Deodoro, Sandra Cristina and de Andrade Moral, Rafael and Fealy, Réamonn and McCarthy, Tim and Fealy, Rowan (2024) Using the surface scattering mechanism from dual-pol SAR data to estimate topsoil particle-sizefractions. International Journal of Applied Earth Observation and Geoinformation, 128 (103742). pp. 1-19. ISSN 15698432

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Abstract

Data extracted from Synthetic Aperture Radar (SAR) have been widely employed to estimate soil properties. However, these studies are typically constrained to bare soil conditions, as soil information retrieval in vegetated areas remains challenging. Polarimetric decomposition has emerged as a potentially useful method to separate the scattering contributions of different targets (e.g. canopy/leaves and the underlying soil), which is of significance for areas that are near-permanently covered in low-lying vegetation (e.g. grass) like Ireland – the study area for this investigation. Here, we test the surface scattering mechanism, derived from H-alpha dual-pol decomposition, together with other covariates, to estimate percentages of sand, silt, and clay, over vegetated terrain, using Sentinel 1 data (dual-pol C-band SAR). The statistical modelling approaches evaluated – linear regression (LRM) and tree-based regression models (machine learning) – explicitly consider the compositional nature of soil texture. When compared to the models fitted without surface scattering data, results showed that the inclusion of the surface scattering data improved estimates of silt and clay, with the compositional linear regression model, and estimates of sand and silt fractions with different tree-based models. While not without limitations, our study demonstrated that the polarimetric decomposition method, which is typically used for classification and segmentation purposes, could also be used for soil property estimation, broadening the application of this technique in microwave remote sensing studies.

Item Type:	Article
Additional Information:	The authors thank the National University of Ireland Maynooth (Maynooth University) for the scholarship awarded to the first author (award number 20253119) under the Hume Doctoral Award scheme; and the IReL for providing open access funding. The authors also thank ESA-Copernicus (Europe) for making available the Sentinel images; Teagasc (Ireland), GSI (Ireland), ESDAC (Europe), and ISRIC Foundation (The Netherlands), for providing or making available the required topsoil data to run the models prediction. We also would like to thank Estevao ˜ Batista do Prado (Department of Mathematics and Statistics – Lancaster University-UK) and Antonia Alessandra Lemos dos Santos (Department of Mathematics and Statistics-Hamilton Institute – Maynooth University) for their assistance in coding compositional data in R
Keywords:	Dual-polarimetric decomposition; H-alpha decomposition; Sentinel 1; Sand; Silt; Clay; Soil texture; Compositional;
Academic Unit:	Faculty of Social Sciences > Geography Faculty of Social Sciences > Research Institutes > Irish Climate Analysis and Research Units, ICARUS
Item ID:	18761
Identification Number:	https://doi.org/10.1016/j.jag.2024.103742
Depositing User:	Corinne Voces
Date Deposited:	21 Aug 2024 14:50
Journal or Publication Title:	International Journal of Applied Earth Observation and Geoinformation
Publisher:	Elsevier
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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