UAV Monitoring Topsoil Moisture in an Alpine Meadow on the Qinghai–Tibet Plateau

Abstract

Soil moisture is one of the most critical soil components for sustained plant growth and grassland management. Unmanned aerial vehicles (UAVs) are gradually replacing manual labor in various aspects of grassland management. However, their potential for monitoring soil moisture in grasslands remains largely unexplored. High vegetation coverage and frequent rainfall in the Tibetan Plateau pose a challenge for personnel working in alpine meadows. To explore the potential of UAV technology for soil moisture detection in these areas, we conducted a rainfall reduction experiment in Maqu County, China to understand the relationships among soil moisture, vegetation coverage, and visible-light images captured using UAVs. The findings indicated a significant correlation between topsoil moisture and the brightness values in visible-light images acquired by UAVs (p < 0.0001). These results demonstrated that visible-light brightness, vegetation coverage, rainfall reduction, and aboveground biomass can be utilized for estimating the topsoil moisture using these images (y = −0.2676 × Brightness + 0.2808 × Vegetation coverage −0.1862 × Rainfall reduction + 0.1357 × Aboveground biomass + 37.77). The model validation worked well (E = 0.8291, RS = −3.58%, RMA = 10.38%, RMSE = 3.5878, Pearson’s r = 0.9631, PSI = 0.0125). This study further addresses the problem of topsoil moisture measurement in flat areas of mesoscale moist alpine meadows and is expected to facilitate the widespread adoption of UAV use in grassland ecology research.