1887
Volume 14 Number 4
  • ISSN: 1569-4445
  • E-ISSN: 1873-0604

Abstract

ABSTRACT

A wide variety of remote sensing and ground‐based (proximal sensing) methods have been developed to describe soil physical properties and their lateral variations. Remote sensing enables the estimation of soil properties over large areas, but the information is often limited to the soil surface. Ground‐based methods enable the derivation of soil properties for the whole soil column thickness, although these methods cannot be conducted over large areas. The aim of the present study is to contribute to the assessment of the efficacy of airborne thermal prospection over bare soils in soil mapping. This study focuses on a comparison between this technique, which can investigate over the whole soil column thickness after a sufficiently long transient heat exchange period, and pedo‐logical and electrical resistivity data that were recorded for three different depths of investigation.

The study area is located in the Beauce region, where the soils (haplic Calcisol or calcaric Cambisol) consist of a loamy–clay layer that is 0.3 m–1.4 m thick and overlies Tertiary Beauce limestone. Thermal measurements were recorded by ARIES radiometer in December, after six days of heat loss from the ground. The investigation depth could thus be considered to be larger than the thickness of the ploughed layer. Comparisons using statistical analyses between the thermal measurements, electrical resistivity, and pedological data demonstrated that: (i) the spatial organization of the thermal inertia map is similar to the spatial organization of the 0‐m to 1.7‐m resistivity map; and (ii) the thermal apparent inertia values are significantly different between the haplic Calcisols and the calcaric Cambisols and can thus be mapped with a high spatial resolution over large areas. The applicability of thermal prospecting in soil mapping opens up many possibilities considering the present advances in light‐infrared radiometers. Beside agronomical concerns, this methodology will also facilitate progress in engineering applications, including the cross‐estimation of electrical and thermal properties.

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References

  1. AFNOR.2003. Qualité du sol ‐ Détermination de la distribution granu‐lométrique des particules du sol. Méthode à la pipette. Norme française NF X 31‐107, Septembre 2003.Indice de classementX31‐107.
    [Google Scholar]
  2. BeaufrèreP., DabasM., DécriaudJ.P. and TabbaghA.1999. Application de la thermographie aéroportée à la prospection archéologique.Revue archéologique de Picardie17, 289–293.
    [Google Scholar]
  3. BessonA., SegerM., GiotG. and CousinI.2013. Identifying the characteristic scales of soil structural recovery after compaction from three in‐field methods of monitoring.Geoderma204–205, 130–139.
    [Google Scholar]
  4. BourennaneH., CouturierA., PasquierC., ChartinC., HinschbergerF., MacaireJ.J. et al. 2014. Comparative performance of classification algorithms for the development of models of spatial distribution of landscape structures.Geoderma119–220, 136–144.
    [Google Scholar]
  5. ChouduryB.J., IsdoS.B. and ReginatoR.J.1986. Analysis of a resistance‐energy balance method for estimating daily evaporation from wheat plot using one‐time‐of‐day infrared temperature observation.Remote Sensing of Environment19, 253–268.
    [Google Scholar]
  6. CousinI., BessonA., BourennaneH., PasquierC., NicoullaudB., KingD. and RichardG.2009. From spatial‐continuous electrical resistivity measurements to the soil hydraulic functioning at the field scale.Comptes Rendus Geoscience341, 859–867.
    [Google Scholar]
  7. DabasM.2009. Theory and practice of the new fast electrical imaging system ARP©. In: Seeing the Unseen, Geophysics and Landscape Archaeology (eds S.Campana and S.Piro ), pp. 105–126. CRC Press, Taylor and Francis Group.
    [Google Scholar]
  8. FourteauA.M. and TabbaghA.1979. Parcellaire fossile et prospection thermique: résultat des recherches à Lion en Beauce (Loiret).Revue d’Achéométrie3, 115–123.
    [Google Scholar]
  9. GauthierF. and TabbaghA.1994. The use of airborne thermal remote sensing for soil mapping: A case study in the Limousin Region (France).International Journal of Remote Sensing15(10), 1981–1989.
    [Google Scholar]
  10. GebbersR., LückE., DabasM. and DomschH.2009. Comparison of instruments for geoelectrical soil mapping at the field scale.Near Surface Geophysics7, 179–190.
    [Google Scholar]
  11. HilkerT., HallF.G., CoopsN.C., ColtazJ.G., BlackT.A., TuckerC.J. et al. 2013. Remote sensing of transpiration and heat fluxes using multi‐angle observations.Remote Sensing of Environment137, 31–42.
    [Google Scholar]
  12. ISO 10693. 1995. Determination of carbonate content.Volumetric method. ISO 10693: 7p.
    [Google Scholar]
  13. IUSS Working Group WRB.2006. World reference base for soil resources 2006.World Soil Resources Reports No. 103. FAO, Rome, ftp://ftp.fao.org/agl/agll/docs/wsrr103e.pdf.
    [Google Scholar]
  14. KahleA. and RowanL.C.1980. Evaluation of multispectral middle infrared aircraft images for lithologic mapping in the East Tintic Mountains, Utah.Geology8, 234–239.
    [Google Scholar]
  15. KappelmeyerO.1957. The use of near surface temperature measurements for discovering anomalies due to causes at depths.Geophysical Prospecting5(3), 239–258.
    [Google Scholar]
  16. KatoS., MatsunagaT. and TonookaH.2014. Statistical and in‐situ validations of the ASTER spectral emissivity product at Railroad Valley, Nevada, USA.Remote Sensing of Environment145, 81–92.
    [Google Scholar]
  17. KrcmarB. and MasinJ.1970. Prospecting by the geothermic method.Geophysical Prospecting18(2), 255–260.
    [Google Scholar]
  18. MallickK., JarvisA.J., BoeghE., FisherJ.B., DreweryD.T., TuK.P. et al. 2014. A surface temperature initiated closure (STIC) for surface energy balance fluxes.Remote Sensing of Environment141, 243–261.
    [Google Scholar]
  19. MéhéniY., GuérinR., BenderitterY. and TabbaghA.1996. Subsurface DC resistivity mapping: Approximate 1D interpretation.Journal of Applied Geophysics34, 255–270.
    [Google Scholar]
  20. MoeysJ., NicoullaudB., DorignyA., CoquetY. and CousinI.2006. Cartographie des sols à grande échelle: Intégration explicite d’une mesure de résistivité apparente spatialisée à l’expertise pédologique.Etude et Gestion des Sols13(4), 269–286.
    [Google Scholar]
  21. MongeJ.L. and SirouR.1975. ARIES: un radiomètre multi‐canal à balayage. 5th Spatial Optics meeting, Société Française d’Optique, Marseille, France, June 1975, library of L.M.D., Ecole Polytechnique. Palaiseau, France, 14 pp.
    [Google Scholar]
  22. NicholsS., ZhangY. and AhmadA.2011. Review and evaluation of remote sensing methods for soil moisture estimation.SPIE Reviews2, 028001, doi:10.1117/1.3534910.
    [Google Scholar]
  23. NicoullaudB., CouturierA., BeaudoinN., MaryB., CoutadeurC. and KingD.2004. Modélisation spatiale à l‘échelle parcellaire des effets de la variabilité des sols et des pratiques culturales sur la pollution nitrique agricole. In: Organisation Spatiale des Activités Agricoles et Processus Environnementaux (eds P.Monestiez , S.Lardon , and B.Seguin ), pp. 143–161. Collection Science Update, INRA Editions.
    [Google Scholar]
  24. PanissodC., DabasM., JolivetA. and TabbaghA.1997. A novel mobile multipole system (MUCEP) for shallow (0–3m) geoelectrical investigation: the ‘Vol‐de‐canards’ array.Geophysical Prospecting45, 983–1002.
    [Google Scholar]
  25. PérissetM.C. and TabbaghA.1981. Interpretation of thermal prospection on bare soils.Archaeometry23(2), 169–187.
    [Google Scholar]
  26. PriceJ.C.1977. Thermal inertia mapping: a new view of the earth.Journal of Geophysical Research82(18), 2582–2590.
    [Google Scholar]
  27. SalisburyJ.W., WaldA. and D’AriaD.1994. Thermal infrared remote sensing and Kirchhoff’s law 1. Laboratory measurements.Journal of Geophysical Research99(B6), 11897–11911.
    [Google Scholar]
  28. SamouëlianA., CousinI., TabbaghA., BruandA. and RichardG.2005. Electrical resistivity survey in soil science: A review.Soil & Tillage Research83, 173–193.
    [Google Scholar]
  29. SchlerfM., RockG., LagueuxP., RonellenfitschF., GehardsM., HoffmannL. et al. 2012. A hyperspectral thermal infrared imaging instrument for natural resources applications.Remote Sensing4, 3995–4009.
    [Google Scholar]
  30. ScollarI., TabbaghA., HesseA. and HerzogI.1990. Archaeological Prospecting and Remote Sensing. Cambridge University Press, 674 pp.
  31. SegerM., CousinI., FrisonA., BoizardH. and RichardG.2009. Characterisation of the structural heterogeneity of the soil tilled layer by using in situ 2D and 3D electrical resistivity measurements.Soil & Tillage Research103(2), 387–398.
    [Google Scholar]
  32. SinghN.D., KuriyanS.J. and ChakravarthyM.C.2001. A generalized relationship between electrical and thermal resistivities.Experimental Thermal and Fluid Science25, 175–181.
    [Google Scholar]
  33. TabachnickB.G. and FidellL.S.1996. Using Multivariate Statistics. New York: Harper Collins.
  34. TabbaghA.1973. Essai sur les conditions d’application des mesures thermiques à la prospection archéologique.Annales de Géophysique29, 179–188.
    [Google Scholar]
  35. TabbaghA.1976. Les propriétés thermiques des sols: Premiers résultats utilisables en prospection archéologique.Archaeo‐Physika6, 127–149.
    [Google Scholar]
  36. TomassoneR., DanzartM., DaudinJ.J. and MassonJ.P.1988. Discrimination et Classement. Paris: Masson.
  37. Viscarra RosselR.A.
    , McBratneyA. and MinassyB. (eds) 2010. Proximal Remote Sensing. Springer, 448p.
  38. WatsonK., RowanL.C., BowersT.L., Anton‐PacheoC., GumielP. and MillerS.H.1996. Lithologic analysis from multispectral infrared data of the alkali rock complex at Iron Hill, Colorado.Geophysics61 (3), 706–721.
    [Google Scholar]
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