An advanced photogrammetric method to measure surface roughness: Application to volcanic terrains in the Piton de la Fournaise, Reunion Island F. Bretar a, d, ⁎, M. Arab-Sedze b, c , J. Champion b , M. Pierrot-Deseilligny d , E. Heggy e , S. Jacquemoud b a CETE Normandie Centre, Laboratoire des Ponts et Chaussées, 10 chemin de la Poudrière, BP 90245, 76121 Grand Quevilly, France b Institut de physique du globe de Paris - Sorbonne Paris Cité, Université Paris Diderot, UMR CNRS 7154, Case 7071, 39 rue Hélène Brion, 75013 Paris, France c IGN, Laboratoire MATIS, 73 avenue de Paris, 94160 Saint Mandé, France d Laboratoire de Géomatique Appliquée, IGN/ENSG, 6 et 8 avenue Blaise Pascal, 77455 Marne la Vallée Cedex 2, France e NASA, Jet Propulsion Laboratory, M/S 300-243, 4800 Oak Grove Drive, Pasadena, CA 91109, USA abstract article info Article history: Received 26 October 2012 Received in revised form 16 March 2013 Accepted 22 March 2013 Available online xxxx Keywords: Surface roughness Image correlation Volcanic terrains Roughness anisotropy Microtopography We present a rapid in situ photogrammetric method to characterize surface roughness by taking overlapping photographs of a scene. The method uses a single digital camera to create a high-resolution digital terrain model (pixel size of ~1.32 mm) by means of a free open-source stereovision software. It is based on an auto-calibration process, which calculates the 3D geometry of the images, and an efficient multi-image cor- relation algorithm. The method is successfully applied to four different volcanic surfaces—namely, a′a lava flows, pahoehoe lava flows, slabby pahoehoe lava flows, and lapilli deposits. These surfaces were sampled in the Piton de la Fournaise volcano (Reunion Island) in October, 2011, and displayed various terrain rough- nesses. Our in situ measurements allow deriving digital terrain models that reproduce the millimeter-scale height variations of the surfaces over about 12 m 2 . Five parameters characterizing surface topography are de- rived along unidirectional profiles: the root-mean-square height (ξ), the correlation length (L c ), the ratio Z s = ξ 2 /L c , the tortuosity index (τ), and the fractal dimension (D). Anisotropy in the surface roughness has been first investigated using 1-m-long profiles circularly arranged around a central point. The results show that L c , Z s and D effectively catch preferential directions in the structure of bare surfaces. Secondly, we studied the variation of these parameters as a function of the profile length by drawing random profiles from 1 to 12 m in length. We verified that ξ and L c increase with the profile length and, therefore, are not appropriate to characterize surface roughness variation. We conclude that Z s and D are better suited to extract roughness information for multiple eruptive terrains with complex surface texture. © 2013 Elsevier Inc. All rights reserved. 1. Introduction Surface roughness is a key factor in understanding soil and terrain properties in micrometeorology, agriculture, hydrology, and volcanol- ogy, as well as in planetary sciences. For instance, on cultivated fields it is an excellent indicator of soil sensitivity to wind erosion; it governs infiltration and runoff processes, and water storage; it influences inci- dent radiation distribution and, indirectly, moisture, temperature, and aeration of the soil. This plays an important role in gas exchange and the development of soil biota (e.g., Vidal Vázquez et al., 2005). On weathered rock surfaces it is a measure of fragmentation mechanisms and thermal properties of surfaces (e.g., Tatone & Grasselli, 2009). Together with the dielectric constant (equivalent of the complex refractive index) of materials and the terrain slope, surface rough- ness also controls scattering or emission of electromagnetic waves (Beckmann & Spizzichino, 1987). Its characterization is consequently critical to interpret optical and microwave remote sensing images from both terrestrial and planetary surfaces. However, in situ mea- surement of surface roughness on a distance of some meters remains a challenge due to the necessity to deploy a substantial geophysical setup. Several contact (roller chain, pin profilometer) and noncontact (laser profilometer, terrestrial laser scanner, stereophotogrammetry) techniques have been applied to describe surface microrelief. Many authors have already related how to implement these techniques: the reader is referred to the review paper of Verhoest et al. (2008) for more details. Contact techniques, such as pin profilometers, are difficult to han- dle and use, and their resolution is limited both in vertical and hori- zontal directions (e.g., Dexter, 1977; García Moreno et al., 2008). Moreover, they may alter the microtopography of the soil surface. A laser profilometer consists of a laser which moves along a horizontal Remote Sensing of Environment 135 (2013) 1–11 ⁎ Corresponding author at: Consulat général de France à Shanghai, Service pour la science et la technologie, Haitong Securities Building, 2F, Suite 201, 689 Guangdong lu, 200001 Shanghai, China. E-mail addresses: frederic.bretar@ieee.org (F. Bretar), sedze@ipgp.fr (M. Arab-Sedze), champion@ipgp.fr (J. Champion), marc.pierrot-deseilligny@ensg.eu (M. Pierrot-Deseilligny), heggy@jpl.nasa.gov (E. Heggy), jacquemoud@ipgp.fr (S. Jacquemoud). 0034-4257/$ – see front matter © 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.rse.2013.03.026 Contents lists available at SciVerse ScienceDirect Remote Sensing of Environment journal homepage: www.elsevier.com/locate/rse