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Coupling two radar backscattering models to assess soil roughness and surface water content at farm scale
Authors:F Capodici  A Maltese  G Ciraolo  G La Loggia  G D’Urso
Institution:1. Dipartimento di Ingegneria Civile, Ambientale, Aerospaziale, dei Materiali (DICAM), Università degli Studi di Palermo, Viale delle Scienze Ed. 8 , I-90128 Palermo, Italy capodici@idra.unipa.it;3. Dipartimento di Ingegneria Civile, Aerospaziale, dei Materiali (DICAM), Università degli Studi di Palermo, Viale delle Scienze Ed. 8 , I-90128 Palermo, Italy;4. Dipartimento di Agraria, Università di Napoli “Federico II”, Via Università 100 , I-80055 Portici, NA, Italy
Abstract:Abstract

Remote sensing techniques are useful for agro-hydrological monitoring at the farm scale because the availability of spatially and temporally distributed data improves agricultural models for irrigation and crop yield optimization under water scarcity conditions. This research focuses on the surface water content retrieval using active microwave data. Two semi-empirical models were chosen as these showed the best performances in simulating cross and co-polarized backscatter. Thus, these models were coupled to obtain reliable assessments of both soil water content and soil roughness. The use of the coupled model enables one to avoid using roughness measured in situ. Remote sensing images and in situ data were collected between April and July 2006 within the European Space Agency-funded project AgriSAR 2006. The images data set includes L-band in HH, VV and VH polarizations acquired from the airborne E-SAR sensor, operated by the German Aerospace Centre. Results were validated using in situ soil water content and roughness measurements. The results show that reliable assessment of both soil roughness (r 2 up to ?0.8) and soil water content (r 2 ? 0.9) can be retrieved in fields characterized by low fractional coverage.

Editor D. Koutsoyiannis; Associate editor C. Onof

Citation Capodici, F., Maltese, A., Ciraolo, G., La Loggia, G., and D’Urso, G., 2013. Coupling two radar backscattering models to assess soil roughness and surface water content at the farm scale. Hydrological Sciences Journal, 58 (8), 1677–1689.
Keywords:backscattering  soil water content  surface roughness  vegetation indices
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