Vegetation characteristics and underlying topography from interferometric radar
Vegetation characteristics and underlying topography from interferometric radar
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DOI：
10.1029/96rs01763
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发表时间：
1996-11
期刊：
影响因子：
1.6
通讯作者：
R. Treuhaft;S. Madsen;M. Moghaddam;J. V. Zyl
中科院分区：
文献类型：
--
作者：
R. Treuhaft;S. Madsen;M. Moghaddam;J. V. Zyl
本文阐述和论证了从干涉合成孔径雷达（干涉合成孔径雷达）数据中提取植被特征和下垫面地形的方法。电磁散射和雷达处理，产生干涉合成孔径雷达观测，建模，植被和地形参数的估计确定，参数误差进行评估的干涉合成孔径雷达仪器性能，参数估计的干涉合成孔径雷达数据和地面实况进行了比较。估算植被和地表地形参数的基本观测值是：（1）互相关幅度，（2）互相关相位，（3）合成孔径雷达（SAR）后向散射功率。一个计算的基础上从植被散射处理作为一个随机介质，包括在植被中的反射活性和吸收的影响，产量表达式的复杂的互相关和后向散射功率的植被特性。这些表达式导致识别一组最小的四个参数描述的植被和表面地形：（1）植被层深度，（2）植被消光系数（每单位长度的功率损失），（3）一个参数，涉及的产品的平均后向散射振幅和散射体数密度，（4）下伏地面的高度。植被和地面参数的准确性，作为干涉合成孔径雷达观测精度的函数，评估飞机干涉合成孔径雷达，其特点是由2.5米的基线，约8公里的高度，和5.6厘米的波长。结果表明，当干涉合成孔径雷达归一化互相关幅度的精度为± 0.5%，干涉相位的精度为± 5°时，干涉合成孔径雷达可以对多种类型的植被层确定几米的植被层深度和地表高度。在相同的观测精度下，消光系数可以估计在0.1 dB/m的水平。由于参数的数量超过了目前干涉合成孔径雷达数据集的观测数量，外部消光系数数据被用来证明从干涉合成孔径雷达数据在阿拉斯加的博南扎溪实验森林的植被层深度和地面高度的估计。该演示显示了大约5米的平均地面实况协议植被层深度和地表高度，与一个明确的依赖于立场高度的错误。这些误差表明，干涉合成孔径雷达数据采集和分析技术需要改进，这将有可能产生几米的精度。干涉合成孔径雷达参数中的信息适用于各种生态建模问题，包括森林生态系统的演替建模。
This paper formulates and demonstrates methods for extracting vegetation characteristics and underlying ground surface topography from interferometric synthetic aperture radar (INSAR) data. The electromagnetic scattering and radar processing, which produce the INSAR observations, are modeled, vegetation and topographic parameters are identified for estimation, the parameter errors are assessed in terms of INSAR instrumental performance, and the parameter estimation is demonstrated on INSAR data and compared to ground truth. The fundamental observations from which vegetation and surface topographic parameters are estimated are (1) the cross-correlation amplitude, (2) the cross-correlation phase, and (3) the synthetic aperture radar (SAR) backscattered power. A calculation based on scattering from vegetation treated as a random medium, including the effects of refractivity and absorption in the vegetation, yields expressions for the complex cross correlation and backscattered power in terms of vegetation characteristics. These expressions lead to the identification of a minimal set of four parameters describing the vegetation and surface topography: (1) the vegetation layer depth, (2) the vegetation extinction coefficient (power loss per unit length), (3) a parameter involving the product of the average backscattering amplitude and scatterer number density, and (4) the height of the underlying ground surface. The accuracy of vegetation and ground surface parameters, as a function of INSAR observation accuracy, is evaluated for aircraft INSAR, which is characterized by a 2.5-m baseline, an altitude of about 8 km, and a wavelength of 5.6 cm. It is found that for ≈0.5% accuracy in the INSAR normalized cross-correlation amplitude and ≈5° accuracy in the interferometric phase, few-meter vegetation layer depths and ground surface heights can be determined from INSAR for many types of vegetation layers. With the same observational accuracies, extinction coefficients can be estimated at the 0.1-dB/m level. Because the number of parameters exceeds the number of observations for current INSAR data sets, external extinction coefficient data are used to demonstrate the estimation of the vegetation layer depth and ground surface height from INSAR data taken at the Bonanza Creek Experimental Forest in Alaska. This demonstration shows approximately 5-m average ground truth agreement for vegetation layer depths and ground-surface heights, with a clear dependence of error on stand height. These errors suggest refinements in INSAR data acquisition and analysis techniques which will potentially yield few-meter accuracies. The information in the INSAR parameters is applicable to a variety of ecological modeling issues including the successional modeling of forested ecosystems.