基于偏振植被指数的植被-土壤混合像元室内实验研究

doi:10.3724/SP.J.1047.2017.00374

摘要/Abstract

摘要：

混合像元是遥感影像中普遍存在的一种现象,对其组成和各成分比例的反演一直是遥感研究中的重难点,而国内利用偏振植被指数对混合像元的研究几乎没有涉及。本次研究通过对不同面积比例的植被-土壤混合像元偏振反射高光谱特征进行分析,讨论不同条件下的植被-土壤混合像元偏振高光谱特性,并利用偏振反射比计算了12种0°偏振态下的偏振植被指数,分别构建了植被指数与植被面积比例以及光谱特征参数与植被面积比例的数学模型。结果表明,混合像元中植被面积比例和偏振角均对其偏振高光谱有一定的影响;865 nm的偏振反射比与植被占像元面积比例的相关性最好,采用多项式进行拟合时,其决定系数达到0.99,适合进行植被占像元面积比例的反演;偏振光谱“红边”处的一阶微分值与植被像元比例存在良好的线性相关,R²=0.974;植被面积比例与植被指数和光谱特征参数呈现良好的相关关系,其中P-DVI和光谱吸收指数（SAI）与植被面积比例的拟合效果最好,决定系数分别为0.99以及0.94,适合进行植被-土壤混合像元中植被面积比例的反演。

关键词: 偏振植被指数, 混合像元, 偏振高光谱, SAI, 微分光谱

Abstract:

In remote sensing images, mixed pixel is a common phenomenon. The inversion of component composition and proportion of mixed pixels has been a key and difficult point in remote sensing research. Besides, the study of the mixed pixel using polarization vegetable index has not been conducted in China, yet. This study analyzed the hyperspectral characteristics of polarized reflections of vegetation-soil mixed pixels in different area ratios and discussed the hyperspectral characteristics under different conditions. We used the polarized reflection ratios to calculate the polarization vegetation indices of 12 types of 0 degree polarization and constructed the mathematical model of vegetation area ratio related to spectral characteristic parameters and vegetation index. The results show that vegetation area ratio and polarization angle have certain influence on hyper-spectrum of polarization of mixed pixels. The correlation between polarized reflection ratio of 865nm and the proportion of the vegetation is the best. When the polynomial fitting is applied, the coefficient of determination is up to 0.99. It implies this method is suitable for the inversion of the proportion of vegetation in pixels. With the proportion of vegetation there is a good linear correlation of first order differential of the polarization spectrum on "red edge",R- square = 0.974. Spectral characteristic parameters and vegetation index have good correlations with vegetation area ratio with the P-DVI and spectral absorption index (SAI) showing the best fitting goodness of vegetation area ratio (the coefficients of determination are 0.99 and 0.94, respectively). It implies this method is suitable for the inversion of vegetation area in vegetation-soil mixed pixels.

Key words: polarization vegetation index, mixed pixel, polarization hyper-spectrum, SAI, differential spectrum

陈星任, 韩阳, 王家琪, 卢珍. 基于偏振植被指数的植被-土壤混合像元室内实验研究[J]. 地球信息科学学报, 2017, 19(3): 374-381.DOI:10.3724/SP.J.1047.2017.00374

CHEN Xingren,HAN Yang,WANG Jiaqi,LU Zhen. Indoor Experimental Study on Vegetation-soil Mixed Pixels based on Polarization Vegetation Index[J]. Journal of Geo-information Science, 2017, 19(3): 374-381.DOI:10.3724/SP.J.1047.2017.00374

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植被指数	名称	公式
P-NDVI	归一化植被指数	(R₈₀₀-R₆₇₅)/(R₈₀₀+R₆₇₅)
P-RVI	比值植被指数	R₈₀₀/R₆₇₅
P-DVI	差值植被指数	R₈₀₀-R₆₇₅
P-MSR	优化比值植被指数	(R₈₀₀/R₆₇₅-1)/(R₈₀₀/R₆₇₅+1)^1/2
P-FNDVI	全波段归一化植被指数	(R₉₃₀-R₅₁₅)/(R₉₃₀+R₅₁₅)
P-FRVI	全波段比值植被指数	R₇₆₅-R₅₈₅
P-FDVI	全波段差值植被指数	R₁₂₃₀-R₁₁₀₀
P-EVI	增强型植被指数	2.5(R₈₀₀-R₆₇₅)/(R₈₀₀+6R₆₇₅-7.5R₄₅₇+1)
P-HJVI	环境植被指数	2(R₈₀₀-R₆₇₅)/(7R₅₅₀-7.5R₄₅₇+0.9)
P-TVI	转换植被指数	((R₈₀₀-R₆₇₅)/(R₈₀₀+R₆₇₅))^1/2+0.5
P-RDVI	再归一化植被指数	((R₈₀₀-R₆₇₅)(R₈₀₀-R₆₇₅)/(R₈₀₀+R₆₇₅))^1/2
P-WDRVI	宽动态植被指数	(0.15R₈₀₀-R₆₇₅)/(0.15R₈₀₀+R₆₇₅)

波段/nm	函数类型Function Type	线性方程Linear Equation	R²
490	线性	Y=0.0759X+0.07243	0.660
	多项式	Y=0.19086X ²-0.13881X+0.11765	0.924
	指数	Y=0.07976e^0.60985^x	0.674
670	线性	Y=0.00952X+0.14264	0.036
	多项式	Y=0.15924X ²-0.16962X+0.17996	0.670
	指数	Y=0.14286e^0.05444^x	0.053
865	线性	Y=0.42943X+0.14957	0.940
	多项式	Y=0.40419X ²-0.02529X+0.2443	0.990
	指数	Y=0.20129e^1.0903^x	0.972

	植被比例
	1/8	2/8	3/8	4/8	5/8	6/8	7/8	9/9
波段位置/nm	718	719	720	723	725	721	722	722

植被指数	线性方程	R²
P-NDVI	Y=0.44855X+0.15725	0.95
P-RVI	Y=2.6253X+1.0798	0.96
P-DVI	Y=0.46314X+0.03518	0.99
P-MSR	Y=0.22428X+0.07863	0.95
P-FNDVI	Y=0.16978X+0.41284	0.79
P-FRVI	Y=1.8486X+1.4331	0.92
P-FDVI	Y=-0.07629X+0.02629	0.92
P-EVI	Y=0.4X+0.0237	0.98
P-HJVI	Y=0.3264X+0.0399	0.98
P-TVI	Y=0.2243X+0.5786	0.96
P-RDVI	Y=4.6949X-0.1587	0.94
P-WDRVI	Y=0.4167X-0.6901	0.96

植被面积比例	吸收谷波长位置/nm	波段范围 /nm	吸收谷宽度 /nm
1/8	1424	1320~1637	317
2/8	1422	1313~1593	280
3/8	1422	1313~1646	331
4/8	1435	1314~1670	356
5/8	1455	1315~1670	355
6/8	1450	1272~1658	386
7/8	1453	1262~1662	400
8/8	1450	1282~1663	381