A GNSS-IR Aided Multispectral Satellite Data Fusion for Meter-Level Wide-Area Volumetric Soil Moisture Estimation
Nicolás Padrón, Sergiy A. Vorobyov
Abstract
Earth Observation (EO) data is captured with different instruments and available in multiple formats. The complementation of two passive remote sensing approaches in local small areas is performed here to produce a single, large-area coverage, volumetric soil moisture (VSM) solution. The sensing approaches under consideration are GNSS Interferometric Reflectometry (GNSS-IR), which is a local land-based microwave remote sensing approach that exploits ground-reflected navigation signals; and also multispectral satellite imagery, which is a space-based optical remote sensing approach that allows to analyze the spectral response of surface materials. The focus is on the processing of GNSS-IR outputs aiding a multispectral model using Landsat-8 data. The aim is to provide an accurate, cost-effective solution with wide-area coverage. Landsat-8 spectral indexes highly correlated with soil moisture are fused with GNSS-IR VSM on multiple terrain types. The proposed solution is demonstrated and verified against data from the Soil Moisture Active Passive (SMAP) satellite mission over large-areas.
BibTeX
@inproceedings{icassp2025_agnssiraidedmult,
title = {A GNSS-IR Aided Multispectral Satellite Data Fusion for Meter-Level Wide-Area Volumetric Soil Moisture Estimation},
author = {Nicolás Padrón and Sergiy A. Vorobyov},
booktitle = {ICASSP 2025},
year = {2025}
}