Work

Phenological Windows for UAV and PlanetScope Monitoring of Greenhouse Gas Fluxes in AWD Rice on the Peruvian North Coast

Year: 2026

Type: article

Abstract: Alternate wetting and drying (AWD) irrigation reduces CH4 emissions from flooded rice but amplifies N2O pulses; identifying candidate phenological windows for the remote screening of greenhouse gas (GHG) fluxes remains challenging with small datasets. In a single-site, single-season exploratory study at INIA Vista Florida (Lambayeque, Peru), eight UAV flights were paired with eight PlanetScope SuperDove scenes (|Δ|≤1 d) and closed-chamber CH4, N2O and CO2 fluxes under four water regimes (CF, AWD5, AWD10, AWD20; 96 sub-plot × date observations). Multivariate explanatory power was assessed by bootstrap Ridge regression on each sensor’s native predictors (VI + GLCM + Tmean for the UAV, VI for PlanetScope). Maximum tillering (79 DAS) emerged as a candidate UAV window, ranking in the top three for all gases through GLCM textures, whereas PlanetScope peaked at Mid-boot and Late-boot (103–107 DAS), with median R2˜UAV at 0.34–0.71 and R2˜Planet at 0.20–0.60. Nested Leave-One-Plot-Out (LOPO) validation gave RCV2 between +0.57 and +0.69 for four of six platform × gas combinations (UAV-CH4 and Planet-N2O stayed weak), and Tmean was decisive for N2O on the UAV (ΔR2=+0.48). Repeating the stage selection inside every LOPO fold preserved the leading combinations and their ranking. These exploratory windows and sensor-native descriptors need multi-site, multi-season validation before operational use.

Source: Remote Sensing

DOI: 10.3390/rs18122011