The leaf area index(LAI) is a critical biophysical variable that describes canopy geometric structures and growth conditions.It is also an important input parameter for climate,energy and carbon cycle models.The scaling effect of the LAI has always been of concern.Considering the effects of the clumping indices on the BRDF models of discrete canopies,an effective LAI is defined.The effective LAI has the same function of describing the leaf density as does the traditional LAI.Therefore,our study was based on the effective LAI.The spatial scaling effect of discrete canopies significantly differed from that of continuous canopies.Based on the directional second-derivative method of effective LAI retrieval,the mechanism responsible for the spatial scaling effect of the discrete-canopy LAI is discussed and a scaling transformation formula for the effective LAI is suggested in this paper.Theoretical analysis shows that the mean values of effective LAIs retrieved from high-resolution pixels were always equal to or larger than the effective LAIs retrieved from corresponding coarse-resolution pixels.Both the conclusions and the scaling transformation formula were validated with airborne hyperspectral remote sensing imagery obtained in Huailai County,Zhangjiakou,Hebei Province,China.The scaling transformation formula agreed well with the effective LAI retrieved from hyperspectral remote sensing imagery.
L波段微波对土壤具有较强的穿透性,所获得的土壤辐射亮温包含了穿透深度内各层土壤的温度信息,因此其所获得的土壤等效温度与红外地表温度具有不同的物理意义,且在数值上也有较大的差异。在应用长时间序列的土壤温度廓线实测数据对水热耦合模型(Simultaneous Heat And Water,SHAW)进行验证的基础上,利用怀来试验区2006～2009年的气象观测数据驱动SHAW模型,模拟了4a的土壤温湿度廓线小时数据,并计算了对应时刻L波段的土壤等效温度,并在不同时段上对L波段土壤等效温度与热红外地表温度之间的差异进行了初步分析,为进一步探讨微波等效温度与热红外地表温度之间的定量关系模型奠定了基础,为用热红外与被动微波数据协同反演土壤温度提供了理论支持。
