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首页> 外文期刊>Quaternary International >Characterization of geomorphological features of lunar surface using Chandrayaan-1 Mini-SAR and LRO Mini-RF data
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Characterization of geomorphological features of lunar surface using Chandrayaan-1 Mini-SAR and LRO Mini-RF data

机译：使用Chandrayaan-1 Mini-SAR和LRO Mini-RF数据表征月球表面的地貌特征

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The lunar surface comprises complex geomorphological features, which have been formed by the conjunction of processes namely impact cratering and volcanism. Geological features on the Lunar surface can be bifurcated into two main areas named Maria region and the Highland region. Taurus-Littrow valley, which was the Apollo-17 mission landing site, consisting of unique geomorphological characteristics by having a sample size of both Lunar Maria and Highland regions. The dielectric constant is a parameter that gives an approximate distribution of the constituent material of the target area. It is a complex quantity, which indicates a periodic variation of the electric field. The real part of dielectric constant indicates stored energy and the imaginary part indicates dielectric loss factor or the loss of the electric field in the medium due to continuous varying electric field. Planetary surfaces for which determining dielectric constant is an important analysis for most of the space missions, ground measurement is not feasible. This work includes the machine learning-based modeling of dielectric constant for the Apollo 17 landing site the Taurus-Littrow valley. Based on the surface roughness of the study area, two models Gaussian and Exponential have been implemented and compared for the modeled output of the dielectric constant values.The modeling approaches for dielectric characterization of the lunar surface were implemented on NASA's LRO Mini-RF SAR data and Mini-SAR hybrid-pol data of ISRO's Chandrayaan-1 mission. The coefficient of determination (r2) and the root mean square error (RMSE) of the theoretical Gaussian model was 0.995, 0.042 and the Exponential model was 0.948, 0.1349 respectively. When compared with the already calculated values of dielectric constant from Apollo 17 return samples and literature survey, the Gaussian model gives a better variation. Gaussian model was further applied to the Lunar north pole crater namely Hermite-A crater, whose distinctive geomorphological characteristics and location being lunar north pole region, makes it one of the coldest places in the Solar System and a prominent location of water ice deposits.
机译：月球表面包括复杂的地貌特征，该特征是由过程的结合形成的，即冲击陨石坑和火山。月球表面上的地质特征可以分为名为Maria地区和高地地区的两个主要区域。金牛座 - Littrow山谷是Apollo-17任务登陆现场，通过在月球玛丽亚和高地地区的样本量来组成独特的地貌特征。介电常数是给出目标区域的构成材料的近似分布的参数。它是一个复杂的数量，表示电场的周期性变化。介电常数的真实部分表示存储的能量，并且假想部分表示由于连续变化的电场引起的介电损耗因数或介质中的电场的丢失。线谱面，确定介电常数是大多数空间任务的重要分析，地测量是不可行的。这项工作包括机器学习的介质常数介质模型，适用于阿波罗17落地的介电常数。基于研究区域的表面粗糙度，已经实现了两个模型高斯和指数的介电常数的建模输出。在NASA的LRO Mini-RF SAR数据上实现了月球表面的电介质表征的建模方法和Mini-SAR Hybrid-Pol数据伊斯罗的ChandRayaan-1任务。理论高斯模型的确定系数（R2）和根均方误差（RMSE）为0.995,0.042和指数模型分别为0.948,0.1349。与从Apollo 17返回样本和文献调查的已经计算出的介电常数的计算值相比，高斯模型提供了更好的变化。高斯模型进一步应用于月球北极火山口，即Hermite-A火山口，其独特的地貌特征和地理位置是农历北极地区，使其成为太阳系最冷的地方之一，以及水冰沉积物的突出位置。

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