Investigation of the Global Influence of Surface Roughness on Space‐Borne GNSS‐R Observations

Journal of Geophysical Research Biogeosciences, Journal Year: 2025, Volume and Issue: 130(3)

Published: March 1, 2025

Abstract Accurately characterizing the impact of vegetation and roughness on CYGNSS observations, which are two main sources disturbance, is essential for achieving high‐quality estimates soil moisture through this mission. While there several ancillary data sets that can be employed to address influence, lack a global set surface motivates us globally map contribution observations. To accomplish this, since separating reflected signals often challenging, we initially integrate contributions into unique variable, denoted as VR. Next, impacts integrated CYGNSS‐derived VR were separated using Leaf Area Index parameter Hr. The mean value Hr obtained in research observations ranges from 3.2 4.6. We observed spatial distribution values influenced by predominant types, with forests exhibiting higher (Hr = 4.47–4.67), while deserts, shrubs, crops, bare soils exhibit smallest 3.25–3.36). Furthermore, inferred optical depth (VOD) conjunction estimated values. good agreement between VOD study other indices, including Vegetation Water Content tree height, highlights effectiveness introduced our its promising potential future GNSS‐R studies.

Language: Английский

Spaceborne GNSS Reflectometry for Vegetation and Inland Water Monitoring: Progress, Challenges, Opportunities, and Potential

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(7), P. 1199 - 1199

Published: March 27, 2025

Global navigation satellite system reflectometry (GNSS-R) uses the reflection characteristics of signals reflected from earth’s surface to provide an innovative tool for remote sensing, especially monitoring and atmospheric environmental variables, such as wind speed, soil moisture, vegetation, sea ice parameters. This paper focuses on current application future potential spaceborne GNSS-R in vegetation sensing retrieval inland water physical reviews technical progress detail, early feasibility studies multiple examples at this stage, United Kingdom Disaster Monitoring Constellation (UK-DMC) 2003 other recent missions. These cases demonstrate unique advantages terms global coverage, low cost, real-time monitoring. explores technology parameters monitoring, its applications. The article also mentioned that accuracy efficiency parameter can be significantly improved by improving models algorithms, using neural networks data fusion technology. Finally, points out direction environment parameters, including expanding areas a broader range resource management. It emphasized essential role ecosystem resources.

Language: Английский