-
小麦是世界上总产量位列第二位,仅次于玉米的粮食作物。我国去年全年小麦产量12 617万吨,增产3.5%[1]。小麦大尺度的长势动态监测和产量预估都具有重要的现实意义。鉴于微波对低矮植被尺寸的敏感性及后向散射所携带的植被信息对小麦各参数研究的重要性,需要对小麦微波散射机理进行更详尽的研究,从而提高对小麦各个生长阶段监测的有效性。低矮农作物属于非各向同性介质且结构复杂,各组成部分的形状、大小、高低、厚度和朝向等对微波后向散射都有较大的影响,因此会造成散射机理的不同[2]。辐射传输理论来源于恒星谱的研究,利用电磁波在散射介质中的多次散射、传播与吸收机理对植被进行研究。由辐射传输理论推广而来的矢量辐射传输理论遵从能量守恒定律,具有物理意义明确和能够叠加计算多次散射的特点,适用于散射粒子较稀少,占空比小于0.005的植被和农作物等地物情况[3]。本文采用了文献[4]提出的求解3个函数(散射振幅函数、消光矩阵、相矩阵)以及解矢量辐射传输方程得出相应Mueller矩阵和Stokes矩阵的方法。该方法首先基于散射振幅函数中入射场与散射场的耦合关系,然后求解消光矩阵内散射粒子的散射及吸收系数和背景介质的吸收系数,最后由相矩阵描述散射能量不同方向之间的转移来处理总的后向散射系数。
文献[5]建立的针对森林环境的密歇根微波冠层散射模型以其严密性和准确性获得了广泛的应用,该模型综合考虑了冠层、茎干、地表三层介质的散射作用。文献[6]省略了文献[5]创建模型中的树干层,利用L波段和C波段较好地模拟了小麦后向散射系数。低矮农作物的散射机理研究衍生出的算法模型推进了微波散射机理的发展[7]。文献[8]提出了一个二阶散射模型来研究小麦,但对麦叶和麦穗的作用研究不够深入。文献[3]对农作物植被的电磁散射机理进行了系统研究,推进了散射模型的发展。文献[9-10]利用微波散射测量数据对小麦的后向散射进行了研究,对各个生长阶段的小麦的微波散射进行了分析。本文选取小麦生长阶段中麦穗出现后的两个生长时期灌浆期和成熟期,针对麦穗出现在小麦最上层以及麦穗和麦秆叶的物理属性差别的特点,把麦穗作为独立的一层,进行多层后向散射建模。本文利用AIEM模型模拟随机粗糙地表后向散射[11],使用消光矩阵和相矩阵计算能量衰减和方向变化,利用Mueller矩阵对方程进行解析。
-
模型构建中,小麦冠层被分为麦穗层、麦秆叶层和土壤层。最上层的麦穗简化为椭圆散射粒子,中间层的麦秆和麦叶分别简化为有限长圆柱体和椭圆盘,麦叶设为均匀分布在第二层空间里,土壤层设为随机粗糙面。
小麦含穗生长期冠层散射机理如图 1所示,图中,M1为麦穗层直接后向散射项;M2为土壤随机粗糙面直接后向散射;M3为麦穗层-土壤层-麦秆叶层-麦穗层耦合散射项;M4为麦穗层-麦秆叶层-土壤层-麦秆叶层-麦穗层耦合后向散射项;M5为麦秆叶层-土壤层-麦穗层耦合后向散射项。边界条件:Z=0作为空气和麦穗的分界面;Z=-h作为麦穗和麦秆叶的分界面;Z=-d作为麦秆叶层和土壤随机粗糙面的分界面。在消光矩阵和相矩阵中都引入一个竖直方向上的变量,描述非均匀分布的非球形散射粒子层的全极化散射。
本文采用的求解方法是对三层耦合具有垂直结构随机介质VRT模型进行简化,如图 2所示。根据地表参数和雷达参数计算不含麦穗层的麦秆叶层和土壤层的双层散射[12],从而获得总的向上反射的Mueller矩阵解,并以此作为麦穗的下垫面(作用类似于双层散射中的随机粗糙面地表),利用公式进行新的双层散射模型计算,即两次使用双层散射模型,获得小麦总后向散射。
鉴于主动微波遥感可以忽略热辐射项,则矢量辐射传输方程可表示为:
$$\frac{\text{d}I\text{(}r\text{,}\hat{s}\text{)}}{\text{d}s}=-{{\bar{k}}_{\text{e}}}\text{(}\hat{s}\text{)}\cdot I\text{(}r\text{,}\hat{s}\text{)+}\int{\text{d}{\hat{s}}'\bar{P}\text{(}\hat{s}\text{,}{\hat{s}}'\text{)}}\cdot I\text{(}r\text{,}{\hat{s}}'\text{)}$$ (1) 式中,$I\text{(}r\text{,}\hat{s}\text{)}$描述了电磁波强度(斯托克斯强度)的散射、吸收和多次散射的传播过程;${{\bar{k}}_{\text{e}}}$为消光矩阵,表示$I\text{(}r\text{,}\hat{s}\text{)}$的衰减;$\bar{P}\text{(}\hat{s}\text{,}{\hat{s}}'\text{)}$为相矩阵,表示多次散射从方向$\text{(}{\theta }',{\phi }'\text{)}$传递到$(\theta ,\phi )$的过程[3]。消光矩阵为:
$$\begin{align} & {{{\bar{k}}}_{\text{e}}}(\theta ,\varphi )\text{=}\frac{4\text{ }\!\!\pi\!\!\text{ }}{k}{{n}_{0}}\operatorname{Im}[\mathbf{\hat{p}}\times \mathbf{\bar{S}}\text{(}\theta ,\phi ;\theta ,\phi \text{)}\times \mathbf{\hat{p}}]= \\ & \frac{2p}{k}{{n}_{0}}\left[ \begin{matrix} 2Im<\mathbf{S}_{\text{vv}}^{\text{0}}> & 0 & Im<\mathbf{S}_{vh}^{0}> & -Re<\mathbf{S}_{vh}^{0}> \\ 0 & 2Im<\mathbf{S}_{hh}^{0}> & Im<\mathbf{S}_{hv}^{0}> & Re<\mathbf{S}_{hv}^{0}> \\ 2Im<\mathbf{S}_{hv}^{0}> & 2Im<\mathbf{S}_{vh}^{0}> & Im<\mathbf{S}_{vv}^{0}+\mathbf{S}_{hh}^{0}> & Re<\mathbf{S}_{vv}^{0}-\mathbf{S}_{hh}^{0}> \\ 2Re<\mathbf{S}_{hv}^{0}> & -2Re<\mathbf{S}_{vh}^{0}> & Re<\mathbf{S}_{hh}^{0}-\mathbf{S}_{vv}^{0}> & Im<\mathbf{S}_{vv}^{0}+\mathbf{S}_{hh}^{0}> \\ \end{matrix} \right] \\ \end{align}$$ (2) 式中,$\mathbf{S}_{\text{pq}}^{\text{0}}$(p,q=v,h)为散射粒子的前向散射矩阵${{\bar{S}}_{\text{0}}}=\bar{S}\text{(}\theta \text{,}\phi \text{;}\theta ,\phi \text{)}$的元素,v表示垂直极化,h表示水平极化。不同类型的散射粒子的消光矩阵形式有一定差别:对称性最强的球形粒子,其消光矩阵为常数;水平方位均匀取向的,为对角矩阵;非均匀取向的为非对角矩阵。用式(2)计算消光矩阵,要求$\bar{S}$足够精确。
相矩阵$\bar{P}\text{(}\hat{s}\text{,}{\hat{s}}'\text{)}$描述散射能量从$({\theta }',{\phi }')$转移到$(\theta ,\phi )$的转移矩阵,有:
$$\bar{P}(\theta ,\phi ;{\theta }',{\phi }')=\left[ \begin{matrix} <{{\left| {{\mathbf{S}}_{\text{vv}}} \right|}^{\text{2}}}> & <{{\left| {{\mathbf{S}}_{\text{vh}}} \right|}^{\text{2}}}> & \operatorname{Re}<{{\mathbf{S}}_{\text{vv}}}\mathbf{S}_{\text{vh}}^{*}> & -Im<{{\mathbf{S}}_{\text{vv}}}\mathbf{S}_{\text{vh}}^{\text{*}}> \\ <{{\left| {{\mathbf{S}}_{\text{hv}}} \right|}^{\text{2}}}> & <{{\left| {{\mathbf{S}}_{\text{hh}}} \right|}^{\text{2}}}> & \operatorname{Re}<{{\mathbf{S}}_{\text{hv}}}\mathbf{S}_{\text{hh}}^{\text{*}}> & -\operatorname{Im}<{{\mathbf{S}}_{\text{hv}}}\mathbf{S}_{\text{hh}}^{\text{*}}> \\ 2Re<{{\mathbf{S}}_{\text{vv}}}\mathbf{S}_{\text{hv}}^{\text{*}}> & \text{2}\operatorname{Re}<{{\mathbf{S}}_{\text{vh}}}\mathbf{S}_{\text{hh}}^{\text{*}}> & \operatorname{Re}<{{\mathbf{S}}_{\text{vv}}}\mathbf{S}_{\text{hh}}^{\text{*}}\mathbf{+}{{\mathbf{S}}_{\text{vh}}}\mathbf{S}_{\text{hv}}^{\text{*}}> & -\operatorname{Im}<{{\mathbf{S}}_{\text{vv}}}\mathbf{S}_{\text{hh}}^{\mathbf{*}}-{{\mathbf{S}}_{\text{vh}}}\mathbf{S}_{\text{hv}}^{\text{*}}> \\ 2Im<{{\mathbf{S}}_{\text{vv}}}\mathbf{S}_{\text{hv}}^{\text{*}}> & 2Im<{{\mathbf{S}}_{\text{vh}}}\mathbf{S}_{\text{hh}}^{\text{*}}> & \operatorname{Im}<{{\mathbf{S}}_{\text{vv}}}\mathbf{S}_{\text{hh}}^{\mathbf{*}}\mathbf{+}{{\mathbf{S}}_{\text{vh}}}\mathbf{S}_{\text{hv}}^{\text{*}}> & \operatorname{Re}<{{\mathbf{S}}_{\text{vv}}}\mathbf{S}_{\text{hh}}^{\mathbf{*}}-{{\mathbf{S}}_{\text{vh}}}\mathbf{S}_{\text{hv}}^{\text{*}}> \\ \end{matrix} \right]~~~$$ (3) 根据矢量辐射传输理论可得到:
$$\begin{align} & \theta \frac{\text{d}}{\text{d}z}\mathbf{I}_{\text{r}}^{\mathbf{+}}\text{(}\theta \text{,}\phi \text{,}z\text{)}= \\ & -\mathbf{K}_{\text{r}}^{\mathbf{+}}\text{(}\theta \text{,}\phi \text{)}\cdot \mathbf{I}_{\text{r}}^{\mathbf{+}}\text{(}\theta \text{,}\phi \text{,}z\text{)}+\mathbf{F}_{\text{r}}^{\mathbf{+}}\text{(}\theta \text{,}\phi \text{,}z\text{)}~ \\ \end{align}$$ (4) $$\begin{align} & -\theta \frac{\text{d}}{\text{d}z}\mathbf{I}_{\text{r}}^{-}\text{(}-\theta \text{,}\phi \text{,}z\text{)}= \\ & -\mathbf{K}_{r}^{-}\text{(}-\theta \text{,}\phi \text{)}\cdot \mathbf{I}_{\text{r}}^{-}\text{(}-\theta \text{,}\phi \text{,}z\text{)}+\mathbf{F}_{\text{r}}^{-}\text{(}-\theta \text{,}\phi \text{,}z\text{)} \\ \end{align}$$ (5) 式中,$\mathbf{I}_{\text{r}}^{\mathbf{+}}\text{(}\theta \text{,}\phi \text{,}z\text{)}\mathbf{I}_{\text{r}}^{-}\text{(}-\theta \text{,}\phi \text{,}z\text{)}$分别表示Stokes矢量的上行及下行强度;$K_{\text{r}}^{\pm }$表示小麦层的消光矩阵;$F_{\text{r}}^{+}\text{(}\theta \text{,}\phi \text{,}z\text{)}$和$F_{\text{r}}^{-}\text{(}-\theta \text{,}\phi \text{,}z\text{)}$表示Stokes矢量强度自$(\theta ,\phi )$散射至$(-\theta ,\phi )$方向的能量,即表示散射源函数,有:
$$\begin{align} & F_{\text{r}}^{+}\text{(}\theta \text{,}\phi \text{,}z\text{)}=\frac{1}{\theta }\text{ }\!\![\!\!\text{ }\int_{\text{ }0}^{\text{ }2\text{ }\!\!\pi\!\!\text{ }}{\int_{\text{ }0}^{\text{ }1}{{{P}_{\text{r}}}\text{(}\theta \text{,}\phi \text{;}{\theta }'\text{,}{\phi }'\text{)}I_{\text{r}}^{+}\text{(}{\theta }'\text{,}{\phi }'\text{,}z\text{)d}{\theta }'\text{d}{\phi }'}}\text{+} \\ & ~\int_{\text{ }0}^{\text{ }2\text{ }\!\!\pi\!\!\text{ }}{\int_{\text{ }0}^{\text{ }1}{{{P}_{\text{r}}}\text{(}\theta \text{,}\phi \text{;}-{\theta }'\text{,}{\phi }'\text{)}I_{\text{r}}^{-}\text{(}-{\theta }'\text{,}{\phi }'\text{,}z\text{)d}{\theta }'\text{d}{\phi }'}}\text{ }\!\!]\!\!\text{ }\!\!~\!\!\text{ } \\ \end{align}$$ (6) $$\begin{align} & F_{\text{r}}^{-}\text{(}-\theta \text{,}\phi \text{,}z\text{)}=\frac{1}{\theta }\text{ }\!\![\!\!\text{ }\int_{\text{ }0}^{\text{ }2\text{ }\!\!\pi\!\!\text{ }}{\int_{\text{ }0}^{\text{ }1}{{{P}_{\text{r}}}\text{(}-\theta \text{,}\phi \text{;}{\theta }'\text{,}{\phi }'\text{)}I_{\text{r}}^{+}\text{(}{\theta }'\text{,}{\phi }'\text{,}z\text{)d}{\theta }'\text{d}{\phi }'}}\text{+} \\ & \int_{\text{ }0}^{\text{ }2\text{ }\!\!\pi\!\!\text{ }}{\int_{\text{ }0}^{\text{ }1}{{{P}_{\text{r}}}\text{(}-\theta \text{,}\phi \text{;}-{\theta }'\text{,}{\phi }'\text{)}I_{\text{r}}^{-}\text{(}-{\theta }'\text{,}{\phi }'\text{,}z\text{)d}{\theta }'\text{d}{\phi }'}}\text{ }\!\!]\!\!\text{ } \\ \end{align}$$ (7) 空气层和小麦层的边界条件$\mathbf{I}_{\text{r}}^{-}\text{(}-\theta \text{,}\phi \text{,}z=0\text{)}$、小麦层和土壤粗糙面的边界条件$\mathbf{I}_{^{\text{r}}}^{\mathbf{+}}\text{(}-\theta \text{,}\phi \text{,}z=-h\text{)}$为:
$$\mathbf{I}_{\text{r}}^{-}\text{(}-\theta \text{,}\phi \text{,}z=\text{)}={{I}_{0}}\delta \text{(}\theta -{{\theta }_{0}})\delta \text{(}\phi -{{\phi }_{0}}\text{)}$$ (8) $$\mathbf{I}_{\text{r}}^{\mathbf{+}}\text{(}-\theta \text{,}\phi \text{,}z=-h\text{)}={{\mathbf{R}}_{\text{w}}}\text{(}\theta \text{)}\mathbf{I}_{\text{r}}^{-}\text{(}-\theta \text{,}\phi \text{,}z=-h\text{)}$$ (9) 式中,${{I}_{0}}$为入射波Stokes矢量;$\delta $表示冲击函数;Rw为Mueller矩阵。
利用迭代法求解并带入边界条件可以得到后向散射求解公式为:
$$\begin{align} & {{\mathbf{I}}^{\text{bs}}}\text{(}{{\theta }_{0}}\text{,}{{\phi }_{0}}\text{)}= \\ & \mathbf{I}_{\mathbf{1}}^{\mathbf{+}}\text{(}{{\theta }_{0}}\text{,}{{\phi }_{0}}\pm \text{ }\!\!\pi\!\!\text{ },z=0\text{)}=\mathbf{T}\text{(}{{\theta }_{0}}\text{,}{{\phi }_{0}}\text{)}{{I}_{0}} \\ \end{align}$$ (10) 式中,
$$\begin{align} & T\text{(}{{\theta }_{0}}\text{,}{{\phi }_{0}}\text{)=} \\ & \frac{1}{{{\theta }_{0}}}Q{{D}_{\text{r}}}\text{(}{{\theta }_{0}}\text{,}{{\phi }_{0}}\pm \text{ }\!\!\pi\!\!\text{ ;}-h/{{\theta }_{0}}\text{)}{{Q}^{-1}}{{R}_{\text{w}}}\text{(}{{\theta }_{0}}\text{,}{{\phi }_{0}}\pm \text{ }\!\!\pi\!\!\text{ )}Q{{A}_{1}}{{Q}^{-1}}\times \\ & {{R}_{\text{w}}}\text{(}{{\theta }_{0}}\text{,}{{\phi }_{0}}\text{)}{{D}_{\text{r}}}\text{(}{{\theta }_{0}}\text{,}{{\phi }_{0}}\text{;}-h/{{\theta }_{0}}\text{)}{{Q}^{-1}}+ \\ & \frac{1}{{{\theta }_{0}}}Q{{D}_{\text{r}}}\text{(}{{\theta }_{0}}\text{,}{{\phi }_{0}}\pm \text{ }\!\!\pi\!\!\text{ ;}-h/{{\theta }_{0}}\text{)}{{Q}^{-1}}{{R}_{\text{w}}}\text{(}{{\theta }_{0}}\text{,}{{\phi }_{0}}\pm \text{ }\!\!\pi\!\!\text{ )}Q{{A}_{\text{2}}}{{Q}^{-1}}+ \\ & \frac{1}{{{\theta }_{0}}}Q{{A}_{3}}{{Q}^{-1}}{{R}_{\text{w}}}\text{(}{{\theta }_{0}}\text{,}{{\phi }_{0}}\text{)}Q{{D}_{\text{r}}}\text{(}{{\theta }_{0}}\text{,}{{\phi }_{0}}\text{;}-h/{{\theta }_{0}}\text{)}{{Q}^{-1}}+ \\ & \frac{1}{{{\theta }_{0}}}Q{{A}_{4}}{{Q}^{-1}}+Q{{A}_{5}}{{Q}^{-1}} \\ \end{align}$$ (11) 式中,Q表示特征值组成的消光矩阵,Q-1表示其逆矩阵;Dr表示与特征值相关的对角矩阵,有:
$${{D}_{\text{r}}}{{\text{(}\theta \text{,}\phi ;-z/\theta \text{)}}_{(i,i)}}=\exp \text{ }\!\![\!\!\text{ }-{{\lambda }_{i}}(\theta \text{,}\phi )z/\theta \text{ }\!\!]\!\!\text{ }$$ (12) $$\begin{align} & {{A}_{\text{1}}}\text{=}\int_{\text{ }-h}^{\text{ }0}{{{D}_{\text{r}}}}\text{(}-\theta \text{,}\phi \text{;}-\text{(}{z}'+h\text{)/}\theta \text{)}{{Q}^{-1}}{{P}_{\text{r}}}\text{(}-\theta \text{,}\phi \text{;}{{\theta }_{0}}\text{,}{{\phi }_{0}}\text{)}\times \\ & Q{{D}_{\text{r}}}\text{(}{{\theta }_{0}}\text{,}{{\phi }_{0}}\text{;}-\text{(}{z}'+h\text{)/}{{\theta }_{0}}\text{)d}{z}'~ \\ \end{align}$$ (13) $$\begin{align} & {{A}_{\text{2}}}\text{=}\int_{\text{ }-h}^{\text{ }0}{{{D}_{\text{r}}}\text{(}-\theta \text{,}\phi \text{;}-\text{(}{z}'+h\text{)/}\theta ){{Q}^{-1}}{{P}_{\text{r}}}\text{(}-\theta \text{,}\phi \text{;}-{{\theta }_{0}}\text{,}{{\phi }_{0}}\text{)}\times } \\ & Q{{D}_{\text{r}}}\text{(}-{{\theta }_{0}}\text{,}{{\phi }_{0}}\text{;}{z}'\text{/}{{\theta }_{0}}\text{)d}{z}'~~ \\ \end{align}$$ (14) $$\begin{align} & {{A}_{3}}\text{=}\int_{\text{ }-h}^{\text{ 0}}{{{D}_{\text{r}}}}\text{(}\theta \text{,}\phi \text{;}{z}'\text{/}\theta \text{)}{{Q}^{-1}}{{P}_{\text{r}}}\text{(}\theta \text{,}\phi \text{;}{{\theta }_{0}}\text{,}{{\phi }_{0}}\text{)}\times \\ & Q{{D}_{\text{r}}}\text{(}{{\theta }_{0}}\text{,}{{\phi }_{0}}\text{;}-\text{(}{z}'+h\text{)/}{{\theta }_{0}}\text{)d}{z}'~ \\ \end{align}$$ (15) $$\begin{align} & {{A}_{\text{4}}}\text{=}\int_{\text{ }-h}^{\text{ }0}{{{D}_{\text{r}}}}\text{(}\theta \text{,}\phi \text{;}{z}'\text{/}\theta \text{)}{{Q}^{-1}}{{P}_{\text{r}}}\text{(}\theta \text{,}\phi \text{;}-{{\theta }_{0}}\text{,}{{\phi }_{0}}\text{)}\times \\ & Q{{D}_{\text{r}}}\text{(}-{{\theta }_{0}}\text{,}{{\phi }_{0}}\text{;}{z}'\text{/}{{\theta }_{0}}\text{)d}{z}'~ \\ \end{align}$$ (16) $$\begin{align} & {{A}_{\text{5}}}\text{=}{{D}_{\text{r}}}\text{(}\theta \text{,}\phi \text{;}-h/\theta \text{)}{{Q}^{-1}}{{R}_{\text{w}}}\text{(}\theta \text{,}\phi \text{;}-{{\theta }_{0}}\text{,}{{\phi }_{0}}\text{)}\times \\ & Q{{D}_{\text{r}}}\text{(}-{{\theta }_{0}}\text{,}{{\phi }_{0}}\text{;}-h\text{/}{{\theta }_{0}}\text{)}~ \\ \end{align}$$ (17) 通过求解可以获得小麦4个极化的后向散射系数为:
$$~\left\{ \begin{align} & \sigma _{\text{VV}}^{0}=4\text{ }\!\!\pi\!\!\text{ }{{\theta }_{0}}{{\left[ \mathbf{T} \right]}_{11}} \\ & ~\sigma _{\text{HH}}^{0}=4\text{ }\!\!\pi\!\!\text{ }{{\theta }_{0}}{{\left[ \mathbf{T} \right]}_{22}}~~ \\ & \sigma _{\text{VH}}^{0}=4\text{ }\!\!\pi\!\!\text{ }{{\theta }_{0}}{{\left[ \mathbf{T} \right]}_{12}} \\ & ~\sigma _{\text{HV}}^{0}=4\text{ }\!\!\pi\!\!\text{ }{{\theta }_{0}}{{\left[ \mathbf{T} \right]}_{21}}~ \\ \end{align} \right.$$ (18) 在对微波散射进行研究时,通常采用dB作为散射强度的单位,其转换通常对散射系数值取对数,有:
$$~{{\sigma }_{\text{pq}}}=10\lg \sigma _{\text{pq}}^{0}~$$ (19) 式中,p表示发射极化;q表示接收极化。
-
本文选取的实验地点位于四川省成都市邛崃前进镇,是电子科技大学所属的川西实验场(北纬30°24′22.29″,东经103°32′15.97″)。该实验场位于成都平原西南部,地势平缓,海拔约483 m,占地约30000m2,主要种植农作物有小麦、水稻、玉米和油菜。冬小麦的种植生长时间为每年的11月份到次年的5月份共约200天。本文研究选取的生长期为小麦灌浆期和成熟期,如图 3所示。测量所使用的陆基散射系统主要有升降平台、控制计算机、散射计和收发天线几部分组成。升降机最大升起高度为15 m,通过计算机控制升降机上的伺服转台,使得收发天线可以在水平和竖直方向调整,满足俯仰角0~90°和方位角0~360°之间的自由转动。散射计采用调频连续波(FM-CW)制式,每个频段采用不同的散射计,共有L、S、C和X波段4个散射计。
本文选取2011年测量的小麦S波段散射数据及地表参数,S波段中心频率为3.1GHz,带宽为0.8GHz。本文研究选取的入射角为22~52°,规避了测量过程中小入射角对冠层后向散射的干扰,避免了大入射角状态下田埂和树木对测量的影响。本文通过实测数据对AIEM模型进行了修正,使之能更好地模拟土壤随机粗糙面的后向散射系数。
-
本文选取小麦生长期中的测量时间为灌浆期2011-04-12和成熟期2011-05-08。粗糙度的测量采用自制的粗糙度板进行均方根高度和相关长度的计算。土壤含水量采用TDR300进行测量。对比小麦生长期两个阶段,如表 1所示。差别最大的是小麦含水量和土壤含水量,成熟期的小麦含水量迅速减少,由绿色失水变为黄色。成熟期测量期间,由于雨水的原因,造成土壤含水量急剧增大,趋于饱和状态。表 1中列举了模型构建考虑的各种参量。土壤的参数和小麦冠层的参数对后向散射系数影响较大,实验中小麦参数值采用30个独立样本进行平均,散射计测量后向散射系数首先采用内外部定标进行数据校正,然后采用两轮数据平均的方法来保障数据的准确性和精度。
表 1 模型所需实测数据
数据参数 灌浆期 成熟期 叶厚/m 0.000 45 0.000 32 叶宽/m 0.0213 0.0206 叶长/m 0.232 0.221 叶含水量/% 80.1 25.4 杆长/m 0.621 0.615 杆直径/m 0.004 5 0.004 3 杆含水量/% 78.3 21.1 叶密度/m-2 2050 2180 小麦层厚度/m 0.815 0.765 穗长/m 0.102 0.145 穗直径/m 0.010 2 0.009 6 穗含水量/% 76.2 22.7 穗密度/m-2 452 469 土壤相关长度/cm 15.26 15.26 土壤粗糙度/cm 2.12 2.12 土壤含水量/% 26.7 42.1
Multiple Layers Backscatter Model of Wheat for S Band
-
摘要: 针对麦穗出现后小麦生长期的微波散射特性,基于矢量辐射传输理论(VRT),建立了小麦S波段多层后向散射模型。模型把小麦冠层划分为麦穗层、麦秆叶层和土壤层,并基于能量守恒的矢量辐射传输理论,对电磁波强度的反射、吸收和传输进行了分析,采用5项后向散射贡献构成冠层总后向散射。模型的解析首先采用先进积分方程模型(AIEM)对土壤粗糙面的后向散射进行模拟,然后利用消光矩阵和相矩阵分别计算散射能量的衰减和散射方向的变化,最后利用Mueller矩阵获得最终的解析解。该文选用2011年川西实验场测量的小麦S波段散射数据对构建的模型进行验证与分析,模型的模拟值与实测值吻合较好。研究结果表明麦穗出现后对小麦冠层后向散射影响较大,建模时有必要单独考虑麦穗的影响。Abstract: The paper presents a multiple layers backscatter model of wheat for S-band based on vector radiative transfer (VRT) theory, which focuses on the microwave character of wheat at the growth stage that wheat ears appeared. The scattered, absorbed and transferred electromagnetic intensity is analyzed based on the law of energy conservation of VRT, and the wheat canopy is divided into three layers, the ears layer, the stem and leaf layer and the soil layer. Furthermore, the total backscatter is composed by using five back-scattering contributions. An advanced integral equation model (AIEM) is applied to simulate the soil backscatter. The extinction and phase matrices are used to compute the scattering intensity decayed and transferred. In addition, Mueller matrix is used to obtain the backscatter values. The backscatter of S-band, which was measured at the West Sichuan Experiment Location in 2011, is applied to analyze and verify the model. The results show the simulated values agreed well with the measured data, and the wheat ears should be taken into account in modeling as a separate element for its influence to backscatter.
-
Key words:
- backscatter model /
- ears /
- S-band /
- VRT /
- wheat
-
表 1 模型所需实测数据
数据参数 灌浆期 成熟期 叶厚/m 0.000 45 0.000 32 叶宽/m 0.0213 0.0206 叶长/m 0.232 0.221 叶含水量/% 80.1 25.4 杆长/m 0.621 0.615 杆直径/m 0.004 5 0.004 3 杆含水量/% 78.3 21.1 叶密度/m-2 2050 2180 小麦层厚度/m 0.815 0.765 穗长/m 0.102 0.145 穗直径/m 0.010 2 0.009 6 穗含水量/% 76.2 22.7 穗密度/m-2 452 469 土壤相关长度/cm 15.26 15.26 土壤粗糙度/cm 2.12 2.12 土壤含水量/% 26.7 42.1 -
[1] 中华人民共和国国家统计局. 中华人民共和国2014年国民经济和社会发展统计公报[EB/OL]. (2015-02-26). http://www.stats.gov.cn/tjsj/zxfb/201502/t20150226_685799.html. National Bureau of Statistics of the People's Republic of China. The People's Republic of China national economic and social development statistical bulletin in 2014[EB/OL]. (2015-02-26). http://www.stats.gov.cn/tjsj/zxfb/201502/t20150226_685799.html. [2] ULABY F T, MOORE R K, FUNG A K. Microwave remote sensing:Active and passive. Volume 2:Radar remote sensing and surface scattering and emission Theory[M]. Delham, MA:Artech House, 1982. [3] 金亚秋, 刘鹏, 叶红霞. 随机粗糙面与目标复合散射数值模拟理论与方法[M]. 北京:科学出版社, 2008. JIN Ya-qiu, LIU Peng, YE Hong-xia. Theory and method of numerical simulation of composite scattering from the object and randomly rough surface[M]. Beijing:Science Press, 2008. [4] TSANG L, DING K H. Polarimetric signatures of a layer of random nonspherical discrete scatterers overlying a homogeneous half-space based on first-and second-order vector radiative transfer theory[J]. IEEE Transactions on Geoscience and Remote Sensing, 1991, 29(2):242-253. doi: 10.1109/36.73665 [5] ULABY F T, SARABANDI K, MCDONALD K, et al. Michigan microwave canopy scattering model[J]. International Journal of Remote Sensing, 1990, 11(7):1223-1253. doi: 10.1080/01431169008955090 [6] TOURE A, THOMSON K P B, EDWARDS G, et al. Adaptation of the MIMICS backscattering model to the agricultural context-wheat and canola at L and C bands[J]. IEEE Transactions on Geoscience and Remote Sensing, 1994, 32(1):41-67. http://cn.bing.com/academic/profile?id=2097666088&encoded=0&v=paper_preview&mkt=zh-cn [7] JIA Ming-quan, TONG Ling, ZHANG Yuan-zhi, et al. Multitemporal radar backscattering measurement and modeling of rice fields using a multi-frequency(L, S, C and X) scatterometer[J]. International Journal of Remote Sensing, 2014, 35(4):1253-1271. doi: 10.1080/01431161.2013.876117 [8] PICARD G, LE T T, MATTIA F. Understanding C-band radar backscatter from wheat canopy using a multiple-scattering coherent model[J]. IEEE Transactions on Geoscience and Remote Sensing, 2003, 41(7):1583-1591. doi: 10.1109/TGRS.2003.813353 [9] 贾明权, 童玲, 陈彦. 水稻后向散射的模拟, 验证及参数敏感性分析[J]. 电子科技大学学报, 2013, 42(6):895-899. http://www.cnki.com.cn/Article/CJFDTOTAL-DKDX201306017.htm JIA Ming-quan, TONG Ling, CHEN Yan. Rice backscattering simulation, verification and parameter sensitivity analyisis[J]. Journal of University of Electronic Science and Technology of China, 2013, 42(6):895-899. http://www.cnki.com.cn/Article/CJFDTOTAL-DKDX201306017.htm [10] HE Lei, TONG Ling, CHEN Yan, et al. Adaptation of MIMICS model of wheat at multi-band (L,S,C,X)[C]//International Geoscience and Remote Sensing Symposium. Milan, Italy:IEEE, 2015. [11] CHEN K S, WU T D, TSANG L, et al. Emission of rough surfaces calculated by the integral equation method with comparison to three-dimensional moment method simulations[J]. IEEE Transactions on Geoscience and Remote Sensing, 2003, 41:90-101. doi: 10.1109/TGRS.2002.807587 [12] 金亚秋. 空间微波遥感数据验证理论与方法[M]. 北京:科学技术出版社, 2005. JIN Ya-qiu. Theory and method for data validation of space-borne microwave remote sensing[M]. Beijing:Science Prwess, 2005.