Estimating Soil Moisture Distributions across Small Farm Fields with ALOS/PALSAR

Area of Science:

• Earth Observation
• Remote Sensing
• Agricultural Science

Background:

• Traditional satellite remote sensing techniques lack the resolution for small-scale soil moisture estimation.
• The Advanced Land Observing Satellite (ALOS) features the Phased Array L-band Synthetic Aperture Radar (PALSAR) with a 6.5m fine resolution.
• High-resolution radar data offers potential for detailed soil moisture mapping in agricultural areas.

Purpose of the Study:

• To determine the relationship between PALSAR's microwave backscattering coefficient (σ) and ground-based soil moisture.
• To evaluate PALSAR's performance for estimating soil moisture distribution in small-scale farmlands.
• To assess PALSAR's capability in estimating crop coverage ratios.

Main Methods:

• Utilized PALSAR data from the ALOS satellite.
• Conducted ground-based soil moisture measurements using time domain reflectometry in a Japanese cabbage field (2008).
• Analyzed the correlation between PALSAR's backscattering coefficient (σ) and measured soil moisture at multiple layers, as well as crop coverage.

Main Results:

• Soil moisture in the 0-20cm layer showed the highest correlation (r = 0.403) with PALSAR's backscattering coefficient (σ).
• PALSAR's σ values demonstrated a strong correlation with the ground surface coverage ratio by cabbage plants.
• The study confirmed a relationship between PALSAR measurements and soil moisture in the topsoil layer.

Conclusions:

• PALSAR's fine resolution enables the estimation of soil moisture distribution in small farmlands.
• PALSAR can accurately estimate soil moisture in the 0-20cm soil layer for both bare fields and areas with crop coverage.
• The technology is valuable for monitoring agricultural conditions at a fine scale.