Observatorio de I+D+i UPM

Memorias de investigación
Ponencias en congresos:
Soil Aggregates geometry
Año:2011
Áreas de investigación
  • Física química y matemáticas,
  • Ciencias naturales y ciencias de la salud
Datos
Descripción
This work deals with the suitability of the Minkowski functionals [1] and fractals parameters [2] to distinguish the geometry of different soil aggregates when they are imaging with X-ray computed tomography. Data were collected from the Long Term Ecological Research (LTER) site located at Kellogg Bi- ological Station (KBS), Michigan and from Shenyang Experimental Station of Ecology site, Chinese Ecosystem Research Network (CERN) located in northwest China. Soil aggregates come from two LTER treatments. These treatments are: conventional tillage with conventional chemical inputs (T1) and native succession (T7). The native succession treatment has been abandoned from agriculture in 1988. Samples from Chine correspond to two treatments: natural vegetation since 2002 (A) and bare soil since 2002 (C). Aggregate image data were obtained on the bending magnet beam line, station 13-BM-D of the GeoSoilEnvironCARS (GSECARS) at the Advanced Photon Source (APS), Argonne National Labora- tory (ANL), IL. The Si (111) channel cut monochromator tuned to 28 keV incident energy was used. The resulting 3D image had 520 slices with 696x696 pixels per slice and a pixel size of 14.6 microns. Detailed information on the procedure is given in [3]. Figure 1 shows a sectional tomogram of one of the soil ag- gregates samples. Each section were binarized using the intermodes procedure. It is a histogram-based iterative method that assumes a bimodal histogram [4]. Figure 2 shows the corresponding binarized image of the tomogram of figure 1. Data were analyzed using one-way ANOVA with four groups, i.e., T1 and T7 from KBS MI and A and C from CERN China. Normality of the residuals was assessed using normal probability plots. Homogeneity of variances among the groups were assessed using box plots and Levene?s test for unequal variances. When variances appear to be heterogeneous the data were analyzed using unequal variance approach. Aikaike information criterion was used to decide whether the model with equal or unequal variances is most appropriate for the studied variable. The analyses were conducted using PROC MIXED procedure in SAS. The differences between Michigan and Chineese aggregates were difficult to interpret. Michigan soils are of moraine origin and China is loess and they have different management histories, different vege- tation, etc. Significant differences for Minkowski functionals and fractal parameters were encounteredFigure 2: Binarized soil tomogram for different treatments. In particular, what appeared to be most interesting was how different the aggregates are on the inside as measured by connectivity (K), area of the boundary of the object (S), and fractal dimensions of the 3D object (DFV) and fractal dimension of its boundary (DFS).
Internacional
Si
Nombre congreso
Interpore: 3rd International Conference on Porous Media & annual meeting
Tipo de participación
960
Lugar del congreso
Bordeaux (France)
Revisores
Si
ISBN o ISSN
DOI
Fecha inicio congreso
29/03/2011
Fecha fin congreso
31/03/2011
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Título de las actas
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Francisco Javier Muñoz Ortega (UPM)
  • Autor: Fernando San Jose Martinez (UPM)
  • Autor: Alexandra Kravchenko
  • Autor: Wei Wang
  • Autor: Francisco Javier Caniego Monreal (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Departamento: Matemática Aplicada a la Ingeniería Agronómica
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