On the characterization of agricultural soil roughness for radar remote sensing studies

Malcolm Davidson (Corresponding Author), Thuy Le Toan, Francesco Mattia, G. Satalino, Terhikki Manninen, Maurice Borgeaud

Research output: Contribution to journalArticleScientificpeer-review

250 Citations (Scopus)


The surface roughness parameters commonly used as inputs to electromagnetic surface scattering models (SPM, PO, GO, and IEM) are the root mean square (RMS) height s, and autocorrelation length l. However, soil moisture retrieval studies based on these models have yielded inconsistent results, not so much because of the failure of the models themselves, but because of the complexity of natural surfaces and the difficulty in estimating appropriate input roughness parameters. In this paper, the authors address the issue of soil roughness characterization in the case of agricultural fields having different tillage (roughness) states by making use of an extensive multisite database of surface profiles collected using a novel laser profiler capable of recording profiles up to 25 m long. Using this dataset, the range of RMS height and correlation values associated with each agricultural roughness state is estimated, and the dependence of these estimates on profile length is investigated. The results show that at spatial scales equivalent to those of the SAR resolution cell, agricultural surface roughness characteristics are well described by the superposition of a single scale process related to the tillage state with a multiscale random fractal process related to field topography.
Original languageEnglish
Pages (from-to)630-640
JournalIEEE Transactions on Geoscience and Remote Sensing
Issue number2
Publication statusPublished - 2000
MoE publication typeA1 Journal article-refereed


  • remote sensing


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