Assessing the chromatic contrast in open surface excavations: a comparative study between subjective and quantitative approaches

The difficulties in the quantification of various aspects of visual impacts, among them the colour contrast, have resulted in delay of the development of effective assessment methodologies for mining operations. Technological evolution in image analysis has boosted the progression of more quantitative approaches. Yet, the critical question on how close the quantitative results are to the perceived colour difference remains an open issue. This paper is one of the few efforts to bridge subjective opinions gathered by a public preference survey with quantitative estimates of three different measurement approaches. Two main conclusions are drawn. First, people tend to compare the colour of the exposed excavation with the colour of the area near the edges of the quarry site. Second, the subjective colour difference is affected by landscape features that cannot be measured in numerical terms from existing image analysis tools.

[1]  Jon Bryan Burley,et al.  Visual Quality/ Aesthetics Modeling for Reclamation/Landscape Disturbance Applications , 1992 .

[2]  Marius Pedersen,et al.  Image quality metrics for the evaluation of printing workflows , 2011 .

[3]  G. Massacci,et al.  Visual impact of quarrying in the Polish Carpathians , 2010 .

[4]  Franz Makeschin,et al.  Assessment of landscape aesthetics—Validation of a landscape metrics-based assessment by visual estimation of the scenic beauty , 2013 .

[5]  Peter G. Engeldrum,et al.  Psychometric Scaling: A Toolkit for Imaging Systems Development , 2000 .

[6]  Dimitris Kaliampakos,et al.  Evaluating mining landscape: A step forward , 2012 .

[7]  F. Müller,et al.  Rural-urban gradient analysis of ecosystem services supply and demand dynamics , 2012 .

[8]  L. Donald,et al.  of the INTERIOR , 1962 .

[9]  Maurice De Sausmarez,et al.  Basic Design: The Dynamics of Visual Form , 1964 .

[10]  T. Daniel Whither scenic beauty? Visual landscape quality assessment in the 21st century , 2001 .

[11]  F. Ayuga,et al.  A contribution to the assessment of scenic quality of landscapes based on preferences expressed by the public , 2009 .

[12]  G. Massacci,et al.  Landscape and Visual Impact Assessment of Opencast Mining , 2004 .

[13]  Christina von Haaren,et al.  Integrating ecosystem services and environmental planning: limitations and synergies , 2011 .

[14]  Valentina Dentoni,et al.  Visibility of surface mining and impact perception , 2005 .

[15]  Brian A. Wandell,et al.  A spatial extension of CIELAB for digital color‐image reproduction , 1997 .

[16]  A. Stamps Use of Photographs to Simulate Environments: A Meta-Analysis , 1990 .

[17]  William C. Sullivan,et al.  Perceptions of the rural-urban fringe: citizen preferences for natural and developed settings , 1994 .

[18]  Ian D. Bishop Testing perceived landscape colour difference using the Internet , 1997 .

[19]  M. Tulder Chapter 1 , 2006, European Spine Journal.

[20]  Dawn T. Nicholson The visual impact of quarrying , 1996 .

[21]  L. E. Richards ENVIRONMENTAL MANAGEMENT IN THE MINERALS INDUSTRY: THEORY AND PRACTICE , 1996 .

[22]  Brian A. Wandell,et al.  Color image fidelity metrics evaluated using image distortion maps , 1998, Signal Process..

[23]  Dimitris Kaliampakos,et al.  Landscape Analysis as a Tool for Surface Mining Design , 2006 .

[24]  Brian A. Wandell,et al.  Color image quality metric S-CIELAB and its application on halftone texture visibility , 1997, Proceedings IEEE COMPCON 97. Digest of Papers.

[25]  Valentina Dentoni,et al.  Assessment of visual impact induced by surface mining with reference to a case study located in Sardinia (Italy) , 2013, Environmental Earth Sciences.