$
		相关性(Correlation)	$C o r r e l a t i o n = \sum_{i = 0}^{k} \sum_{j = 0}^{k} \frac{(i - M e a n) \times (j - M e a n) \times p {(i, j)}^{2}}{V a r i a n c e}$
地形特征		海拔	ASTER GDEM V2数据集
		坡度	ASTER GDEM V2数据集
		坡向	ASTER GDEM V2数据集