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Bi-dimensional soil roughness measurement by photogrammetry for SAR modeling of agricultural surfaces

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Abstract
In the description of soil roughness for SAR monitoring, the hypothesis of surface isotropy was currently admitted and in-situ roughness measurements were recorded along linear profiles. However, this paper showed for agricultural soil surfaces this hypothesis is not valid and anisotropic surface must be assumed. Stereoscopic pairs of vertical photographs were acquired to produce Digital Elevation Models (DEM) for the soil roughness description. This paper presents a measurements method to describe the bi-dimensional soil roughness and discuss 3 advantages of the photogrammetric method compared to the linear measurements. (i) A high variability of the roughness parameters estimated by linear profiles m as observed. Using the DEM, a high number of profiles were drawn for a given direction. A more accurate estimation of rms and correlation length was obtained averaging several profiles. (ii) The anisotropy were measured and represented by it directional variograms. (iii) The anisotropic roughness were decomposed in 2 models: the isotropic random roughness and the anisotropy induced by, the sowing-rows.
Keywords
soil roughness, BACKSCATTERING, anisoptropy photogrammetry

Citation

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Chicago
Blaes, X, P Defourny, M Callens, and Niko Verhoest. 2004. “Bi-dimensional Soil Roughness Measurement by Photogrammetry for SAR Modeling of Agricultural Surfaces.” In IEEE International Symposium on Geoscience and Remote Sensing (IGARSS), 4038–4041. New York, NY, USA: IEEE.
APA
Blaes, X., Defourny, P., Callens, M., & Verhoest, N. (2004). Bi-dimensional soil roughness measurement by photogrammetry for SAR modeling of agricultural surfaces. IEEE International Symposium on Geoscience and Remote Sensing (IGARSS) (pp. 4038–4041). Presented at the IEEE International Geoscience and Remote Sensing Symposium, New York, NY, USA: IEEE.
Vancouver
1.
Blaes X, Defourny P, Callens M, Verhoest N. Bi-dimensional soil roughness measurement by photogrammetry for SAR modeling of agricultural surfaces. IEEE International Symposium on Geoscience and Remote Sensing (IGARSS). New York, NY, USA: IEEE; 2004. p. 4038–41.
MLA
Blaes, X, P Defourny, M Callens, et al. “Bi-dimensional Soil Roughness Measurement by Photogrammetry for SAR Modeling of Agricultural Surfaces.” IEEE International Symposium on Geoscience and Remote Sensing (IGARSS). New York, NY, USA: IEEE, 2004. 4038–4041. Print.
@inproceedings{2036882,
  abstract     = {In the description of soil roughness for SAR monitoring, the hypothesis of surface isotropy was currently admitted and in-situ roughness measurements were recorded along linear profiles. However, this paper showed for agricultural soil surfaces this hypothesis is not valid and anisotropic surface must be assumed. Stereoscopic pairs of vertical photographs were acquired to produce Digital Elevation Models (DEM) for the soil roughness description. This paper presents a measurements method to describe the bi-dimensional soil roughness and discuss 3 advantages of the photogrammetric method compared to the linear measurements. (i) A high variability of the roughness parameters estimated by linear profiles m as observed. Using the DEM, a high number of profiles were drawn for a given direction. A more accurate estimation of rms and correlation length was obtained averaging several profiles. (ii) The anisotropy were measured and represented by it directional variograms. (iii) The anisotropic roughness were decomposed in 2 models: the isotropic random roughness and the anisotropy induced by, the sowing-rows.},
  author       = {Blaes, X and Defourny, P and Callens, M and Verhoest, Niko},
  booktitle    = {IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)},
  isbn         = {9780780387423},
  keyword      = {soil roughness,BACKSCATTERING,anisoptropy photogrammetry},
  language     = {eng},
  location     = {Anchorage, AK, USA},
  pages        = {4038--4041},
  publisher    = {IEEE},
  title        = {Bi-dimensional soil roughness measurement by photogrammetry for SAR modeling of agricultural surfaces},
  year         = {2004},
}

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