高光谱与LiDAR数据融合研究——以黑河中游张掖绿洲农业区精细作物分类为例

杨思睿, 薛朝辉, 张玲, 苏红军, 周绍光

Fusion of hyperspectral and LiDAR data: A case study for refined crop classification in agricultural region of Zhangye Oasis in the middle reaches of Heihe River

Sirui YANG, Zhaohui XUE, Ling ZHANG, Hongjun SU, Shaoguang ZHOU

表1 基于2种形式的SMLR对不同单一特征EMAP和EAP分类的精度与Kappa系数

Tab.1 Classification accuracy and Kappa coefficient for different single features (EMAP,EAP) based on SMLR in two forms(%)

序号	类别	linear			RBF-MRF
序号	类别	X^h	EMAP(X^h)	EAP(X^L)	X^h	EMAP(X^h)	EAP(X^L)
1	玉米	87.20	87.28	54.16	94.59	86.40	70.53
2	韭菜	88.92	92.13	65.51	96.54	98.10	87.96
3	菜花	84.78	93.10	79.33	85.29	94.47	91.35
4	菜椒	87.02	84.75	79.48	95.02	97.14	74.17
5	土豆	94.09	84.53	53.07	97.70	88.08	42.57
6	冬笋	96.93	95.86	90.75	98.47	98.98	83.14
7	西瓜	81.92	87.55	72.83	95.45	80.50	66.68
8	建设用地	77.47	75.42	31.26	97.87	97.53	53.85
OA		84.41	83.96	53.09	95.08	91.70	66.70
AA		87.29	87.58	65.80	95.12	92.65	71.28
Kappa		78.82	78.24	41.45	93.10	88.59	56.37