数字高程模型
遥感
全球导航卫星系统应用
地质学
地形
全球定位系统
比例(比率)
仰角(弹道)
环境科学
大地测量学
地理
地图学
计算机科学
几何学
数学
电信
作者
Hugo Carreño-Luengo,Guido Luzi,Michele Crosetto
出处
期刊:Remote Sensing
[MDPI AG]
日期:2019-10-31
卷期号:11 (21): 2556-2556
被引量:29
摘要
Understanding the effects of Earth’s surface topography on Global Navigation Satellite Systems Reflectometry (GNSS-R) space-borne data is important to calibrate experimental measurements, so as to provide accurate soil moisture content (SMC) retrievals. In this study, several scientific observables obtained from delay-Doppler maps (DDMs) ⟨ | Y r , t o p o ( τ , f ) | 2 ⟩ generated on board the Cyclone Global Navigation Satellite System (CyGNSS) mission were evaluated as a function of several topographic parameters derived from a digital elevation model (DEM). This assessment was performed as a function of Soil Moisture Active Passive (SMAP)-derived SMC at grazing angles θ e ~ [20,30] ° and in a nadir-looking configuration θ e ~ [80,90] °. Global scale results showed that the width of the trailing edge (TE) was small T E ~ [100, 250] m and the reflectivity was high Γ ~ [–10, –3] dB over flat areas with low topographic heterogeneity, because of an increasing coherence of Earth-reflected Global Positioning System (GPS) signals. However, the strong impact of several topographic features over areas with rough topography provided motivation to perform a parametric analysis. A specific target area with little vegetation, low small-scale surface roughness, and a wide variety of terrains in South Asia was selected. A significant influence of several topographic parameters i.e., surface slopes and curvatures was observed. This triggered our study of the sensitivity of T E and Γ to SMC and topographic wetness index ( T W I ). Regional scale results showed that T E and Γ are strongly correlated with the T W I , while the sensitivity to SMC was almost negligible. The Pearson correlation coefficients of T E and Γ with T W I are r Γ ~ 0.59 and r T E ~−0.63 at θ e ~ [20, 30] ° and r Γ ~ 0.48 and r T E ~ −0.50 at θ e ~ [80, 90] °, respectively.
科研通智能强力驱动
Strongly Powered by AbleSci AI