The use of suitable pseudo-invariant targets for MIVIS data calibration by the empirical line method Alessandro Mei ⇑ , Cristiana Bassani, Giuliano Fontinovo, Rosamaria Salvatori, Alessia Allegrini National Research Council of Italy, Institute of Atmospheric Pollution Research, Via Salaria Km 29, 300, Monterotondo, RM, Italy article info Article history: Received 14 May 2015 Received in revised form 30 November 2015 Accepted 18 January 2016 Keywords: Empirical line method Pseudo-invariant target MIVIS abstract The Empirical Line Method (ELM) enables the calibration of multi- and hyper-airborne/satellite image converting DN or radiance to reflectance values performed by using at ground data. High quality outcome can be reached with the selection of appropriate Pseudo-Invariant Targets (PIT). In this paper, spectral variability of ‘‘usual” (asphalt and concrete) and ‘‘unusual” (calcareous gravel, basaltic paving, concrete bricks, tartan paving and artificial turf) PITs is retrieved for ELM application. Such PITs are used to cali- brate the Multispectral Infrared and Visible Imaging Spectrometer (MIVIS) airborne sensor in 12 different Runs. Firstly, processing of field spectral data enables the evaluation of pseudo-invariance of targets by studying their spectral changes in space and in time. Finally, these surfaces are used as Ground Calibration (GCT) and Validation Targets (GVT) in ELM. High calibration accuracy values are observed in Visible (VIS) range (98.9%) while a general decrease of accuracy in Near-InfraRed (NIR) (96.6%) and Middle-InfraRed (SWIR) (88.1%) are reached. Outcomes show that ‘‘usual” surfaces as asphalt and con- crete and ‘‘unusual” surfaces such as tartan can be successfully used for MIVIS image calibration. Ó 2016 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved. 1. Introduction The calibration of remotely sensed data removes atmospheric effects and maximizes their quantitative utility for land cover changes monitoring or quantitative analysis (Gao et al., 2006; Karpouzli et al., 2003). Several methods are implemented to retrieve surface reflectance from at sensor radiance such as the covariance matrix method (Ferrier, 1995), the dark pixel/histogram method (Chavez, 1996; Themistocleous and Hadjimitsis, 2013) or physically based algorithm (Bassani et al., 2010). An alternative approach is the Empirical Line Method (ELM), which allows to cal- ibrate multi- and hyper- spectral data from raw DNs or radiances to reflectance values (Ben-Dor et al., 2004). The ELM offers relatively simple calculation of surface reflectance if invariant in-space and in-time target measurements are available. Calibration surfaces with different albedo (dark and brighter) are normally used. Generally, different authors settle that ground target selected surfaces should be homogeneous, pixels sized, with different albedo and ideally spectrally featureless (Clark et al., 2002; Ben- Dor et al., 2004). Asphalt and concrete surfaces are often suggested appropriate as ground calibration targets in the visible and the near-infrared spectral domain (Lawless et al., 1998), while analysis carried out from ground measurements shows significant spectral variability (Lacherade et al., 2005). Clark et al. (2011) and Puttonen et al. (2009) show that the use of Pseudo-Invariant Targets (PIT), such as asphalt surfaces, without detailed knowledge of specific site’s characteristics is not recommended and it is advisable to make field measurements simultaneously or very close to the imagery acquisition time. While several studies suggest the suitability of these kinds of targets to use in ELM by BRDF measurements (Clark et al., 2011; Casselgreen et al., 2007; Sandmeier and Itten, 1999), there is still a gap of knowledge and confusion regarding their spectral and physical features. In fact, while in Themistocleous et al., 2012 black and gray asphalt and concrete surfaces can successfully be used as pseudo-invariant targets throughout the year, Clark et al. (2011) considers new asphalts too spectrally dark to be a calibration target and weathers can quickly modify them. Due to relevant effects such as solar angle, wear and moisture that influence reflectance of ground targets, the evolution of their temporal spectral stability represent a crucial issue. As demon- strated by Anderson and Milton (2006), the comparison of asphalt and concrete absolute reflectance at short-term and long-term http://dx.doi.org/10.1016/j.isprsjprs.2016.01.016 0924-2716/Ó 2016 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved. ⇑ Corresponding author. E-mail address: alessandro.mei@iia.cnr.it (A. Mei). ISPRS Journal of Photogrammetry and Remote Sensing 114 (2016) 102–114 Contents lists available at ScienceDirect ISPRS Journal of Photogrammetry and Remote Sensing journal homepage: www.elsevier.com/locate/isprsjprs